Quantum-Si Incorporated - Ordinary Shares - Class A Stock

Thank you. Good day and thank you for standing by. Welcome to the Quantum SI Second Quarter 2026 Earnings Call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during this session, you'll need to press star 1 1 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 1 1 again.

Please be advised that today's conference is being recorded. I'd now like to turn the conference over to Risa Lindsay.

Good afternoon, everyone, and thank you for joining us. Earlier today, Quantum SI released financial results for the second quarter and six months ended June 30th, 2026. A copy of the press release is available on the company's website. Joining me today are Jeff Hawkins, our President and Chief Executive Officer, as well as Jeff Kyes, our Chief Financial Officer. Before we begin, I would like to remind you that management will be making certain forward-looking statements within the meaning of the federal securities laws. These statements involve material risks and uncertainties that actual results or events to materially differ from those anticipated. Additional information regarding these risks and uncertainties appears in the section entitled Forward Looking Statements of our press release.

For a more complete list and description of risk factors, please see the company's filings made with the Securities and Exchange Commission. This conference call contains time-sensitive information that is accurate only as of the live broadcast date today, August 13th, 2026 at 1.30 PM Pacific time. Except as required by law, the company disclaims any intention or obligation to update or revise any forward-looking statements. During this call, we will also be referring to certain financial measures that are not prepared in accordance with U.S. generally accepted accounting principles or GAAP. The reconciliation of these non-GAAP financial measures to the most directly comparable GAAP financial measures is included in the press release filed earlier today.

With that, let me turn the call over to Jeff Hawkins. Good afternoon, and thank you for joining us. On today's call, we will provide a business update and review our operating results for the second quarter of 2026. After that, we will open the call for questions. Before diving into specific updates, I want to address at a high level the Proteus roadmap update we announced earlier today. We have updated the Proteus launch timeline from the end of 2026 to the second quarter of 2027. The primary driver of the change is the decision to add an additional integrated instrument design cycle to the program prior to moving to production.

In connection with this roadmap review, we have also made program leadership and governance changes to strengthen accountability, improve technical oversight, and ensure the Proteus program is managed against clear product readiness gates. Furthermore, we are taking operating expense actions in parallel with this roadmap update that are designed to reduce our cash burn and align our cost structure with the revised timeline while preserving investments in the highest priority Proteus workstreams. Our conviction in Proteus remains strong. We have generated sufficient sequencing data from integrated units that we remain confident in the underlying technology. Thank you. That said, we are taking these actions now because we believe it is more responsible and capital efficient to de-risk the platform before production than to move forward before product readiness is fully demonstrated. Focusing on the customer experience at launch is the most important thing we can do to protect the long-term value of the Proteus platform. The remainder of the call will be organized around our three corporate priorities for 2026, which are as follows. deliver Proteus with the capabilities customers need to prepare the market for Proteus launch and to preserve our financial strength.

Our first priority is to deliver Proteus with the capabilities customers need. First, let's start by diving a bit deeper into the instrument development. In 2025, we built and tested Proteus prototypes. first half of 2026, we built and began testing integrated units. Those integrated units have generated valuable learnings about both manufacturing processes and system level performance that prototypes could not fully provide. Based on that testing, we concluded that moving directly from the current integrated unit design to production would carry more execution risk than we are comfortable with taking. therefore adding an additional integrated instrument design cycle before moving into production. The purpose of this additional design cycle is to reduce manufacturing risk, improve system repeatability, strengthen product readiness, and to ensure a positive customer experience at launch. We are making this decision now because we believe it is more responsible and more capital efficient to de-risk the platform before production than to scale prematurely and put the customer experience at risk.

Finally, I want to reiterate that we have generated sufficient sequencing data from integrated units that we remain confident in the underlying technology. Turning now to recognizer development, we communicated on our first quarter earnings call that our internal developmental sequencing kit was able to detect 17 amino acids. progress in this area and the pace of improvement we are seeing has continued to meet our expectations. Given the revised instrument timeline, we will be able to progress even further in this area before locking the reagent formulation for launch. We believe that with this additional time, we will be in a strong position to deliver Proteus with a detection capability of either 19 or 20 amino acids at launch. We will have greater clarity on this. specific reagent configuration when we get closer to launch. Finally, I want to share an important update on our library preparation strategy. As a reminder, library preparation is the process used to prepare a customer sample for sequencing.

Our kit performs two key functions, digesting proteins into peptides and attaching a linker to those peptides. That linker enables each peptide to attach to the bottom of the nanowells on our sequencing array where it can be sequenced as a single molecule. Historically, we approached library preparation as a general purpose kit intended to work across the broad range of proteins and applications. One of the important benefits of having our first generation platinum system in the market is that we have gained significant real-world insight into how different proteins behave during library preparation. as well as customer needs across a range of applications. Through our work supporting Platinum customers, we have also developed improvements and add-on capabilities related to library preparation, both internally and, in some cases, in collaboration with customers. These learnings have led us to an important strategic shift, evolving from a single generic kit to a suite of application-oriented kits that can be used individually or in combination to optimize sequencing performance for specific customer use cases. We believe this strategy provides two key advantages.

First, by giving customers more complete off-the-shelf tools tailored to their applications, we can make implementation more efficient and reduce the amount of customer optimization required. Second, this approach allows our development teams to deliver a broad range of capabilities faster and with lower technical risk. Developing kits around more specific application needs is less complex than trying to make one generic kit, which performs optimally across every protein type and workflow. We are excited about this strategy and believe it positions us to bring new library preparation capabilities to market in connection with the Proteus launch. Our second corporate priority is to prepare the market for Proteus launch. As a reminder, during 2025, we launched a placement program for our first generation Platinum system. This program allows customers to access the platinum instrument in their own labs without needing to secure budget for an upfront capital purchase.

Through this program, we have gained important market and technical insights that give us increasing confidence in the opportunity for protein sequencing and in the alignment between customer requirements and our target specifications for Proteus. First, we have had the opportunity to work with customers across a broad range of applications spanning academic research and biopharma. One recent example is work we have been doing with a BioPharma customer in Europe on the application of protein sequencing to adeno-associated viral vectors, or AAV serotyping. AAVs are commonly used as delivery vehicles in gene therapy, and the presence and relative abundance of different AAV serotypes is important to therapy performance. This application is well suited to protein sequencing because the differences between AAV serotypes often involves only a small number of amino acid differences. With platinum, we have been able to demonstrate the ability to detect relevant amino acid differences. However, due to the limited sequencing output of platinum, we did not reach the sensitivity required for routine use in that customer workflow.

Importantly, using the platinum data, we were able to model expected performance on Proteus based on its planned increase in number of nanowells, and that model suggests the customer sensitivity requirement is achievable on Proteus. Based on readily available market data, there are more than 150 biotech and pharmaceutical companies developing gene therapies that use AAVs for delivery, suggesting that this single application could represent an attractive market opportunity for Proteus. The second important learning from our platinum commercial activities is the potential opportunity in non-human proteomics. Earlier this year, researchers at the U.S. Naval Research Laboratory published data using our single molecule protein sequencing technology for novel pathogen and toxin detection. Over the past few months, we have been working with multiple customers applying protein sequencing to agricultural applications, pathogen detection and typing, and viral protein surveillance applications. We have identified two important features of non-human proteomics that make it especially interesting for Proteus. many of these markets are not well served by traditional techniques such as immunoassays or western blots.

Second, in many applications, customers need a technology that does not depend on a defined reference because the pathogen or protein of interest may evolve through small changes including single amino acid differences. We believe these market features align well with the core capabilities we are designing into Proteus. based on readily available market data and looking specifically at the pathogen research and agricultural research markets where our platinum work has given us a clearer understanding of customer needs. We believe the non-human proteomics market opportunity for Proteus is substantial at more than $4 billion annually. We believe this is a conservative estimate because it does not include additional segments such as environmental, animal health, industrial, or food applications where we believe there may be meaningful future opportunity, but where our understanding of the specific customer needs and fit for protein sequencing is still developing. Finally, I want to provide a brief update on our commercial initiatives to build awareness of Proteus in advance of launch. Commercial team has been executing well, and we continue to receive very positive feedback on Proteus and the wide range of applications it is designed to address. To date, we have identified and qualified more than 250 unique institutions with stated interest in Proteus and the capabilities we are aiming to deliver. and institutions span multiple market segments, including academic research, biopharma, and industrial applications, and they have asked to be updated as new information and data become available.

We will continue to provide updates on this important market development initiative as we progress toward the Proteus launch. Our third priority is to preserve our financial strength. As I stated earlier, the operating expense actions we communicated today are intended to reduce cash burn, extend our runway, and align our cost structure with the revised Proteus timeline while preserving investments in the highest priority workstreams required for launch. We are making these decisions as a matter of fiscal discipline. Our focus is to concentrate resources on the activities that most directly improve Proteus readiness, de-risk the platform before production, and allow us to fund that work responsibly over the extended timeline.

I will now turn the call over to Jeff to review our financial results. Thanks, Jeff. I'll now review our second quarter and first half financial results this discuss the expected financial impact of the operating expense actions we announced today, and then provide an update on our full year outlook. Revenue in the second quarter of 2026 was $344,000 compared to $591,000 in the second quarter of 2025. Revenue for the first six months of 2026 was $602,000 compared to $1.4 million in the prior year period. Results continue to reflect the dynamics we have discussed throughout 2026, including limited near-term capital purchasing activity for platinum, ongoing consumable utilization for our installed base, customer awareness of the anticipated Proteus launch, and deliberate commercial decisions designed to position customers for for a successful transition to Proteus. Gross profit was 172,000 in the second quarter of 2026, resulting in gross margin of 50%. For the first six months of 2026, gross profit was 246,000, resulting in gross margin of 41%.

Gross margin continues to be affected by the mix in timing of instrument, consumable, and service revenue, as well as the commercial choices we are making to support the market readiness for Proteus. Turning to expenses, GAAP total operating expenses for the second quarter of 2026 were $25.8 million compared to $30.5 million in the second quarter of 2025. the adjusted operating expenses were $22.6 million compared to $23.8 million in the prior year quarter. For the first six months of 2026, GAAP total operating expenses were $49.9 million and adjusted operating expenses were $43.9 million. We continue to manage expenses with discipline while prioritizing the investment required to complete Proteus development. scale internal testing, support manufacturing readiness, and prepare the commercial organization for launch. As part of this disciplined approach, earlier today we announced operating expense actions, including a targeted reduction in force representing approximately 20% of the total company headcount. These actions are designed to better align our expense base with the updated Proteus development plan, reduce cash usage, extend our runway, and provide additional flexibility as we execute the remaining product readiness work. In making these decisions, we were deliberate in preserving investment in the highest priority work streams required for the Proteus launch.

We expect these actions, once complete, to result in approximately $12 million of annual operating expense savings. Net loss was $23.5 million in the second quarter of 2026 compared to a net loss of $28.8 million in the same period of the prior year. Adjusted EBITDA was negative 21.2 million compared to negative 22.2 million in the prior year quarter. Dividend and interest income was 1.7 million compared to 2.3 million in the prior year quarter, reflecting the rate environment and changes in vested balances. As of June 30th, 2026, we had $169.9 million in cash, cash equivalents, and investments in marketable securities. Taking into account the reduction in force and other operating expense management actions, we now believe we have sufficient capital to support the updated Proteus plan, execute the key activities required for launch, and fund operations into the fourth quarter of 2028. This runway allows us to remain focused on the highest return uses of capital, including platform readiness, customer sample evaluations, manufacturing readiness, and commercial launch execution.

Our full year 2026 outlook remains focused on three financial priorities. maintaining spending discipline, funding the activities required to deliver Proteus with the capabilities customers need, and preserving the balance sheet strength necessary to support launch and adoption. For the full year 2026, we're reiterating guidance of revenue of approximately $1 million, adjusted operating expenses of $98 million or less, and total cash usage of $93 million or less. The key financial takeaway is that we are aligning our capital allocation with the updated Proteus Development Plan. Prevised launch timing allows us to complete the additional design, testing, and readiness work needed before production, while the operating expense actions announced today are intended to fund that work in a disciplined manner. We're also continuing to invest in the activities that support customer confidence ahead of the launch, including evidence generation with platinum, Proteus awareness initiatives, customer sample evaluations, and targeted commercial engagement. Taken together, these actions are designed to reduce cash usage, extend a runway, and preserve the financial flexibility needed to execute the Proteus launch plan effectively. In summary, we remain focused on using capital efficiently, funding the critical path to Proteus launch, and making the right long-term trade-offs to support the adoption of the Proteus platform.

With that, operator, please open the line for questions. As a reminder, if you'd like to ask a question at this time, please press star one one on your touchtone phone, and wait for your name to be announced. To withdraw your question, please press star one one again. Our first question today will come from Scott Henry with Alliance Global Partners.

Thank you and good afternoon. I'm going to start with a couple big picture questions. I recognize you probably answered this perhaps in more detail, but I'm just looking for kind of a... you know, top down, higher level thought, you know, what drove the change? Did it come from customers or, you know, as you were working through it, did you just say, hey, you know, if we make these changes, it'll be that much more of an effective product?.

Yes, Scott, it's a good question. It comes from our internal assessment. You know, it's a mix of just the performance we're seeing in terms of repeatability and consistency across the machines we have, thinking about what the manufacturing processes have looked like all the way from the optical module and its sort of yields and success rates into the integrated machines, looking at that and saying what improvements are necessary to have a very high quality repeatable manufacturing and supply chain, looking at long lead components and planning those out. It's really us thinking through all of those things and saying to have the highest likelihood of success to ensure that this is the machine that customers expect, performs the way we want, can manufacture it and deliver it consistently, we believed we needed to add this additional cycle. It wasn't driven by some sort of new feedback from customers that caused us to believe we need to add some capabilities we weren't planning for. It's really an internally driven assessment of where we are and the best way to get to the product with the capabilities and manufacturing quality we expect.

Okay, great. That's helpful. And with regards to the target of 2Q27, do you feel pretty comfortable in that number? How much risk is there to that date, I should say?.

Yes, Scott, it's a good question. It's a complex development program, so you're never 100% sure of anything. That said, I can tell you that we completed a very thorough review of the program. We took all the learnings from both prototypes and integrated unit testing. into consideration. We've added this design cycle that really helps us to retire a lot of key risk before we move into production. And then we, as we mentioned in our prepared remarks, really stepped up some of the program management side, the things we're doing to have even higher oversight and governance. you know, including from my role, you know, in this project. So I think when you take all those together, you know, based on everything we know, we think we factor that in, that the timeline of Q2 reflects the work required to deliver the product that meets our standards.

And that's, you know, sort of how we landed on that date.

Okay, great. And then, you know, another big picture question. I think everyone understands the enormity of the proteomics market in the different applications and how each one individual can be a blockbuster indication. But the question is, your new products, they tend to have something that leads the way, a hook. And do you get a sense of, when you go to launch it, what the hook for it is? the Proteus is going to be, who are going to be the main initial users, adopters of the technology, or maybe it'll be a mix of multiple. I just wanted to get your thought on that early adoption.

Yes, I think so of a couple things. I think naturally with any new product launch and we saw this even in the very earliest days of platinum, you're going to have some number of customers often in the academic research space who are going to adopt the new technology and sort of explore its capabilities. and its edges of performance. I think there's always going to be some number of those folks. That's obviously not your big sort of user base for the long haul, but they certainly are there in the early days. I think as we look at where are more of those applications market segments where you can edit, sort of have that initial hook. I sort of would think of it in two ways. One is clearly in the academic research environment, our ability to have very high coverage of proteins, be able to address the most studied post-translational modifications.

Those types of things fit very well into sort of that translational world. I've got a protein, now I wanna study it in a population of people. I think as we look more into biopharma and other industrial applications, as we talked about on our call a bit. Our ability to work with proteins that aren't covered by existing technologies, we've seen this a bit in the military applications we've talked about. We've worked across multiple branches here and within U.S. military, we've got active engagements with other militaries outside of the U.S. You know, this sort of ability to apply a technology that doesn't need a defined reference to things like pathogen identification, pathogen surveillance, other epidemiological type of work. We think that opportunity could be very helpful. very meaningful and isn't well served by a competitive method.

So that could be another area where we see sort of a hook. And that spans researchers, it spans government entities, it could span industrial as you think about antibody production and other things. So I think those are maybe the two really unique capabilities.

we see sort of having some hooks into the different segments. Okay, great. Just a final quick question on R&D. I can see SG&A contracting with the cost cuts. How should we think about R&D in the next couple of quarters relative to Q2?.

I think you're going to see R&D fairly consistent to prior quarters. I mean, there are some adjustments as we streamlined the timeline. development process as we commented on earlier, Scott, but by and far and large, The spend on the program and the important spend on the program will remain intact because that's the most important thing that we're doing here. There could be some ups and downs just over the next couple of quarters as we change around a few things to make sure the program's on track and it stays on track for Q2 2027. But our operating expenses are still there. action is really hitting all areas across the company and is really associated with the timeline of the program and to make a few things around the company more efficient. So, you know, from that aspect, I think you're going to see the spend relatively consistent with a few adjustments. Okay.

Okay, great. Thank you for taking the questions. Thanks, Scott.

Our next question comes from Michael King with Rodman and Renshaw.

Hi, guys. Thanks for taking the question. Maybe just a bit of a follow-up on Scott, your answers to Scott's questions about the additional design cycle. So, again, just to be clear on this, was this – function of you running demonstration runs with, you know, with prototype systems, or was this a result of some scale-up that you were doing for, you know, future customer delivery? That's the first part of the question. And the second part of the question is, How does this affect your ability to satisfy the early access program that you've put in place?.

Yes, Michael, so again, this is driven by us having deployed integrated machines in our R&D environment and looking at the repeatability of the performance we see, not just in pure sequencing, as you can imagine when you're developing a product like this, you're also looking at a lot of the performance. a lot of other more fundamental performance metrics or requirements of specific submodules even of the system. And what we were really looking at is how are all of those things performing? Where are they against what our expectation is? And that feeds back into also, what did we learn when we produced those units? and what other things we could do that would make that process more efficient in the future or result in a higher first pass yield. So it's a mix of assessment of the repeatability of performance and also our assessment of opportunities to make some design for manufacturability type changes now that to you the second part of your question is critical when you think about when we launch we want to be able to confidently and reliably make these instruments and deliver them to customers. So some of those changes are exactly aligned to do that so we don't end up with that learning down the road when we're in the market. Okay. And would it apply to the reagents themselves, Jeff, or just the instrumentation? It's very hardware-focused, Michael. I mean, reagent development is still ongoing as well as the consumables, but those areas have really been tracking largely to our expectations, very instrument-centric areas.

on this particular sort of topic. Got it. And the part of the question about the early access? Yes.

Yes, so we haven't yet officially started any early access. We have announced that we have for select customers done some sample testing. With this shift in the timeline, we would expect that the early access will also move out. We don't have an official date with which we're saying we're going to start that activity. But I think from our mindset, we want to really see this instrument design cycle get completed, built, and tested internally. That would then allow us to sort of open up for testing customer samples and then sort of following on would be sort of deploying these into the field for early access. So I think that event's going to, you know, it's going to obviously shift out in time.

Yes.

Okay. And then is there any thought maybe you could, would you be able to, I know you're limiting your supply with Platinum Plus, but, sorry, Platinum Pro, but are you able to, you know, swap those units in just to keep, you know, potential clients engaged with the, you know, with the company? Yes.

Is that kind of a good idea? Yes, Michael, we have sufficient Platinum Pro machines to be able to work with customers. We have been continuing to use the placement program where we have folks, as the one example I gave, around AAV serotyping. That's a good example of leveraging the placement program to to engage with a customer, work on their application, really for us, both the customer and us, to understand exactly what's needed to get there. And we feel very good there about Proteus sort of closing the remaining gap. So we still have that available. Our reps have that available. Some customers like that path, others prefer to wait and start with produce. So we really let the customers steer that, but we're comfortable that we have sufficient supply of to continue to support that placement program, you know, as customers may be.

request on the path to Proteus. Okay. And just as far as kind of merging, you know, the full... Excuse me, the full suite of reagents with the commercial unit, assuming that you guys hit your timelines. I was under the impression you'd have... you'd have all the full repertoire of 21 amino acids available sometime in the first half of next year. Is that still your goal? And would that mean that when... produces out there that the um you know the full suite of uh reagents is available.

Yes, so Michael, let's go back. What have we said sort of historically? We've said when we believed we would launch Proteus by the end of this year, we had said we would launch with 18, and we would demonstrate all 20, and then add 20 when we got into 2027. What we communicate today was with the timeline move we expect now that we'll be in a position to launch with either 19 or 20 if we launch with 19 then we would still expect to bring on 20 during 2027 we just don't know yet exactly where we'll land on 19 or 20 but we still think we'll be able to demonstrate all 20 this year we just aren't yet ready to commit to exactly what will be in that kit except to say we do believe it will be either 19 or 20 given the additional time.

Okay. Thanks very much for taking the questions. Yep. You're welcome. Our next question comes from Kyle Nixon with Canaccord Genuity.

Hey, guys, thanks for the questions. On the additional cycle that you're, I guess, working on, can you maybe speak to how performance or reproducibility could be affected by this? Or maybe the steps that you take to avoid maybe impacting what your prior performance level expectations were going to be?.

Yes, Kyle, I think – let me answer what I think you're asking, and if I'm off, just let me know. So what we've observed, again, in the units that we have internally is we have some instruments that really reliably perform at a very high level, meaning above our internal specifications. for the product. We have other machines that are performing sort of at or a little below where that's at. And what we are really trying to do with this set of this sort of design spin is, you know, make the changes we've identified that we believe allow all of those units to be performing consistently at that higher level. So we think this enables us to sort of unify the repeatability sort of profile of the instruments and also equally as important, take some of the complexity or challenges we saw in manufacturing out by making those designed for manufacturability improvements. So I think it will be a combination of the improvement and the simplification of the manufacturing process, but then also the repeatability we should see in the machine should continue to trend up.

and be consistently above our internal specifications. Yes, that was perfect. Thanks, Jeff, for the clarification. And I guess on this note, I'm not I mean, I'm curious if the production time or any sort of... you know, any kind of like timing with, I don't think the sales cycle is a good question for this, but I think like the production could be interesting to ask about. Could that be, is that elongated through this process? It's like not really clear if this is how much is affected in manufacturing versus the kind of the end product, if that makes sense. Thanks. Yes.

Yes, that's a good question. So I'll say a couple of things on the manufacturing front. It has definitely been more challenging and sort of longer to get we had anticipated. I think we have an optical module that is made as a fully built up component by one of our partners that is then sort of and shipped to our instrument partner who then puts that into the broader fully integrated machine. When you're doing this for the first time, you certainly learn a lot about how each of the steps in the process works, how bringing all that together works, and then learn a lot about how exactly exactly do you test that and confirm its functioning is going to meet its requirements. So we've definitely learned a lot about that. That improves every time we make another machine, and I think with the set of changes for manufacturability we've identified, we'd expect with this next cycle for that to look a lot better. to look a lot more compressed and lead to a very high yield sort of success coming out the end of the line. So I'd say sort of that about the manufacturing side of the house.

In parallel, we are obviously being very conscious conscious of how lead times of components can move around. That is not a constraint today, but we're watching very closely, especially in the world of electronics and GPUs, to make sure – I mean, you don't have to be an expert in AI to know that the proliferation of data centers and the build out there is a massive consumer of those chips. So we are definitely staying very close to our vendor for those and ensuring that we have those procured well in advance so that when we get to the production stage, that's not a limiting factor. So I think that's the most important thing to limit any future production is really staying on top of long lead components. But I think in terms of just the time to build, that should be largely resolved through this next spin we do prior to going into production.

All right, excellent. On the topic of data, so with this like chip inflation and memory prices increasing and everything, of your exposure to that potential challenge, I guess, beyond 26 when you have Proteus out there? I know the architecture is a bit different, but maybe obviously like the company's has been reliant upon semis and everything. So just remind us, thanks. Yes, so if you look at Platinum, the consumable is based on.

semiconductor chip so you're sort of square in the foundry world of producing chips when you look at Proteus that that consumable is essentially a fused silica ray so a form of a glass array that's not a CMOS chip it has a fabrication step where we put the nanowells on, but in that context there are many vendors that can do that, and we're a very small consumer of that. We also get a lot more individual consumables from a single . So our exposure to sort of the semiconductor and chip world sort of goes away when we move into Proteus. In terms of the instrument, we still have a little bit of exposure in terms of the GPU. We have a GPU in this system to do data analysis. Again, we're a pretty small player in that world, so we don't perceive it as a As a large risk, that said, we understand lead times can be very long. And given the relatively low number of these that we use, comparatively, it's very easy to sort of stockpile a bit and hold that to just sort of buffer any potential for that sort of the supply of GPUs to be moving in or out. sort of get away from the historical CMOS-related semiconductor chip that was certainly more at risk of the sort of the foundry capacity that you're alluding to.

Okay, that's what I thought. And then on the non-human market opportunity that you talked about, I think that was $4 billion. And I assume it's plant-animal and similar things like that. I mean, I have to imagine that was always part of the plan, I guess. Maybe just kind of backtrack a bit and talk about originally why human, I guess. I suppose, was maybe the focus, and especially on the pharma side, of course those drugs are meant for humans, and going forward maybe this is a good, like, low-hanging fruit potentially for early on with Proteus and, I guess, with the residual platinum activities.

Yes, so Kyle, I think obviously we've always wanted to target our technology to any markets as we can. I think naturally when you go to market, given all of our respective backgrounds and the backgrounds of our sales professionals, you go to large academic centers, large academic medical centers, biopharma. And when you're in those, you're largely in the human world, whether it's basic research, mechanism of action, translational, you're in, to your point, you're in sort of the human world. Platinum is really a show. showing us really what the breadth of that non-human market might look like. With platinum, we originally got our first sort of exposure to this through the military side with pathogen and toxin detection. When we opened up the placement program, we got drawn into more, in the area of pathogen ID and surveillance, antimicrobial resistance, lots of different areas sort of getting drawn into different types of laboratories doing that work. Those can be government, they can be industrial, they can be academic.

The other side is with the placement program, we got drawn into some in the agricultural space So really, Platinum, what Platinum did was draw us in in a way where we got a depth of understanding of what the customer is trying to accomplish, the limitations of the tools available to them, and what specific capabilities we could add that would make our technology even more attractive in that segment. So while it's all you. been a part of our plan, I think the depth of understanding we've been able to gain from the platinum exposure really helps us make sure all of those capabilities and the additional that they're looking for are in the Proteus platform so we can really go attack that when we launch the platform.

Great. And last one on AI. So, I'm just curious if you're hearing anything, like, any inbounds or if you're, like, looking forward a bit and trying to think about, you know, the potential to generate proteomics data to train an AI model, maybe at, like, a pharma and just given, you know, for clinical human samples, you need kind of more of a, there's a wide dynamic gradient involved there, you know, can, you know, Proteus maybe satisfy that market opportunity as well, given that could be relatively larger for time.

Yes, Kyle, I think you're spot on, and I think we're hearing this. Not only are we hearing it, I think other companies operating in the proteomics space are certainly talking a lot about AI. To get the most out of AI, it's really about the training data, how rich is that data, Is it linked to outcomes or phenotypes, those types of things? So we certainly are hearing that in the marketplace. We're hearing it not just in biopharma, but also we hear about it in the academic space because many of the leading academic institutes are sort of operating at the cutting edge of AI tools for whether that be proteomic analysis, whether it be protein and generating novel proteins or whether it be how might we multi omic integrate different modes of data and get the most out of that so I think academic institutes are certainly playing a big a big role in that area I'd also say internally we've talked about this before but just to reinforce it you know intelligence has been something we have applied significantly in our operations. We use it in the analysis of data. We use it in many other functions. We've talked about it in the recognizer design, the enzymes in our kit, but we also use it across marketing and finance and other areas market research inside the company and it's a it's certainly a very powerful productivity tool as well.

So we're bought in. We definitely believe in it as a tool we use, and we do believe our technology will play a role with Proteus in helping people who are looking to build those sort of rich databases to train AI models.

Awesome. I have one more question for Jeff Kyes. On the model, so the $12 million in OpEx savings, yes, that's a lot. I think it was referenced earlier how that's probably just mostly SG&A, but can you just talk about the cadence and the timing of when that truly will hit and be fully implemented over the next couple of quarters? Yes.

Yes, I think we're going to start seeing the benefits of that in, call it, fourth quarter, second half of fourth quarter, because we have to work through seventh related costs and the timeline of certain folks leaving the company. But on an annualized basis, that was my prepared remarks that we expect 12 million related to this specific company. action of annualized savings as we move forward once it's all once it's all implemented.

Okay, perfect. Thanks, guys. Appreciate it. Thanks, Kyle. Our next question comes from Charles Wallace with HC Wainwright.

Hi, thanks for taking my questions. This is Charles. I'm for RK. So, I was wondering if you could share kind of the specific gating items between now and the second quarter of 27. Yes, and what what new items are in there that weren't in the prior game items? I.

Yes, I mean, the main gating item, Charles, to our prepared remarks is adding this additional instrument design cycle. So that cycle involves, you know, finalizing the exact changes we're going to make in that cycle, rolling that through manufacturing. building those machines and getting them in-house and tested. So we expect to work through that cycle of finalize the design, build, test, and confirm performance, you know, over the course of the remainder of this year. So that's really the big task. Assuming that task goes well, we intersect it with what we're doing on the on the reagent side and with the consumables, and then you bring that together through the first half of 2027 and with the launch in the second quarter. So I would say that that's the key gating item is really just working through that cycle, getting those instruments installed, and confirming the performance. Okay.

Yes, that's really helpful. And then I guess another question. So I think you said earlier that you haven't started the Early Access Program, if I heard correctly. And so are you still planning to do that? And when would you kind of do that? Would that be kind of this year event or maybe before the launch?.

Yes, so it's definitely before the launch, but yes, I did answer that earlier. You're correct. We haven't started that yet with this design cycle that we're going through. We wouldn't expect to start that till sometime after this cycle is complete. So, you know, we don't have an exact date, but if you just sort of think through this cycle, you know, confirming the performance, you know, it's probably more of a end of year, beginning of next year type of event is where that would happen. What we're hoping to be able to do perhaps in advance of that is start allowing customers to send some samples for evaluation. Again, we don't have an exact date for when we would offer that capability, but that's something we're keeping a close eye on we'd like to be able to do that and we would expect to be doing that before we went to a deployed sort of early access. So right now if you're trying to peg something I'd say I'd be thinking more, you know, as early access is sort of an early 2027 type of event.

Okay, that's very helpful. Thank you. Thanks, Charles.

Our next question comes from Jason McCarthy with Maxim Group.

Hey guys, this is Michael Okunowich on the line. Thank you for taking my questions today. Just a couple, primarily on the market opportunities here. First off, I wanted to ask just about the non-human proteomics market, how mature that is and if it's, I guess, ready for a device with the capabilities of protease at this time, or is this something where you would need to build out a base of published academic research first?.

Yes, so it's a good question. And what I would say is the reason we focused our remarks on specifically the pathogen research and agricultural is because we've got actual hands-on experience with our existing Platinum and Platinum Pro devices in that market segment. are customers trying to solve problems or address initiatives they have right now in place from their institutes. So we believe those markets are absolutely ready for the technology. Some are already applying our first generation technology and many of them we would expect would move and apply the Proteus technology. Where your comment about the maturity of the markets comes in is the part that we also talked about a little bit in the prepared remarks, which is there are a lot of other areas in non-human like animal health or industrial or food or environmental. Those areas we don't have as much of that direct customer experience, and yet we're doing the work to learn about those. So we're not really factoring those into our thinking right now, because to your point, we don't know exactly what the fit of the technology is or what the exact need or urgency might be.

But certainly in pathogen and agricultural, given the platinum work, think it's a market that's there today and we think Proteus will only build upon the opportunity that we've already sort of uncovered with Platinum.

Thank you. And then I wanted to see if you could help qualify the difference between only capturing 17 or 18 aminos versus capturing the full suite. Is this something where there's an incremental benefit to the end users, or does having the full suite open up new applications entirely?.

Yes, I would think of it in two ways. One is, as you start to get out to 18, 19, and 20, you can imagine that we're talking about, generally speaking, lower abundance amino acids. As you can imagine, when we were developing the technology, we tried to target the most abundant one. So I think for many applications, a significant difference between 18, 19, or 20. I think in the area of really deep protein profiling, so maybe somebody who wants to try to sequence as many of the amino acids, let's say, in an antibody as they can, that's where that sort of, to your point, that opportunity opens up or if people want to do that, they might really care about, you know, the difference between 18, 19, or 20. So I think there are some examples of that. There are many instances where it's probably less impactful to the performance.

But I can tell you there's also just a general, of psychology of customers that I think getting out there to 19 and 20 just sort of resonates as it's complete. It's sequencing. I think when people think of sequencing, they largely think of DNA and they think of, you know, you've got to cover all the bases in DNA. So I think there is sort of maybe a little bit of a mental or psychological bar that it's a less nuanced conversation with the customer when you have all 20 than when you have, say, 18 or 19. But I think outside of a small number of applications where you really need all 20, it doesn't really open up a lot of markets. It's more you overcome the need. that it makes the sales cycle a bit more straightforward. It makes the explanation easier. get into all these nuances with a customer about what you know what coverage they need for their application.

Yes, you don't have to justify why 18 isn't enough anymore.

It's the same concept in the DNA sequencing world. Before we were sequencing everything, we used to use arrays, right? And the question was, well, how many of the different SNPs in the genome could you look at? Well, this one looks at 500,000. This one looks at 800,000. And eventually when sequencing came out, it was like, well, I can just now look at the whole exome. or the whole genome, and people just moved there because they didn't need to make that choice. They didn't need to think through exactly what panel they needed if they could just see the whole thing. I think sequencing is somewhat like that in protein. If you just have the full suite, you don't have to really help people think that through despite the fact that in most applications the difference between 18 19 or 20 is very marginal.

Well, thank you. I really appreciate the additional color. Congrats on the progress.

Thank you. Thank you. This will conclude today's conference call. Thank you for participating. You may now disconnect.

This live transcript is auto-generated without human intervention or review.

[Call has ended.]

Greetings. Welcome to the Quantum-Si Incorporated Annual Meeting. [Operator Instructions] I will now turn the conference over to your host, Jeff Hawkins, President and Chief Executive Officer of Quantum-Si.

Good afternoon, and welcome to the 2026 Annual Meeting of Stockholders of Quantum-Si Incorporated. It is 1:00 p.m. Eastern Time, and I would like to call this meeting to order. I am Jeff Hawkins, President and Chief Executive Officer and a member of the Board of Directors of Quantum-Si. Today's meeting is a live audio webcast. We hope that this virtual meeting will maximize the participation of stockholders regardless of their location. Thank you very much to those who are participating in our meeting today. It gives me great pleasure to welcome you to this meeting.

Now I would like to make some introductions of members of the executive team, and then I will describe the format of this meeting. The executive team is a small part of a much broader and very talented team moving Quantum-Si forward every day. Our people are why Quantum-Si has made it so far so quickly and will be responsible for helping us to continue to fulfill our mission. I would like to introduce Jeff Keyes, our Chief Financial Officer and Treasurer; John Vieceli, our Chief Product Officer; Todd Rearick, our Chief Technology Officer; Lindsay Thompson, our Chief Human Resource Officer; and Christian Lapointe, our General Counsel and Corporate Secretary.

Part of the team are the outside professionals who support us. Ousmane Caba from PricewaterhouseCoopers, our independent auditors, is in attendance, and Larry Nishnick from DLA Piper, our external legal counsel, is also here. In terms of the format of the meeting, Jeff and Christian will guide us through the formal part of the meeting. I have appointed Jeff to serve as Inspector of Elections at this meeting, and in that capacity, he will report on the results of the voting as tabulated by Broadridge Financial Solutions. Each of us look forward to having the chance to answer any questions you may have.

I will now turn the formal part of the meeting over to Jeff and Christian.

Thank you, Jeff. As Jeff stated, we will proceed with the formal business of the meeting as set forth in the proxy materials, including the notice of this meeting. The proxy materials, including the notice of this meeting was mailed on April 1, 2026, to the stockholders of record as of March 20, 2026. The agenda for the meeting as indicated in the notice and accompanying documents sent to you is to vote on the following proposals: first, to elect 10 directors to serve 1 year terms expiring in 2027. Second, to ratify the appointment of PricewaterhouseCoopers LLP, as Quantum-Si's independent registered public accounting firm for the current fiscal year. And third, to approve by nonbinding advisory vote, the compensation of our named executive officers.

We will now consider and call to vote each proposal in the same order. The proposals are described in detail in our proxy statement. The polls for each matter are open for voting and will remain open until we announce that the polls are closed, which will occur after we have read the description of all the proposals to be voted on at this meeting or such earlier time as may be announced. No ballots or proxies or revocations thereof or changes thereto will be accepted after the polls are closed. The Inspector of Elections will announce the results of the voting at the end of the formal part of this meeting.

Before we address the proposals to be voted on today, we would like to point out that most stockholders have already cast their votes by completing proxy cards or by voting over the Internet. These votes have been tabulated by Broadridge Financial Solutions. We would now like to ascertain from the Inspector of Elections if a quorum is present for this meeting.

The count of shares present immediately prior to the commencement of the meeting included -- indicated that 124,647,066 shares of the company's common stock are present or represented by proxy including 104,709,566 shares of the company's Class A common stock, 19,937,500 shares of the company's Class B common stock with each share of Class A common stock entitled to 1 vote and each share of Class B common stock entitled to 20 votes. This is approximately 84.59% of the outstanding total voting power of the shares of common stock of the company as of the record date. We, therefore, have a majority of the voting power of the outstanding shares of common stock represented at this meeting or through representation by proxy.

Thank you, Jeff. We therefore declare that a quorum exists. Let's proceed to voting on each of the proposals. The first proposal is to elect each of Charles Kummeth, Jeffrey Hawkins, Paula Dowdy, Ruth Fattori, Amir Jafri, Jack Kenny, Brigid Makes, Scott Mendel, Kevin Rakin and Jonathan Rothberg, as directors for a term of 1 year to serve until 2027 Annual Meeting of Stockholders and until their respective successors are elected and qualified. Additional information about them is available -- is included in our proxy statement. We hereby declare that each nominee has been duly nominated and that Quantum-Si has not received notice of any other nominations as required under the company's bylaws. Accordingly, all nominations are closed.

The polls will be open for the next few minutes to vote on the election of directors as well as the next matters. After voting has been completed on all matters on the agenda, the votes will be counted.

The second item on today's agenda is the ratification of the appointment by the Board of Directors of PricewaterhouseCoopers LLP as Quantum-Si's independent auditors for the current fiscal year. Any stockholder who has already voted and does not want to change their vote, need not take any further action.

The third item on today's agenda is the approval by a nonbinding advisory vote of the compensation of our named executive officers as disclosed in our proxy statement. Any stockholder who has already voted and does not want to change their vote need not take any further action.

This concludes the proposals to be voted on at this annual meeting. Let's now turn to the results of the voting. We now declare that the polls are closed on each, Proposal #1, Proposal #2 and Proposal #3. The Inspector of Elections will now give us a report on the voting results.

We have completed a preliminary count of the ballots, and we will, of course, have those numbers outlined in a Form 8-K, which will be filed with the SEC no later than Thursday, May 21, 2026. With respect to Proposal #1, the election of directors, the requisite number of shares have been voted for Mr. Kummeth, Mr. Hawkins, Ms. Dowdy, Ms. Fattori, Mr. Jafri, Mr. Kenny, Ms. Makes, Mr. Mendel, Mr. Rakin and Dr. Rothberg.

With respect to Proposal #2, the ratification of the appointment of PricewaterhouseCoopers LLP as our independent auditors, the requisite number of shares have been voted for this proposal.

With respect to Proposal #3, the approval by a nonbinding advisory vote of the compensation of our named executive officers, the requisite number of shares have been voted for this proposal. That concludes my report as Inspector of Elections.

Thank you. Because the affirmative vote of the holders of the requisite number of shares has been obtained on each proposal, we hereby declare that each proposal has been officially approved and ratified by the stockholders. Mr. Hawkins, there being no other business to conduct at this meeting, we are ready to declare the formal part of our meeting officially adjourned.

There being no other business to conduct at this meeting, I hereby declare the formal part of our meeting is officially adjourned. Thank you for your attention.

We will now turn the meeting over to Jeff Hawkins for any Q&A. We are obliged to say that the management's remarks and responses to any questions may contain forward-looking statements. As is custom, we point out that actual results may differ significantly from results discussed in the forward-looking statements. Factors that may cause such a difference include those set forth in the company's SEC filings, including the company's annual report on Form 10-K for the fiscal year ended December 31, 2025, and its quarterly report on Form 10-Q for the quarter ended March 31, 2026.

Thank you, Christian and to our stockholders. I would again like to express my sincere appreciation to the stockholders who attended the meeting virtually and voted as well as those who submitted their proxies but were not able to attend. We would be glad to now open the floor up to any questions or comments from stockholders. If you wish to ask a question, please submit your questions via the link included in the webcast today under ask a question.

Jeff, can you please confirm if we have any questions.

At this time, Jeff, we have no questions from stockholders.

Great. If there are no more questions, then we will conclude this session. Thank you.

This concludes today's conference, and you may disconnect at this time. Thank you for your participation.

Good day, and thank you for standing by. Welcome to the Quantum-Si First Quarter 2026 Earnings Call and Business Update. [Operator Instructions]. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Risa Lindsay. Risa, go ahead.

Good afternoon, everyone, and thank you for joining us. Earlier today, Quantum-Si released financial results for the first quarter ended March 31, 2026. A copy of the press release is available on the company's website. Joining me today are Jeff Hawkins, our President and Chief Executive Officer; as well as Jeff Keyes, our Chief Financial Officer. Before we begin, I would like to remind you that management will be making certain forward-looking statements within the meaning of the federal securities laws.

These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated. Additional information regarding these risks and uncertainties appears in the section entitled Forward-Looking Statements of our press release. For a more complete list and description of risk factors, please see the company's filings made with the Securities and Exchange Commission. This conference call contains time-sensitive information that is accurate only as of the live broadcast date today, May 7, 2026. Except as required by law, the company disclaims any intention or obligation to update or revise any forward-looking statements. During this call, we will also be referring to certain financial measures that are not prepared in accordance with U.S. generally accepted accounting principles or GAAP.

A reconciliation of these non-GAAP financial measures to the most directly comparable GAAP financial measures is included in the press release filed earlier today. With that, let me turn the call over to Jeff Hawkins.

Good afternoon, and thank you for joining us. On today's call, we will provide a business update and review our operating results for the first quarter of 2026. After that, we will open the call for questions. As we communicated on our last earnings call, we expect that 2026 will be a transition year with revenue primarily driven by consumable utilization from our installed base and some new placements of Platinum, very modest new capital sales and a laser focus on Proteus development and preparing the market for a strong commercial launch by the end of 2026. As such, our three corporate priorities for 2026 are as follows: to deliver Proteus with the capabilities customers need, to prepare the market for Proteus launch and to preserve our financial strength.

Our first priority is to deliver Proteus with the capabilities customers need. We made significant progress with the proteus development program during the first quarter of 2026. The results of this progress were highlighted in our recent announcement regarding the successful completion of sequencing on fully integrated Proteus instruments.

The achievement of a milestone of this complexity is a significant derisking event for any new platform development program. To accomplish this result, we had instruments and software that automatically performed all the steps in the sequencing process from reagent preparation to sample loading through to sequencing and data capture and analysis. We also had developmental sequencing reagents, kinetic arrays and associated surface chemistry that enabled single molecule loading and sequencing with the detection of 17 amino acids.

While there is more work to do to get to the commercial launch, it is clear that the Proteus platform is a fundamentally superior technology compared to Platinum. Beyond automation and throughput, which customers will certainly value, the core technology in Proteus consistently delivers higher proteome coverage. At its core, Proteus has better signal-to-noise ratio and can reliably detect much shorter pulses of recognizers, which translates into detecting more amino acids per peptide and longer average peptide read lengths.

In terms of recognizer development, we recently reported that our internal developmental sequencing kit was able to detect 17 amino acids. Not only have we increased the number of unique amino acids detected from 15 in December of 2025 to 17 in just 4 months, but we have also made improvements that increased the detection frequency across all the amino acids we detect. Our recent progress in this area and the pace of improvement we are seeing provides us with high confidence that we are well on our way to delivering Proteus by the end of 2026 with the detection of 18 amino acids, demonstrating detection of all 20 amino acids during 2026 and in turn, delivering a sequencing kit in 2027 that detects all 20 amino acids.

Finally, I want to provide an update on our progress towards enabling post-translational modification capabilities on Proteus. For background, depending on the PTM, customers today have two choices: affinity-based methods, which are limited to a specific site or specific protein of interest or mass spectrometry, which requires complex sample preparation procedures and access to sophisticated bioinformatics personnel to collect, filter and analyze the data using a variety of software tools that are required to provide site resolved profiles.

This is true for a well-studied PTM like phosphorylation. But when you move into other PTMs like methylation, acetylation or citrullination, the options are even more limited with the available analysis tools often being lab developed versus commercially available. During our November 2025 Investor and Analyst Day, we provided insight into three different ways that our technology can detect PTMs. One of those ways is via kinetic signatures. In short, using the rich set of data that each recognizer generates as the sequencing reaction moves through each amino acid in the peptide, the software can automatically determine if a PTM is present or not, which PTM it is and at which specific amino acid site.

The primary advantage to this method is that the sequencing chemistry is universal and the PTM detection is accomplished using automated analysis algorithms. This is in stark contrast to affinity-based methods, which require site-specific PTM reagents and in some cases, those reagents are protein-specific as well. Given the extremely large amount of data we expect to generate in a Proteus sequencing run and leveraging the power of advanced AI tools, the potential to develop PTM capabilities using kinetic signatures and continuously expand those capabilities over time is immense.

This is why we are laser-focused on this approach, and I am pleased to report that we are making great progress in this area and expect to have more specific updates to share in the near future. Our second corporate priority is to prepare the market for Proteus launch. In preparation for commercial launch of Proteus, we are focusing our commercial and scientific affairs teams on three main strategic initiatives: first, demonstrating the value of our single molecule protein sequencing technology; second, expanding awareness of Proteus across geographies and end market segments; and finally, identifying and developing a funnel of potential Proteus customers to ensure successful commercial adoption upon launch.

To demonstrate the value of single molecule protein sequencing, our scientific affairs team has been working with customers using our first-generation Platinum instrument and commercially available kits to generate data and release the results via posters at industry conferences, manuscripts via preprint and peer-reviewed publications. Since the start of 2026, we have had a total of three customer manuscripts released via preprint or peer review, five posters presented at industry conferences and a customer podium presentation during U.S. HUPO. The data released this year shows a wide range of applications from rapid pathogen and toxin detection to clinical proteomics to detection of post-translational modifications in translational research.

Importantly, the data released this year also spans multiple end market segments, including academic research, clinical, biopharma and government. We believe that these sets of customer data and other studies in the pipeline will continue to demonstrate that the potential opportunity for our technology extends well beyond the basic research markets that we operate in today. This is important since customers in biopharma, translational research and clinical testing typically have higher consumable utilization rates and repeat order patterns compared to basic research customers.

Turning now to our work on expanding awareness of Proteus across geographies and end markets. In April, we announced the beginning of the Proteus roadshow series. These events are designed to educate the market on the value of our proprietary single-molecule protein sequencing technology and the Proteus instrument and projected capabilities. The individual roadshow events can take the shape of one of two types of formats. First, in institutions where we have an existing customer, we work with them to bring together as many of their colleagues as possible to expand the institutional awareness of our technology. Expanding institutional awareness can benefit our existing user by creating more demand for inclusion of our technology in ongoing research studies, and it also aids us in building a large community of interested users for Proteus, increasing the number of potential avenues to pursue for funding the purchase of the instrument in the future.

The second type of event is tailored to locations where we do not have an existing customer. In these locations, we focus on a centrally located venue and our outreach focuses on engaging potential users from as many unique institutions in the surrounding area as possible. While we have just started the roadshow series, the early data is encouraging. At one recent event, we had 25 people register attend, but on the day of the event, we had 35 people in attendance. All the attendees were researchers who currently use or want to begin to incorporate proteomic technologies into their research.

Importantly, these 35 attendees invested nearly 2 hours of their time to learn about our technology, the Proteus system and to discuss potential applications with members of our commercial and scientific affairs team. We expect to continue with roadshows throughout the year, and we'll provide more updates on specific cities and associated event metrics as the program progresses. Finally, in addition to supporting our existing Platinum users, our sales team is focused on identifying and developing a funnel of potential Proteus customers to ensure successful commercial adoption upon launch.

Our team has been assigned quantitative goals for each quarter, and we are pleased with the current progress we are seeing. As part of this process, we recently announced that we had successfully completed sequencing of our first customer samples on the Proteus prototype. In this first instance, the customer is an existing platinum user, and they were interested in seeing how much better the data would be with Proteus. While there were many exciting takeaways from the data, the two that resonated the strongest with the customer was the increase in the number of amino acids detected and the increase in the average read length on Proteus compared to Platinum.

When combined, improvements in these two attributes provide the customer with significantly more sequence level information about each of their proteins of interest. The positive response from this customer confirms our belief that offering the ability for customers to send in samples for evaluation could be a very useful tool to deepen engagement and advance the customer through the buying process prior to Proteus commercial launch. We are working closely with our manufacturing partners to increase the number of Proteus instruments available within our R&D labs. And once complete, we expect to be able to offer sample evaluations more broadly to prospective customers.

Our third priority is to preserve our financial strength. We believe that the data we will generate over the coming months will continue to demonstrate that Proteus is not only a new architecture with greater throughput and automation, but also a significant leap forward in terms of sequencing performance and application breadth. We continue to believe that Proteus will be the long-term driver of commercial adoption, revenue growth and our path to profitability. We remain committed to continuing to operate with a high level of fiscal discipline while ensuring the core strategic initiatives are appropriately funded to deliver Proteus on time and with the capabilities customers are asking for. I will now turn the call over to Jeff to review our financial results.

Thanks, Jeff. I'll now walk through our operating results for the first quarter of 2026. Revenue in the first quarter of 2026 was $258,000, consisting of revenue from our Platinum line of instruments, consumable kits and related services. Gross profit was $74,000, resulting in a gross margin of 29%. Gross margin in the quarter was primarily driven by revenue mix with a higher proportion of consumables relative to hardware. As we have discussed and guided for 2026, we expect revenue in the near term to reflect the anticipated launch of Proteus as some customers time purchasing decisions closer to the availability of our new platform.

Turning to expenses. GAAP total operating expenses for the first quarter of 2026 were $24.1 million compared to $25.6 million in the first quarter of 2025. Adjusted operating expenses were $21.4 million compared to $22.9 million in the prior year quarter. Year-over-year, we funded R&D at a slightly higher level to support Proteus development while maintaining discipline in total overall adjusted operating expenses. Dividend and interest income was $1.9 million in the first quarter of 2026 compared to $2.5 million in the prior year quarter. The year-over-year decrease reflects lower interest rates and changes in investment balances. As of March 31, 2026, we had $190.4 million in cash, cash equivalents and investment in marketable securities. As we presented on our last call, our outlook for 2026 includes total revenue of approximately $1 million, adjusted operating expenses of $98 million or less and total cash usage of $93 million or less.

2026 is a delivery transition year as we prepare for the anticipated launch of Proteus, and we are making intentional choices that prioritize long-term platform adoption over near-term revenue maximization. This includes embedding upgrade paths and certain Platinum Pro unit sales in 2026, which has a near-term revenue impact as well as expected timing shifts as customers plan for Proteus availability. With our development progress, Proteus roadshow events and continued education of channel partners worldwide, we're seeing strong interest in Proteus, which is influencing customer purchasing time lines.

Our operating expense guidance and cash utilization remain on track and reflect the activities required to complete development and support a successful commercial launch of Proteus. Our expected cash usage also includes modest inventory build and commercial readiness efforts ahead of the launch. With over $190 million in cash and investments at March 31, we continue to believe we have cash to support operations into the second quarter of 2028, approximately a year and a half after our estimated Proteus launch date.

After the Proteus launch, we expect meaningful operating expense leverage over time as launch-related development spend rolls off. Because we are utilizing key external partners for certain development-related activities, we anticipate the ability to ratchet down R&D spend post launch. This gives us flexibility to reduce total operating expenses and extend our cash runway while retaining the option to selectively redeploy resources into high-return commercialization initiatives as we scale.

Finally, management and the board remain aligned with shareholders. Inside ownership remains meaningful and recent Form 4 activity by management continues to reflect routine tax-related mechanics associated with equity compensation vesting with no management team members selling shares outside of planned mandated sales to cover required tax withholdings. In addition, it is important to note that two of our board members collectively purchased over 600,000 shares during the quarter in the open market. With that, we're happy to take your questions.

[Operator Instructions] Our first question comes from Scott Henry with AGP.

The first kind of bigger picture question. And as customers are starting to use the Proteus and they're seeing the more amino acids and the larger or the longer read lengths. Can you talk a little bit about that, what that means to the customer experience? I know you mentioned more information, but is it also better information, faster information, kind of new applications. I'm just trying to get an idea a little bit more about the customer experience with Proteus versus Platinum.

Yes. Thanks, Scott, for that question. So maybe we'll break it down into three different application buckets. So one bucket could be, I have a sample and I want to identify the proteins that are present in that sample. Another bucket would be the post-translational modifications and a third sort of application area would be, let's say, variant. I'm engineering a protein and I want to see if there are variants of the target protein I'm trying to make. If you think about getting more amino acids, getting longer read lengths and so sort of getting more content per protein, if you're in that protein identification sort of area, it means you're going to be able to deal with a more complex mixture of proteins. You'll have more unique content, unique information with which to determine the variety of proteins that are there.

Even more importantly, when you look at post-translational modifications or looking for variants in proteins, that's where more amino acid coverage, longer read lengths gives you the ability to detect more of those events, see those events may be spread out along the length of a peptide. They're not always at the beginning of a peptide. So these things give you a much higher level of fidelity and capability when you start thinking about those applications like post-translational modifications or variants. So that's maybe a way to think about what are these fundamental sequencing capabilities mean to a customer in terms of the applications they're doing.

Okay, great. Thank you for that color. And somewhat related and this relies a little bit about your -- on your perception and perhaps some of the earlier customer feedback you've gotten. But how could you anticipate customers' volume when one switches from a Platinum to the Proteus because you have all these added benefits, could it double volume? Could it 4x volume? Just -- I mean, I realize this is a bit of guesswork, but I just want to get your thoughts on that.

Yes. I mean I think it's the right question, Scott, and I think it's a little hard to predict right now because I think if we maybe take the question up to the 10,000-foot level, within the Platinum customers, Proteus clearly is going to bring a broader set of applications, which we would expect would open up the utilization of our technology in a lot more sort of research studies. So we would expect within that Platinum base that the Proteus should see more volume than Platinum sees. Exactly how much that is, is that a factor of two? Is that a bigger number than that? I think that's the part until we get machines in the field and running it is a little hard to predict.

The other aspect is all those labs and customers and some of the market segments that we just haven't been able to access with Platinum at all. And we think the capabilities, especially focusing in on post-translational modifications, focusing in on those protein variants that's going to open up a whole bunch of new customer stuff where today, we don't even have a Platinum in there. We're getting no volume. That will be sort of a new address for us and the ability to go sort of farm that account across a lot of different researchers in one institute and really drive volume into our machine.

Okay. Great. Final question. Between now and launch, you have about six months. Are there any gating factors technologically? Or is it mostly production and building of inventory between now and then?

Yes, Scott, so the way I think about it is you have sort of the invention or the big technological breakthrough phase. That's happened. That's behind us. We've achieved that. We know the technology works. We know we're getting the performance from the fundamental components of our technology, whether that's the consumable, the instrument or the sequencing reagents. So really, what we view the next six months as, is a mix of the manufacturing sort of transfer and bring up that you mentioned, but also just what I would call sort of very standard hardware or instrument engineering and systems integration.

So driving up the reliability, the success rates, making sure you really get to the target specifications you want, not just in terms of amino acid coverage, but the precision you're getting, the reliability you're getting, the mean time between failure. So I put all of those things into what would classically be considered pretty standard systems engineering or systems integration work. So it's technical in nature, but not something where we'd expect to need to have some sort of innovation breakthrough. We think the innovation phase of the program and the invention phase is behind us, and it's really now more an operational and execution-related development effort.

Our next question comes from the line of Michael King with Rodman & Renshaw.

Actually, a couple of quick ones. I'm just -- this is because I'm really dumb. I'm trying to understand that how you got lower -- you say you have operating expenses in the quarter were $24.1 million versus $25.6 million for the same period last year, but you accelerated -- you say you funded research and development at a higher run rate year-on-year. So how does that math math?

Thanks Michael, this is Jeff Keyes. So just overall, from an R&D standpoint, it can be a little lumpy from quarter-to-quarter just as we deploy with third-party partners to help on certain aspects of related activities. So that's why I was saying this year compared to last year, we were spending at a slightly higher level, but we were spending in SG&A at a slightly lower level just based on other activities that we've pulled back and streamlined as part of our overall OpEx optimization and streamlined process to ensure that we have good runway going forward.

So R&D can be a little lumpy from quarter-to-quarter. But overall, we expect to spend within those guidelines that I mentioned earlier.

Okay. Thanks for clarifying. Sorry to ask such a dumb question. The second -- the next question is, are you ramping -- I know you use third-party manufacturer, but are you ramping their production in advance of shipments? Or will that not happen until later in the year? Or does that just happen as a function of incoming orders? Maybe you can talk a little bit about that.

Yes, Michael, right now, the focus is really ramping the delivery of instruments that we're using for R&D purposes. So that's really the main focus today is just building out that base of instruments. That said, some of the build that's happening will ultimately support the early access customers in the summer as we work through the continued development. In terms of building inventory for the launch. That's something we'll start to look at as we move through the year and sort of really pacing that for what we see as sort of the funnel and any sort of preorders that may come in at the back end of the year.

So really think right now around -- it's more of an internal scale-up to just be able to continue to expand the development activities and be able to support those early access sites in the summer. think of inventory build for sales sort of being something later in the year.

Okay. Thanks for clarifying that. And then just -- I'm curious about the roadshow activity. I'm just wondering if you can say -- maybe you guys can print up T-shirts or something for this, but how many cities, how many sites do you guys expect to hit? And I'm just wondering also if you think about bringing your existing customers or potential customers into your headquarters to train them up so that once the installation is completed, they can immediately start doing their sequencing at scale instead of having to climb the learning curve, if that makes sense.

Sure. Let's break the question into two parts. So in terms of the road shows, we put out a press release a couple of weeks ago talking about the first few cities that we were targeting with with those events. We're continuing to scale that up. We are committed to continuing to provide a press release around the cities. Right now, we've been most heavily focused in the U.S. market, but I can tell you that we've begun locking in the dates for some of the roadshows and events in Europe. So sort of keep your eyes out for press releases in this area.

We'll continue to update you on the total -- on the new cities each quarter as we move through. We're seeing this as a very valuable tool, Michael, in terms … of reaching people, but the amount of time you get, I think if you go -- if you're a sales professional and you are trying to educate somebody on a new product or technology and you just go as a sales call, you typically get a lot in a fairly short period of time, maybe 30 minutes, a really generous customer maybe gives you an hour of time.

So it could take several sales calls to build the level of information awareness that we get when we do these roadshows where people come and spend about two hours on average at these events. So we like the format. We're liking the engagement. We're getting positive feedback. So again, we'll announce and help you understand the number of cities and the locations over the coming months.

Yes. I apologize. I think we were out that day that you made the announcement. So you've got Seattle, Houston and D.C. So I guess what do you do, you draw your clients from the surrounding environments and have them come in for their training or for the demonstration.

Yes. So the roadshow is more about educational. It's not really hands-on with the technology. To get to that part of your question, Michael, I think what we're really focused on is as we get our internal fleet of instruments sort of up to the number we'd like to have to have some additional capacity to apply the customer work. What we would look to do is have customers initially sending samples to us, so we're generating data and they get that data in their hands and are starting to work through that sort of evaluation process and ultimately, the budgeting process.

So to your point, when we get to launch, we have some number of customers who have already done the prework and what they'll be doing more is working through their sort of budgeting process to get the capital to purchase the machine on the back end. Once it's in their lab, we're very comfortable with how to train a customer to do this. We've done it to date on the Platinum instrument and Proteus having all of the sequencing component automated should be easier to train a customer than it even is today. So we're not worried about that back-end training component. We think that sample evaluation access early to get data in their hands is sort of the key thing, and that's the next major milestone we're looking to accomplish here over the coming quarter.

Okay. Amazing. And then just one final quick question. What does the early access site selection process look like? And how many sites do you expect to have active by the end of the summer? Can you give us a range or point estimate?

Yes. So I would say the process looks like we're going to want to have early access sites that span market segments. So clearly, we're going to want some number of academic institutes because those folks will be the type of customer who not only will do the early access, but are also going to publish. That said, we're also evaluating the potential to have one or more of the early access sites be in a commercial environment, whether that be biopharma, antibody production, some area like that, where we really want the data, I mean the experience in that market segment.

But we know that when you get into a commercial setting, oftentimes, those customers aren't able to publish. So we're thinking about those factors, demonstrating the capabilities, multiple segments, also thinking about geographies. We haven't set out an exact number. I think the way we're thinking about it, Michael, is we wouldn't -- we're going to want to have a reasonable number of these. I don't think you're going to see us do 10 of them, but at least a handful sort of is probably in the neighborhood of what we'd be looking to implement over the course of the summer and even into the fall and again, spanning geographies and markets.

Our next question comes from Charles Wallace with H.C. Wainwright.

This is Charles on for RK. I think -- so the first question I have, so you called out that your -- any Platinum Pro unit sold in 2026 is going to have an embedded credit towards Proteus. So I guess my first question is, have you sold any Platinum Pro units? And do you have some of these credits kind of stacked up at this point?

So I'll start with it. And if I don't get everything out, we'll -- I'm sure Jeff will jump in here with anything I miss. So not every Platinum Pro has to have that credit. So it's a credit that is available to customers if they want to have that ability. Sometimes when you have a new machine coming, people say, well, I want to buy it, but I'm not really sure what's going to happen when the new machine comes out, how long will you support it, those types of things, so they want to have a credit. So it is available to customers if they request it. That said, some of the -- sometimes machines you're selling now were ones that were budgeted for many months ago up to a year ago.

So those processes and those quotes would have gone out without this credit. So that might not show up in some of the machines that get sold throughout the year if they were budgeted for in the past. At this point, we're not really breaking out which of the capital sales have had the credit or not. I think as we go through the year and see other metrics of sort of the funnel building, perhaps we'll be in a position to provide a little more color on that because, again, a credit is really a protection for the customer.

They still have that option to buy the Proteus or not. So I think at this point, we're not breaking it out. We don't want to sort of overstate the demand for the future machine just based on if somebody asks for a credit or not.

Okay. Yes, that makes sense. And then I guess my next question. So for the early access program, you mentioned maybe a handful of units. And then I guess you also said you're building a fleet of internal units. So I guess the first part of that question is how large of an internal fleet are you targeting? And then also, how long does it take typically for an instrument to be built and be fully functional?

Yes. So I think in terms of the internal fleet, I don't know that we have an exact number that we would give out. I think you can think about the internal fleet as needing to support our instrument -- our engineering team, right, so people working on instruments, integration, software. We have reagent development, so the people putting the sequencing reagents into consumables and getting those optimized and ready to go.

So they have to have access to machines. And then, of course, as we're bringing up manufacturing, we have to have some number of machines in our quality control testing environment to do -- to develop the QC test. We'll run the specifications that we'll hold ourselves to when we are launching -- when we're sort of finalizing a kit and ultimately deciding what can be shipped to a customer. So we have multiple groups who need access to that. In general, our strategy is we continue to build those, and we try to maximize their utilization.

If we see that those are all maxed out, we keep building. We don't ever want to be throttled in terms of our ability to push as much testing volume and development volume through those internal machines. In terms of timelines for build, I think it would be a little early to try to put a specific time line on what's the lead time to build an instrument. I can tell you that there are a small number as is the case in most instruments of long lead parts. Those -- everybody -- we're not different than anybody in this regard in that we procure those in advance and hold those parts. So the assembly process itself is really more about applying the labor and optimizing those processes. I can tell you that we're having -- we're not having issues with when we build a machine, does the machine show up at a Quantum-Si facility and function properly. So we're not having those types of challenges that sometimes exist in early hardware development programs.

But in terms of, are we operating the line with perfect efficiency and perfect throughput, I think it's safe to say we're not yet, but we're very comfortable that we know how to do that, and we can optimize that well in advance of any commercial ramp. And again, since it's very labor-oriented, we have external partners. And one of the reasons we use those partners when we're doing instrument sort of manufacturing, they have the capacity. They have the people. They can flex that up or down as our forecast requires. So again, as long as we maintain that long lead sort of parts in inventory, the ability to flex up or down is a pretty efficient thing to do when you have external partners who have that kind of capacity.

Our next question comes from Kyle Mikson with Canaccord Genuity.

This is Charlotte [Mauer] on for Kyle. To start, do you think you could elaborate a little bit more on the recent successful sequencing run on the Proteus and how the performance maybe compared to your expectations? Also, what were some of the most notable improvements? And were there any specific challenges that you guys came across that kind of need to be addressed before moving forward?

Thanks, Charlotte. So I'll maybe work on that question backwards the forward. So the last part of your question was, did we experience any challenges testing those samples? And the answer to that question is no. We were able to run those samples successfully. We ran them actually both on Platinum and on Proteus so we could get at the same time comparison. In this particular sort of situation, these are a series of proteins that the customer has previously worked with and tested in their own lab using a Platinum instrument.

So really, what they were focused on for their applications. They're trying to both identify these proteins, but they're also doing some really novel work around developing tools for essentially de novo detection of amino acids. So they're really focused on the coverage and they're really focused on the read length. So obviously, getting data from Proteus, one is just the amount of output you get, the number of reads you get is obviously going to be much, much higher with the Proteus just simply based on the number of features on that chip compared to the platinum.

The coverage, as I mentioned in the prepared remarks, not only are we detecting 17 amino acids now, our detection frequency of the other ones is considerably higher. And then when you think about read length -- what the customer saw in these particular samples is that the read length on Proteus was about double, so about twice as long as what they're used to seeing on Platinum. So again, if we go back to one of my earlier answers to Scott, why would a customer care about more amino acids being detected or longer read length? Well, in this case, they're working on samples where they want to identify these proteins and potentially variants or modifications of them.

So they're really thinking about these algorithms they're developing that they want to do de novo detection with. So more content, longer reads, more complete sort of information is going to really help them with their exploratory algorithm work in addition to just the basic performance that they see in terms of identifying those and sort of subtyping those different proteins that they're looking at.

Awesome. I also had some questions about the roadshow as well. It sounds like there's been some strong early interest, but I was wondering if you could maybe dive a little bit deeper into any relevant feedback or interest that you've received like from the customers at this point about the Proteus and maybe some key highlights or takeaways and maybe anything on the feedback on the pricing specifically and what you've heard so far?

Yes. So I think the early feedback, most of the early interest that we anticipated and have been talking about is customers are really excited to have the ability to analyze PTMs. It's an area of translational research, basic biology research, mechanisms of action that outside of phosphorylation, it's a pretty difficult field to tackle even if you have access to some of the highest-end mass spec machines.

So PTMs are obviously a big draw in those environments. I think it's been interesting to see -- I mentioned there's sort of two different formats, one where we're working more with an existing user and focus a little bit more on depth of institutional knowledge versus a [brand new city].

One thing we're seeing in the first format where we go to where there's an existing Platinum and really try to open up the education is not just the core lab, but all the other researchers, whether they're translational, whether they're basic biology, the number of people who have an interest have a study in mind, have a potential way to utilize the technology, that's been a really positive learning for us as we think about how do you drive that institutional sort of momentum towards funding? How do you get the core lab to say, it's not just the things you're thinking about doing, but some of your customers, right? These other researchers in your institute have a desire to get access to the tech. This type of momentum can be really helpful when you're working through who's going to get the funding and where does the funding proposal sit at an institution amongst all the other capital equipment they're looking at.

So I think that's a good example of the value of doing these. To your point on pricing, we've announced that price. We haven't heard any pushback on that price. I wouldn't expect to hear any at this point for sort of two reasons, Charlotte. One is, remember, if you're thinking about the application space for translational modifications, those folks who are trying to work on that are often using very high-end mass spec equipment. That equipment can cost upwards of $1 million or more. So us sitting at $425,000 is really attractively price compared to sort of what they might be spending on one of the high-end mass spec machines.

The other piece is that's just, I think, a state of where we're at is we haven't given people enough information today that someone's got to really make that decision on the price. I think the good news is no one is hearing it and running away. So it tells us we're not too high. We didn't set it so high that people are sort of very skeptical of the price. But I think we won't get down to probably some of the really nuanced feedback until we continue to put out more data or they are able to start getting sample evaluations in hand. But as I said, thus far, no one's -- no one's been concerned. People have thought it's very reasonable for its capabilities. And I think we'll just keep driving home that message around the capabilities at $425,000 versus having to go all the way up over $1 million for a mass spec that can do the same thing.

Great. Yes, that makes a lot of sense. And then maybe if I can ask one last quick question. Looking ahead to expectations for 2027 and some of your capital deployment, you mentioned utilizing key external partners for certain development-related activities. Where in the process do you expect to use these partners the most? And then how should we think about this reduction in capital deployment relative to your 2026 levels kind of given this full year of spending on commercialization efforts for the Proteus?

Let me start, and then I'll pass it to Jeff for a little additional color. So the first thing I would say is we're using these partners today across some of our sort of consumable development efforts, our optics system that's inside of the Proteus and then the instrument development. So we have partners who are working with us across those various R&D efforts. Some of those partners will flip into our manufacturing partners next year. So they'll be with us, but it will be more in terms of building inventory and supporting that. Maybe, Jeff, you can sort of give a little feel for how we think about the burn down after we launch.

Yes. Regarding total OpEx as we move forward, as we go into 2027, we'll need some of these partners to help stabilize the program shortly after launch, which is typical from a new development project. But after that, since we are using a significant amount of external partners, we're going to be able to ratchet down that R&D spend specifically. And those were my comments earlier where I said we would be able to either bank that savings or redeploy it. But we're going to look for opportunities between R&D and other activities to ratchet down our OpEx, and we'll gauge that relative to how the Proteus uptake goes in 2027, and we'll be able to manage it going forward.

So it's definitely on our radar and something we'll be working on and the R&D spend for external partners is the first obvious step, and then there'll be other items that we can look at going forward.

And Charlotte, I'll just add one point. Consistent with what we did this year, as we look at our guidance in '27, we'll be able to be more quantitative when we get there in terms of how we think about our adjusted OpEx or our cash use. So I know that we'll continue to provide that guidance. It's just a little early to be providing it right now. But I mean, I think you can gather from Jeff and my feedback how we're thinking about rotating those dollars off in R&D, some deployment perhaps into other initiatives and banking the majority of that savings.

This concludes the question-and-answer session. I would now like to turn it back to Jeff Hawkins for closing remarks.

Thank you for attending our call today. We look forward to providing additional business updates on our next earnings call.

Thank you for your participation in today's conference. This does conclude the program. You may now disconnect.

Thank you for standing by, and welcome to the Quantum-Si Fourth Quarter and Year-End 2025 Earnings Call. [Operator Instructions] As a reminder, today's program is being recorded.

Now I'd like to introduce your host for today's program, Risa Lindsay. Please go ahead.

Good afternoon, everyone, and thank you for joining us. Earlier today, Quantum-Si released financial results for the fourth quarter and full year ended December 31, 2025. A copy of the press release is available on the company's website. Joining me today are Jeff Hawkins, our President and Chief Executive Officer; as well as Jeff Keyes, our Chief Financial Officer.

Before we begin, I would like to remind you that management will be making certain forward-looking statements within the meaning of the federal securities laws. These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated. Additional information regarding these risks and uncertainties appears in the section entitled Forward-Looking Statements of our press release. For a more complete list and description of risk factors, please see the company's filings made with the Securities and Exchange Commission.

This conference call contains time-sensitive information that is accurate only as of the live broadcast date today, March 3, 2026. Except as required by law, the company disclaims any intention or obligation to update or revise any forward-looking statements.

During this call, we will also be referring to certain financial measures that are not prepared in accordance with U.S. generally accepted accounting principles or GAAP. A reconciliation of these non-GAAP financial measures to the most directly comparable GAAP financial measures is included in the press release filed earlier today.

With that, let me turn the call over to Jeff Hawkins.

Good afternoon, and thank you for joining us. On today's call, we will provide a business update and review our operating results for the fourth quarter and full year of 2025 and provide an outlook for 2026. After that, we will open the call for questions.

Before diving into specific updates, I want to first frame at a high level how we are thinking about 2026. We expect that 2026 will be a transition year with revenue primarily driven by consumable utilization from our installed base and some new placements, very modest new capital sales and a laser focus on Proteus development and preparing the market for a strong commercial ramp in 2027 and beyond. As a reminder, our 3 corporate priorities for 2025 are as follows: to accelerate commercial adoption to deliver on our innovation road map and to preserve our financial strength.

Our first corporate priority was to accelerate commercial adoption. Our revenue for the fourth quarter was $451,000 as top line results continued to be impacted by the capital sales headwinds in the market. As we look to 2026, we believe that our placement program will continue to allow us to engage with new customers and capture consumable revenue, but that capital sales of our first-generation Platinum Pro instrument will be very limited, given the deliberate focus on market preparation for the Proteus launch at the end of 2026. We will provide more color on this topic throughout the call.

As a reminder, during the second quarter of 2025, we announced the launch of an expanded set of instrument acquisition options that allow customers to have our instrument in their lab and purchase and run consumables without having to find the capital dollars to acquire the instrument upfront. By all measures, this program has been a success, and we view it as a key market development program to continue with during 2026 as we build momentum into the Proteus launch.

Since launching the program, we have secured 17 new customers spanning academic labs, pharma and biotech. It has allowed us to access key opinion leaders in some of our direct markets that we had not had access to prior to this program. We view these labs as strong long-term prospects for Proteus and we believe that being able to engage with them now and have their laboratory staff get hands-on experience with our technology will improve the prospects of them adopting Proteus once launched. In addition to capturing consumable revenue from these 17 customers, we are also building a strong publication pipeline that will help to further demonstrate the value of our technology across a range of applications.

Turning now to Scientific Affairs. As we have previously shared, developing a publication pipeline takes focus and effort over an extended period of time. During 2025, we had 5 manuscripts submitted for publication and built a strong pipeline of additional studies and manuscripts for future publication. The time we invested in this area in 2025 continues to yield results and we have already seen 3 new manuscripts released via publication or preprints in the first 2 months of 2026. More important than the number of new manuscripts is the range of applications we are beginning to see emerge.

One of the papers from Dr. Lowe of Stanford University showcase the potential of our technology to be applied in the field of clinical proteomics to address complex conditions like hemoglobinopathies that are not easily resolved using current technologies. The second example of a new application of our technology was captured in a manuscript from the researchers at the U.S. Naval Research Laboratory. They described a modified workflow that enabled biological sample to result in under 24 hours for rapid pathogen and toxin detection, an area that is underserved by existing technologies.

We believe that these papers and others in the pipeline will continue to demonstrate that the potential opportunity for our technology extends well beyond the basic research markets that we operate in today. We believe that this is important since these new applications move us towards customers who typically have high consumable utilization rates and repeat ordering patterns.

Beyond these initiatives, we continue to monitor and evaluate several partnership opportunities that may further accelerate certain components of our development activities spanning from new customer applications to sample preparation and enrichment and applications of artificial intelligence tools that could extract deeper insights from the protein sequencing data our system generates. Novel enrichment technologies for very low abundance, high-value biomarker analysis is a key area of interest for us, and we are currently exploring some promising partnership opportunities in this space.

As I stated earlier, our focus in 2026 is on the development of the market for Proteus, which we expect to launch at the end of this year. This started in earnest at our October 2025 Investor and Analyst Day, where we showed data demonstrating that Proteus is surpassing our first-generation technology across all key performance metrics. While we indicated during the event that sharing the early Proteus data would likely impact Platinum Pro sales, we believe that sharing this data would allow us to more effectively engage with potential customers and channel partners about budgeting for Proteus well in advance of its launch.

Based on customer and channel partner feedback to date and to continue to advance the Proteus prelaunch discussions, we decided to pull forward the announcement of our list price from the second quarter of 2026 to today. Accordingly, we announced that the list price for Proteus will be $425,000. We believe this list price strikes the appropriate balance between capturing the premium value of Proteus and the expected launch capabilities while also making the platform more accessible to a larger number of potential customers than existing technologies.

Our second priority was to deliver on our innovation road map. 2025 was a successful year across all of our development programs. We launched our version 4 sequencing kit and an expanded set of 24 barcodes during the third quarter of 2025, our version 3 library prep kit in the fourth quarter of 2025 and most importantly, demonstrated sequencing on a prototype Proteus system, which exceeded our current system across all performance metrics at our November 2025 Investor and Analyst Day.

We also shared our progress and plans for expanded proteome coverage and PTM analysis capabilities as well as the feasibility of a controlled cleavage chemistry, a critical piece of core technology that ensures we have a clear, executable path to our long-term goal of enabling de novo protein sequencing at scale.

As we look to 2026, our full focus is on Proteus development. I am pleased to report our instrument development efforts remain on track. Our prototype systems continue to perform well and are fully deployed within our internal R&D efforts. We have also received our first fully integrated Proteus instruments and are working with our partners to continue to manufacture and deliver additional instruments to support the scale-up of our internal development work.

Next, I want to provide an update on our efforts to improve proteome coverage, which spans 2 key areas: one, expanding the number and frequency at which we detect individual amino acids and two, the sequencing read length we achieved. I would like to take a few minutes to touch on both areas.

First, during our November 2025 Investor and Analyst Day, we shared details about our proprietary amino acid recognizer development program. Specifically, we shared about how we had recently seen a significant improvement in our performance of developing new amino acid recognizers, through a combination of applying state-of-the-art artificial intelligence tools trained on our proprietary data and by scaling up the throughput of our candidate screening and selection process.

At the November 2025 event, we stated that we believe that we would be able to launch Proteus with detection of 18 amino acids and would further demonstrate detection of all 20 amino acids in 2026. I am pleased to report that we are progressing ahead of expectations on both goals and expect to provide a more quantitative update on this topic in the near future.

The second component to proteome coverage is sequencing read length. Prior to sequencing, customers prepare their protein sample using our library prep kit. The library prep process digest the proteins into smaller pieces called peptides and then attaches a linker that allows the peptides to bind to the nano wells on our consumables. Based on the method of digestion our library prep kit deploys, the average length of the peptides generated is approximately 18 to 20 amino acids.

As we shared at our November 2025 event, the early data on Proteus indicated that the average sequencing read length on Proteus was superior to our existing platform. This means that the number of amino acids we can sequence per peptide was more than we can with platinum. A longer sequencing read length is important as we look to unlock certain high-value applications for customers like deep PTM analysis and profiling.

I'm pleased to report that we are continuing to observe longer sequencing on Proteus and based on continued promising results, we have dedicated some members of our R&D team to focus on maximizing sequencing read length. We look forward to providing more quantitative updates on this area in the months ahead.

Finally, I want to take a moment to review our progress and forward plans with library prep. We launched our version 3 library prep kit during the fourth quarter of 2025. The Version 3 kit enables customers to sequence samples with as little as 1 to 2 nanograms of protein. Overall, the version 3 kit delivered a more than 100-fold reduction in input required over our prior library prep kit. As part of that development effort, the R&D team identified some potential avenues to explore for even further reduction in input requirements. We have a small team working on technical feasibility now, and we'll have more updates to provide on our next earnings call.

Our third priority was to preserve our financial strength. We believe that the data will continue to demonstrate that Proteus is not only a new architecture with greater throughput and automation, but also a significant leap forward in terms of sequencing performance and application breadth. We also believe that Proteus is well positioned to be the long-term driver of commercial adoption, revenue growth and our path to profitability.

We are fortunate to have a strong balance sheet that allows us to execute on this strategic plan with a focus on long-term value creation, but also acknowledge that the Proteus focus in 2026 will impact top line results. We are committed to continuing to operate with a high level of fiscal discipline while ensuring the core strategic initiatives are appropriately funded to deliver on time and with the capabilities customers are asking for.

I will now turn the call over to Jeff to review our financial results.

Thanks, Jeff. I'll now walk through our operating results for the fourth quarter and full year 2025 and then provide our outlook for 2026. Revenue in the fourth quarter of 2025 was $451,000, consisting of revenue from our Platinum line of instruments, consumable kits and related services. Gross profit was $122,000, resulting in a gross margin of 27%. Gross margin in the quarter was primarily impacted by revenue mix with a higher proportion of consumable revenue to hardware as well as certain inventory adjustments recorded during the period.

For the full year 2025, revenue was $2.4 million, gross profit was $1.2 million and gross margin was 47%. Full year gross margin benefited from a higher mix of instrument sales and a lower overall impact from inventory adjustments compared to the fourth quarter. As Jeff stated earlier, we have been impacted by capital headwinds throughout 2025, first, starting with delays in NIH funding and concern over the overall NIH budget and indirect reimbursement rates as well as general uncertainty around tariffs and putting customer capital budgets in limbo as they look to prioritize what they spend capital dollars on in an uncertain environment.

Turning to expenses. GAAP total operating expenses for the fourth quarter of 2025 were $21.2 million compared to $31.3 million in the fourth quarter of 2024. Adjusted operating expenses were $18.3 million compared to $26.7 million in the prior year quarter. For the full year 2025, GAAP total operating expenses were $117.3 million compared to $110.2 million in 2024, while adjusted operating expenses were $86.3 million, down from $99 million in the prior year.

The year-over-year reduction in adjusted operating expenses reflects continued cost discipline, more focused R&D activities and targeted resource allocation towards advancing the Proteus platform. Included in full year GAAP operating expenses were charges of approximately $18.7 million, primarily related to the accounting adjustment of a net termination payment and associated asset write-off from a lease facility in New Haven, Connecticut as well as settlement and preliminary settlement of certain legacy litigation matters.

Dividend and interest income was $2.2 million in the fourth quarter of 2025, consistent with the prior year quarter and $9.7 million for the full year of 2025 compared to $11.4 million in 2024. The year-over-year decrease for the full year reflects lower interest rates and changes in invested balances. As of December 31, 2025, we had a $215.8 million in cash, cash equivalents and investment in marketable securities.

Turning to our outlook for 2026. We are anticipating total revenue to be approximately $1 million, with adjusted operating expenses of $98 million or less and total cash usage of $93 million or less. We view 2026 as a deliberate transition year for the company as we prepare for the anticipated launch of Proteus at the end of 2026.

We are making intentional choices that prioritize long-term platform adoption over near-term revenue maximization. This includes embedding upgrade pass into Platinum Pro units, which has a near-term revenue impact as well as impacts of customer delayed purchases as they plan for Proteus as we continue to educate and prepare the market about the leapfrog capabilities of our next platform.

From an operating expense standpoint, our guidance reflects the activities required to complete the development in support of the successful commercial launch of Proteus by the end of the year, while continuing to manage costs with discipline. Our expected cash usage also includes modest inventory build and commercial readiness efforts ahead of the launch. With $215.8 million in cash and investments at year-end, we believe we are well positioned to execute on our strategy and support operations into the second quarter of 2028.

As we look past 2026, I will remind you that we have built our operating expense structure that leverages key external partners for development-related activities as we complete these activities, including launching Proteus, we have the ability to reclaim this operating expense spend to augment our cash runway or strategically redeploy some to other activities such as commercialization activities.

I will reiterate what Jeff said on how we're thinking about the business in 2026 and as we move forward. Again, 2026 reflects a transition year with intentional trade-offs. We're expanding our installed base in a capital-efficient way, maintaining customer engagement and data generation and positioning the company for the Proteus launch rather than optimizing for near-term instrument revenue. Importantly, we are executing the strategy from a position of financial strength. We have the flexibility to fund development, commercial readiness and ongoing operations without being forced into near-term capital decisions.

Finally, management and the Board remain deeply aligned with shareholders. Insider ownership remains very meaningful and recent Form 4 activity reflects routine tax-related mechanics associated with equity compensation vesting with no management team members selling shares outside of planned mandated selling for required tax withholdings. Overall, we believe we are making the right trade-offs, prioritizing long-term platform value over short-term optics and positioning Quantum-Si for what we believe will be a highly meaningful next phase of growth.

With that, we're happy to take your questions.

And our first question for today comes from the line of Scott Henry from Alliance Global Partners.

Just a couple of questions. First, what are you seeing as far as consumable trends as far as the trends within the installed base?

Yes, Scott. So we're continuing to see customers purchase at a consistent rate. As we said in the past, the academic customers will sometimes purchase more episodically by consumables, complete the sets experiments, then publish data before buying again. Other segments of the market will have a more consistent order pattern. But if you think about -- maybe one way to think about it is the guidance we gave for revenue this year, we're expecting very modest CapEx.

But what is baked into that guidance is we're expecting a more than 25% increase in the number of consumable kits that are being run by our customers. So we are seeing that utilization improve. And we think what we're learning and how to do that and how to really drive that, we think learning that now and getting that really well understood process will be obviously very important as we get to Proteus and look to drive the utilization of that system as well.

Okay. So if I'm interpreting that correct, for 2026, in anticipation of the Proteus launch, we should really factor in very few placements with almost all the revenue coming from consumables and service revenue.

Yes, I think that's correct. A lot of the revenue obviously coming from consumables or the services revenue. In terms of the capital equipment side, maybe just a couple of pieces of information. The first is, yes, we expect a fairly modest number of Platinum Pro machines being purchased for capital.

The other point to make on that, that's a little bit of a nuance, but it's important, Jeff talked about in his remarks that in some instances, customers are might want to buy a Platinum Pro, but they'll be asking for a credit for a future Proteus machine. And if we offer that credit it can sort of alter the revenue recognition in the short term, capturing it over the full period of time when they eventually purchase a Proteus. So there is that component to it as well if people have that credit sort of reduces the recognized revenue in the short term.

Okay. And then I know you're not looking to give guidance into 2027, but in a bigger picture type of way, can you talk a little bit about how we should think about the launch curve for the Proteus? Would you expect early adopters to use it right away and then kind of the typical S-curve or just how we should think about the traction, given that you already have the Platinum on the market, so is somewhat educated customer base. But just kind of qualitatively, how you would think about that.

Yes, I think about it in a couple of distinct sort of groups of customers. To your point, we have existing Platinum users and some number of those people will certainly move over to the Proteus over the course of the first year or 2 of the launch. I think it really is going to depend upon exactly which applications are available at launch. And then sort of what are the other potentially transitional financial incentives we might give to those customers to help them move with us earlier in the launch curve.

So I think about the existing installed base in that way. A lot of people do know about Platinum and Platinum Pro, but I can tell you from the early feedback I'm hearing from our team in the field as they're out talking about Proteus. We are also getting in front of a lot of people that we've had no access to or fairly limited access to prior because the applications that we are offering on Platinum Pro might not have met their needs where now with some of those capabilities being communicated as coming with Proteus is opening the door to be able to talk with those potential customers. I think that's a new sort of set of customers that don't have a Platinum today and are now engaging with us. So I think about those folks, they'll probably follow a more sort of sequenced. Some people will adopt early, some will wait to see. So that group probably moves in a more classic new technology introduction sort of way.

And I think the third piece, the third sort of leg of the stool in this case is really our channel partners. As we've talked about on prior calls, we've built a global channel partner network. We think we've got all of the major markets covered with that. Will every one of those markets be a good fit for Proteus? That's something we're really working through. We do have a really important channel partner meeting coming up this month where we're going to get together in person with these partners.

I think we'll learn a lot at that meeting about really which of those partners and which of the markets are going to be good opportunities for Proteus. And obviously, that -- the access to those markets can help us early in the launch as our partners are also investing and working to build out their installed bases.

So that's how I think about it. I mean, there will always be some stepwise fashion to the commercialization. But I think this year and what we're committed to is really helping you understand exactly how we're building that momentum towards that launch to try to have that sort of curve, go efficiently and sort of reach that inflection point we want over sort of maybe a longer early access period that we went through with the Platinum machine.

Okay. Great. And just the final question, which is just more clarification. The $98 million in guidance for operating expenses, is that -- does that include stock comp? Or is that more of just a cash expense guidance number?

Scott, this is Jeff. Yes. So that includes -- that's kind of our adjusted operating expense number. And for adjusted operating expense, we do pull out stock-based compensation. We think that's -- on an adjusted basis, that's kind of the more reasonable way to look at OpEx that's more cash oriented as we look forward.

And our next question comes from the line of Swayampakula Ramakanth from HCW.

With you announcing the price point for Proteus, I'm just trying to understand what it means. Does this mean that you have some secured preorders or letters of intent that you feel comfortable enough to put the dollar amount, I mean, the price point out this early.

Yes. Good question, RK. We don't have any secured orders to communicate at this time. I think we're putting the price out because what we're seeing as we're out talking with customers and some of the questions we're getting from our channel partners in preparation for our meeting this month is they're looking for that price point to be able to do their capital planning. We are aware of a few grants that some customers are working on that are going to be due over the next couple of months for their sort of regular capital planning cycle. And to ensure we get incorporated in those submissions, we need to be able to provide that price.

So we see this as sort of helping to continue that dialogue with customers, help them have the data they need at the time frame when their grants or their tenders, if they're located in international locations are due, they're going to need that price point. So that's why we're releasing it now is to ensure we get incorporated into those proposals and that we get incorporated at the right level in that to the extent they get funded, they've got the right amount of dollars got aside to purchase the machine.

Okay. And then based on some of the commentary that you've been talking about, how people spending on capital expenditure is -- it has been a tough one for at least in 2025. So going into 2026, with this particular price point, do you see folks go the lease purchase method? Or do you think that there will be decent number of potential clients who would actually purchase it for cash.

Yes, RK. So maybe the first point to make here is at this time, we've only communicated a list price and an ability to purchase a Proteus through a straight capital purchase. We haven't extended some of the other purchase or acquisition sort of models to Proteus at this time. We're going to continue to do those other models with Platinum Pro, but we haven't yet committed to doing that with Proteus.

I think we're watching a couple of things. I think the first thing is, obviously, some of the NIH uncertainties, at least appear on paper to be improving the most recent NIH budget is about a 1% reduction over the prior year, so much less dramatic cuts than originally thought. I think importantly, and Jeff called this out in his remarks, but to reiterate, the indirect overhead rates are not changing in 2026. That was a pretty significant concern for customers in '25 as indirect often are a source of the funding for new equipment. So I think it's we're sort of fortunate in that regard.

Proteus is probably the bigger impact on Platinum sales. But on the flip side, we'll get to see sort of a more stable NIH environment for a year here before we're in the market with Proteus. And again, taking steps deliberately in our engagement with customers, including with the list price, they really try to get into those grant applications, those tender proposals here early such that those capital dollars would be ready when we get to launch in our delivering units out into 2027 and beyond. So that's really how we're thinking about it and sort of the things we're watching.

Okay. And then the last question for me is, when you're talking about trying to identify more amino assets than what you thought you would have by the time you get Proteus into the market. So are we thinking that we could be closer to 20 M&A assets by the time you launch? Or I know you didn't give specifics, but I'm just trying to understand from your excitement. So where do you think we'll be heading by that time?

Yes. So RK, we're thinking about it in a couple of different ways. I think that I commented on, and maybe I'll try to add a little bit of color here. So we're focused on, obviously, how many of the 20 amino assets can we detect. And in that regard, we said we believed we'd be able to launch produce with 18, and we would demonstrate 20 this year.

Now when we communicated that, we, of course, expected to demonstrate 20 by the end of the year as we show in our Investor Relations materials. And obviously, the later in the year, that is then it pushes out sort of the delivery into 2027 with enough time to sort of do reagent development. So as we are able to sort of make progress there sooner, it opens up the prospects of that getting all 20 getting into a kit sooner into the launch of Proteus than maybe we originally anticipated.

The other factor is we're really looking at the combination of a number of amino acids, the frequency at which we detect those in all the different sequencing contexts and then adding in sort of that additional layer of how long is the sequencing [ read length ]. And if you put all these together, we're really focused on is how much of the protein are resequencing, how much of that protein are we seeing? And the more we're seeing the more sort of applications open up the deeper the ability to analyze samples for PTN and other things become.

So I think we're seeing sort of progress across all of these areas sort of ahead of the pace we expected when we laid out sort of that road map at our Investor and Analyst Day. And I think we're committed to you and the rest of analysts and investors that we'll provide some more quantitative sort of milestones on this as we go this year to help you understand sort of what level of improvement has been made here over say, the existing commercial kit. We're going to do that as we move through the year, but it's sort of on all of those factors where we're seeing really positive progress from our teams and feel good about the capabilities we'll be able to deliver not only at launch but getting to that full 20 is soon after launch as we possibly can.

And our next question comes from the line of Michael King from Romita Renshaw.

Congrats on the progress on the technology front. I'm just wondering, as far as Proteus is concerned, when you look at your existing customer base versus the potential customer base for Proteus. How much overlap do you think there really is? Are the -- are they similar? Are they the same? Or are they not the same at all. And if the latter will each of your sales be sort of a conquest sale as opposed to repeat customer sale?

It's a good question, Michael. So we haven't really tried to quantify exactly what the overlap is. But maybe I'd speak about it a little more qualitatively. So we've talked about before our Platinum machine is in sort of a wide range of labs. So a good number of our Platinum machines, as you can sort of pick up on by looking at the publications are in of what I would call a core lab, a large academic center, who's got mass spec and other technologies and a lot of sort of proteomic analysis capabilities.

So a good number of our machines, both in academia, but also in pharma are in what I would call more classic proteomic core labs. Those folks are, in our view, are going to be a very good potential fit to move from Platinum or Platinum Pro machine and into the Proteus. Some of our machines, though, because of the price point of the Platinum Pro machine are in what I would call smaller basic research laboratories, perhaps a single investigator with a fairly small laboratory staff. So some of those folks might not quite have the volume of research or the level of funding needed to move the Proteus.

That said, there could be groups of, say, 2 or 3 investigators in some of those institutes that made pool funds together to purchase a Proteus. So a little harder to figure out the exact ratio of of those smaller individual investigator labs converting to Proteus, but we think some of them will really where we're focused with some of this initial sort of transition or upgrading will be amongst those larger core labs, proteomic centers of excellence that really are pretty ideal fits and where we think that overlap between use of Platinum today and use of produce in the future could be a pretty high level.

Okay. for the additional color. I'm just wondering, you talked about in your formal remarks, the interaction you've had with clients and the -- not necessarily implementation, but the design or conceptualization of kits. Are there sort of a couple of applications that are low-hanging fruit, whether it's, I don't know, kinase pockets or other GPCRs, other sort of validated drug targets or perhaps detection technologies like for biomarker work, where do you see sort of the top 2 or 3 applications giving you a tailwind on launch?

Yes. I think we're -- we obviously, through the Platinum machines being in the market are working with customers, not only across a lot of segments, but across a lot of different sort of disease areas. I think we talked a little bit in the prepared remarks about some of the data that came out recently from Stanford that's in hemoglobinopathies. That's an example of sort of a clinical application, something we hadn't really conceived when we came to market with platinum, but a great application of sequencing a single amino acid change drives the diagnostic drives the sort of the treatment outcomes.

I think when we think about Proteus, I still think about it right now in somewhat broader set of capabilities, and I think we'll refine our point of view on maybe specific disease areas or research areas as we get closer to market. But I think the broad capabilities we really want to make sure we have is with the Proteus having a lot more sequencing output, one clear opportunity is to really work with much more complex biological samples, right? So that's -- that today is a limitation with our current platform. That opens up people doing work in sort of identifying new biomarkers that could be academically, that could be in -- that could also be in pharma and biotech.

Post-translational modifications, Michael is a big focus of ours. That's an area today that some people have applied our tech to. It takes a little more work on customers' side today to do that with our current technology and the capabilities and the analysis tools but it's an area that we're dedicating a lot of time to. And as we lift this overall proteome coverage, it's really going to enable that area. And we think that that's important in discovery of biomarkers. That's important in translational on validating those biomarkers on a high number of samples. And whether that's for a therapeutic target or for a diagnostic biomarker, the PCMs, we think, is a key part.

And that sort of ties me to the last piece, which is that translational lab is a lab we haven't been in as much today. We're often in -- we're in a core lab or we're in a basic sort of biology research lab, you're doing very fundamental research, translational labs, taking those defined biomarkers and trying to scale up that work on a large number of samples to validate it's linked to disease or its diagnostic potential or treatment response, whatever that end point might be. We don't have as much exposure in those labs today, but we think the ability to look at PTM, the ability to look at more complex samples really helps us start to line up to fit into that translational lab where we would expect them to be doing that type of work, and those labs are typically also your more consistent consumable utilizers than some of the more fundamental research labs.

Great. And then sorry, if you just indulge me one more. Just as far as the total spend is concerned, does that include or anticipate some increase in the field sales force? Are you going to be adding bodies to get out there?

Michael, this is Jeff Keyes. Yes. So for 2026, our total spend includes completing out the Proteus development program and augmenting our commercial team to be able to be launch ready as we get into the end of the year and into 2027. As I mentioned as well, once we're done with the development of the Proteus program, we've utilized a lot of outside spend for development activities. And once the program is concluded, we have the ability to pull a lot of that outside spend back and then either make it for additional cash runway or redeploy it to other activities.

So there's also an opportunity to redeploy to commercial activities. But as we plan for our 2026 guidance, we are fully funded from a commercialization standpoint. And obviously, that will be evaluated over the course of 2026 to make sure we have the right resources, right partners and right deployment for the Proteus launch.

Our next question comes from the line of Kyle Mikson from Canaccord Genuity.

[indiscernible] provide some detail on this. So I want to ask this question of what exactly you've heard from customers that gave you confidence to slow things down on the Platinum side and then move all focus to Proteus. And I'm wondering if that came from just maybe just elaborate a little bit on what the [indiscernible] was and if that came from the new customers that Proteus kind of for you or if it was from the existing base?

Yes. I think, Kyle, the way to think about it is for or some of the customers, it's really a question of do they deploy capital dollars today or a Platinum when the Proteus is coming. I think for those customers who see an opportunity to use the existing technology for their work today and eventually grow into the produce. We are taking advantage of our ability to use the placement program to get access to them.

As we said in the prepared remarks, I think it's a good data point since we launched that program, we've placed instruments and unique customer end points. So I think when the current tech fits, and it's really more about they don't want to purchase today, knowing something new is coming, we do have that placement option to work with them get them on the technology, get them utilizing it and then convert them in the future.

I did mention earlier, if someone is purchasing a Platinum machine and wants to make sure they're protected from sort of the Proteus launch and making sure they have some financial benefit of that. We're certainly prepared to extend credits to those folks. And then I think there are a third bucket of customers, which are they want to be able to do something in terms of maybe the complexity of the sample or the throughput of work that just doesn't match up well to Platinum. So Proteus will be their entry point to working with Quantum-Si.

So I sort of break people into those 3 buckets, and I think many people fit in either the first one where we access them today with the placement, moving them into a produce in the future or they're going to be Proteus first because it really is more about aligning what they're trying to accomplish with the capabilities of that platform.

Okay. Thanks, Jeff. And it's just interesting because like in theory, Labstat were willing -- like would be willing to buy a Platinum for less than $100,000, would be willing to or comfortable with this price point. So I wanted to ask you what the list price a little bit. I know that was -- I think you touched on it earlier in a prior question.

But the price is obviously almost equal to what you just did in revenue in the fourth quarter. I know there's a lot of dynamics going on, but maybe there are some new customers that you'll be able to target now that have access to more funds or they're more affluent. And overall, just again, just kind of curious what gives you comfort that the price point is going to be appropriate given the uptake that we've seen with Platinum thus far.

Yes. I think there's a couple of factors in play here. I think, obviously, there are some new customers that we can get to that we just can't access today. I think, as an example, we've talked about this in the past. In core labs today, we're often sort of a complementary platform to other platforms. And some of our labs then are the smaller individual investigator labs. So obviously, Proteus wouldn't be a great price point in those smaller individual investors or labs.

But in the core labs, if you think about the price point we're at and the capabilities we're talking about $425,000 is sort of about in the middle of what they're sort of -- maybe even the lower end in some of the best sort of the high-end mass spec machines can run upwards of $850,000 up to over $1 million each. So we don't think $425,000 in terms of those core labs and some of those higher volume sites is at all an impediment.

I think it really comes down to what are the capabilities of the platform and do they address either very difficult things to do with their existing tech? Are they answering very important questions that researchers want to study. And if you do those things and we believe Proteus is going to have those capabilities, specifically things like PTMs, the complex biological samples the increased proteome coverage will have to do things like sequencing antibodies and looking at variable regions. These sort of things that are very difficult to do unless you own that $1 million mass spec machine and have all the custom infrastructure, when you start positioning Proteus in that context, a $425,000 price point, I think, is a very reasonable place to be at. It captures our value, but makes it more accessible than those sort of $1 million price points.

But yes, I think you're correct in one way that is that smaller individual investigator who has a lot less funding is probably not going to be the perfect target. But again, the way we view those as might there be 2 or 3 of those investigators that would look to pull money together to purchase a machine and have this capability. That's not something we've had to do today with Platinum or Platinum Pro, but certainly something you see in our industry in spatial and other areas where smaller investigators pool together to have the capability to do things when sometimes it's not offered at the core lab or somewhere nearby for them.

Got it. Can you just clarify, would you launch Proteus with the rental kind of program as well? Or would it be solely kind of direct in term of sales?

Yes. Right now, we are -- we've only announced the list price and the intent to do direct capital sales. We -- I think we'll start there. We'll get feedback in the market and then decide if we want to open up other acquisition models. But right now, our intent is to launch with only the ability to do a direct capital acquisition and then sort of get the market feedback and decide if we open that up to other things over time.

Okay. And then Jeff Keyes, it sounds like the mix will be mostly consumables this year, almost entirely symbols. So that would typically mean higher margins for most tools companies. But I think in your case, consumables seem to have a lower margin compared to the instrumentation. So I guess, I know you're not guiding to gross margin, but how low could it get to this year relative to the mid- to high 40s that you've been at recently in the past couple of years?

Yes. So I think your comments are reasonable and everything else being equal, our consumables have a lower margin than capital equipment, but there's a couple of things going on here, too, because during the course of 2026, we expect to have some capital sales and some placements as well as consumable revenue, but the caveat on that is on the capital sales. We anticipate a lot of them to have this credit towards Proteus for future acquisition of a Proteus model that has deferred revenue. that, that will be impacting our overall margin as well. So I don't think we're going to have specific guidance for margin specifically.

But having said that, I think you can expect reasonably it's going to be lower than that kind of 40% to 50% range that we've had for the full year. and it will evolve and be impacted simply on the number of credits that we provide for Proteus for the actual capital equipment sales of the [indiscernible]

In the entire -- [indiscernible] maybe I can add one additional piece of color. I think consumable volumes in terms of production volumes are still rather modest today for us. And obviously, in our industry, getting to scale on that is a key component to achieving sort of the desired gross margins for consumables. I'd say that, though, and just remind us all that and we've talked about this on other calls, and we talked about it extensively at our Investor Day, 1 of the reasons to move to the new architecture with Proteus was not just sequencing output and automation, but the consumable architecture, moving from a CMOS-based chip to a passive nano well array, there's a significant advantage to us in terms of our cost of producing those not only at scale, but even in the earlier days of building that product.

So I think there's a couple of factors in play here, the consumable architecture run and being at fairly low volume. And again, we factored both of these things into that technology decision as we sought out to develop Proteus and the associated consumable architecture.

Okay. And then Jeff Hawkins I want to ask like a Proteus question for you. So what would be the biggest risks, I guess, to launching Proteus, like in this R&D ramp that you got going on what could happen to the downside that could cause that's about '27, for example? And then secondly, I'm just wondering how important is to actually obtain that 20 amino acid kind of milestone because maybe that sounds like a big driver on '27, '28, but maybe that's more critical to about the long-term aspect launch for growth drivers to novo sequencing or PTM detection and things like that.

Yes, Kyle. So I'll work backwards with you on this one. So I would agree with you that I don't think the 20 amino acid detection is the key driver, certainly in the early days of the Proteus launch. I agree with you that coverage is obviously -- it's always a net positive to customers when you can detect more amino acids, it's obviously clearly important as you try to get to de novo sequencing. But I would agree with your general thesis that the 20 is not -- 18 versus 20 is not going to be the major driver of customer adoption of Proteus when we launch it.

I think in terms of risk of launch, I always break product development programs down into sort of 2 key things. One is have you gotten through the innovation and invention phase of the program, meaning the technical risk has been taken off. And for us, the answer to that is unequivocally yes. The invention occurred, the big innovation leads have been made. We've demonstrated sequencing on prototypes. We've got multiple running. We're getting integrated units and expect to communicate sort of progress on those over the coming months.

So I feel like that technical risk component of the development where you still have to get that big breakthrough come up with that aha moment. That's behind us now. This is really now a focus on the second phase I see in product development, which is really the hardware integration, the bringing up of the manufacturing capabilities, working on things like optimizing performance and reliability, these what I would call more classic system integration or sort of hardware engineering. That's where we're at, and those are the things we're doing.

Could you hit a bus in the road and that takes a little bit longer sure, that could happen. But I think when those -- when you're in that phase of development, if you get delayed, you're talking about delays sort of on the level of a few months, you're not talking in quarters and years like you are if you're back in that innovation phase. So again, we feel good about launching by the end of 2026. But if you want me to paint for you what the risk is, I think the risk is some of those steps of getting the performance where we want it to be, the reliability, where we want it to be, the manufacturing quality where we wanted to be.

If any of those things get delayed, again, I think we're talking about a much shorter time scale than some of the big chunks of delays you see with technologies that are still back in that innovation and invention sort of phase of development.

Awesome. And then just final one. I think you guys are one of the last tools companies to report earnings here and it's timely given the White House ONB, the Office of Management and Budget. They've been slowed authorized the release of NIH awards. We obviously had this budget that you referenced, Jeff, there might be a deadline kind of soon for this for OMV. So are you hearing anything on that front and maybe any risk for more uncertainty with respect to the kind of NIH academic funding like this year?

We haven't heard anything new beyond the color I gave. I think we're aware of what you're describing. We haven't heard that though through the through the customer channel, meaning people saying they need to get a budget in by a certain time. I think what we're focused on with customers are often sometimes it's related to NIH, but often it's just what's the capital budgeting cycle of their institution. They have to have they are requested by April or May in order to be funded in a certain time frame or tenders internationally, they have to be in by a certain time in the summer to fund the next year.

So we're doing more with like sort of financial calendars than we are sort of a push right now related to anything out of OMB or out of the NIH. But I think we'll keep a close ear to the field as that unfolds, but nothing coming yet inbound from customers. We'll have to sort of see if that changes as the information works its way through the market and to our customers.

This does conclude the question-and-answer session of today's program. I'd like to hand the program back to Jeff Hawkins for any further remarks.

Thank you for joining our call today. We look forward to providing more updates on the Proteus program and the continued progress towards commercial launch on our next earnings call. Thank you.

Thank you, ladies and gentlemen, for your participation in today's conference. This does conclude the program. You may now disconnect. Good day.

All right. Good morning, everybody. I appreciate everyone being here in person. And for those online, welcome as well. I want to kick off today, give you a quick overview of what we're going to accomplish during this presentation, and then I'm going to try to set the stage with sort of the complexity of the proteome and the challenge we're trying to solve that I think will then tie nicely to what you're going to hear today both on the hardware road map side, but also what we're doing on the chemistry side. So again, I'll kick off. Todd will take you through Proteus, where we're at with that program, the data underlying that technology and where we're at and why we feel very confident in sort of the leap it's going to make in performance. Also give you a small peek into what we have going on, on the technology road map. Proteus is actually the preponderance of the spend today. It's the majority of what we invested in R&D, but we do have modest investments into that longer-term view, and Todd will help you sort of see what those are and how they intersect.

John will get into how we're going to get to 20 amino acids and how soon will we get there, and he'll give you details on that. And then Brian will sort of cap it off with and how do we translate all of this in this toolkit with this core technology for kinetic detection into post-translational modifications. I'll close out with how do we sort of get to launch, what milestones should you expect to hear from us over the course of the next year.

So to kick it off high level, proteomics is sort of a massive market. There's a lot of different segments in the market. Today with our first-generation technology we play in academic research. We have some pharma biotech, defense and even more recently in agriculture. So it's a huge market, a lot of different applications of protein detection technologies, but it's also extraordinarily complex. And I think we often talk about the proteome or proteoform. So at the basic level, you have about 20,000 proteins. But when you take into account all of the post-translational modifications, the isoforms, the single amino acid variants, you get into the range of sort of millions of proteoforms that you have to tackle. So it's an immensely challenging problem. And it's not specific to a single disease.

I think, obviously, in the market today, there's a lot of noise around tau protein and Alzheimer's disease. But proteoforms play a role in many disease areas. They play a role in cardiovascular. They play a role in cancer, immunology, just many fields. And I think the key is -- this means affinity-based approaches are going to be nearly impossible to scale to this type of complexity. Think about 20,000 proteins and some of those proteins having multiple different modifications. The number of reagents you would need is just sort of a daunting almost impractical task. And while developing a single molecule protein sequencing technology is not easy when you achieve the level of capability you should be able to do with this, and I think the R&D leaders will demonstrate today, it is applicable to this challenge at this scale, the scale of all of these different proteins and all of these different changes.

So here's a good example. I think tau protein probably has the most visibility in our market today. Obviously, a phosphorylated version of this protein is a diagnostic biomarker in Alzheimer's. It's a target of a therapeutic. So it gets a lot of attention. But if you go into the literature and you look and this study here is from Dr. Kelleher at Northwestern University in Chicago. What they've shown is it's way more complex than just that. There's probably many more biomarkers to mine inside of this protein. And you see here some of the readout they have, everything from phosphorylation to acetylation to methylation. So multi-PTM across many proteins is the scale of the problem that's trying to be solved. But variants also matter.

So here's a good example in the clinical side. So in this case, sickle cell disease, but there's a range of hemoglobinopathies, which are all single amino acid variants that lead to a different phenotype. So this is a great example of sometimes it's a post-translation modification, sometimes it's a single amino acid variant. So again, if you think about sequencing as the method, reading out the amino acids, reading out the PTMs, it gives you that breadth you need to really cover the range of complexity of not only biology research, but diagnostics. So what happens today with this complexity? Well, what happens is essentially labs own a lot of specialized equipment. And most of those pieces of equipments cost in the range of sort of $1 million. So it ends up being a very centralized core lab heavy model. And those instruments, while very powerful, many of them have pretty laborious manual laboratory workflows, the data analysis, a lot of custom pipelines and different things. So again, sort of centralizes the market to large, well-funded sort of high infrastructure core labs.

So when we think about Proteus, that's really what we think about. First is the core technology. What's the best way to tackle this daunting problem of 20,000 proteins and millions of proteoforms. Again, I think the R&D leaders today will do an effective job of helping you understand why we think single molecule protein sequencing is the way to do that and do it in a protein-agnostic way. Automation is a big part, the data analysis, the laboratory workflow. So today, we'll give you a little bit of a feel for how much automation are we bringing to the table here with the Proteus platform as it compares to our current Platinum Pro. And then affordability, these machines, as I said, run up to $1 million or more. We think there's a way to do this and not be up in those price points. We think there's an opportunity to make this more accessible to a broader number of laboratories, both here in the United States and globally and really bring deep protein analysis to the masses.

So today, where will we focus? So we'll start with Todd. He'll take us through the Proteus platform. He'll give you a little reminder of what's the leap we've made in architecture, why did we make that leap and get you into some of the actual data that we've been generating in our development program and again, give you that view for -- and then how does that intersect with our long-term road map. John will take us through the path to 20 amino acids. I think we frequently get asked, when are you going to achieve that? What's it take? Is it possible? We've had these questions over the last year or so. And I think John will do a really effective job taking you deep into how do we do this? Why do we think we've hit an inflection point and what's that mean in terms of our time frame to deliver?

And then Brian, on the PTM side, what are all the capabilities and all the data that sits inside of the sequencing technology and how do you apply that to get really broad PTM profiling. And then I'll round out on Proteus and address a couple of the questions we've heard. What did we learn from commercializing our first-generation technology? How does that factor into technology choices we made, specs, different things we're aiming for with Proteus. And then really how do we see ourselves going to market and give you a view of sort of both technical and commercial milestones you should expect from us over the course of now until the launch at the end of 2026. So with that, without further ado, we'll bring up Todd, who will take you into the Proteus program and the long-term road map.

Thank you, Jeff. It's really excited to have this presentation today. It's been a lot of work that the technical team has done over the last year. We've been executing on the vision of the Proteus program over the last year, and they made a ton of progress, and it's really a privilege to get to come here and share it all with you. Before we talk about the status of the program, I wanted to spend some time talking about what Proteus is and why we -- just remind everyone why we're going down this architecture change. The Platinum instrument and system is based around an integrated consumable device that has both a fluorescence lifetime imager and the wells that we mobilize the peptides into. There's about 2 million wells in that device.

And what we're doing with the proteus architecture is we're repartitioning the system. We're taking the complexity of the imaging system out of the consumable and putting it into the instrument. That makes the consumable much simpler and much more scalable. We wanted to get on that path of really scaling the technology much more than we could do with the integrated device. And then the instrument then contains that imaging system that supports that simple, scalable consumable. And at the same time, we're taking the opportunity to add some workflow automation to make it easier for users. That new consumable, we call the kinetic array, it's based around a low-cost fused silica die at its core. It's a passive device. There's no active components on it. There's 80 million wells per device in the first implementation, and that compares to the 2 million in platinum. So it's a big scale up in the number of wells that we can support.

The architecture, though, supports scaling to billions of wells, and that's one of the reasons why we made this change. That simple glass device then gets encapsulated in a plastic assembly that provides 4 flow cells. So each one of those flow cells contains 20 million wells that can be interrogated and there's features on it to support automation in the system. The instrument then contains this high-performance imaging system, and that's really what enables us to use this very simple passive consumable. And in addition, the instrument contains a liquid handling system that allows that workflow automation, and it provides the capability to do more advanced workflows that could provide deeper insight that we wouldn't want to burden the user with.

So where are we at? At this point, over the last year, we've really focused on retiring technical risk in the program and figuring out all the specifications for the product. And we've done that through a series of prototypes that we've used to mature all the critical system components and retire those risks. The integrated design is complete at this point based on all the learning from those prototypes, and we're building the first systems now. Through those prototypes, we've really been able to develop all of the new elements of the system and make sure they're working and get them working well.

So for the liquid handling system, for instance, we have a prototype liquid handling system. It's the exact same architecture as what's in the final product. And in fact, it shares a lot of the same components with the final design. And with that, we've automated our full sequencing workflow and demonstrated that working. We've implemented all the new elements that are required to make that work. And what I'm showing here is data from experiments that we run with the automated workflow that show that it's much more reproducible than the manual workflow, which is a lot of what we would expect from an automated system. We've been able to make things much more reproducible.

With that kinetic array, we've done a lot of development there. So we just had some simple prototypes last year at this time. Now we have a wafer fabrication process established. We've optimized the well structure and design for the best performance in our system. We've designed this whole thing from the ground up to be scalable and low cost. So those wafers have to go through some functionalization after they're built. All of that is done at the wafer scale and processes that can be done in bulk and scale to very high volumes for low cost.

The die size that we're using right now is the same size and geometry that's going to be in the final product. So we're already operating at the scale that we need in the final product. We've already proven all of that out. And then we have that packaging process with all the features we need for automation already developed and tested and working together. The imaging system was a big area for us. This is where we're taking all that responsibility of producing the data from the peptides and collecting it, and we're putting all that into the system. It's a big change to what we do architecturally, and it required a lot of development. We've built multiple versions of prototypes of the imaging system. They're all the same architecture as the final product design. They have all the same features. They do the detection the same way. The only difference is they just use commercial off-the-shelf components instead of some of the custom optics that we have in the final product that gives us the full field of view that we want.

And with that imaging system and with the dies that we've developed that work with it, we've been able to demonstrate, really validate the transition from lifetime detection that we do on the platinum product to detecting in color and Proteus. This was a big transition for us. It's completely proven out. What I show on the right-hand side are you really see 8 separable clusters in a 2-dimensional space of color and intensity. Those represent 8 different dies that we can have in the system at one time, and we can distinguish them from one another, and that means we can detect the molecules are bound to accurately. Just for reference, in the platinum system, our latest kit needs 6. And here, we're demonstrating 8, and there's actually plenty of room there for more.

So this is a very accurate and extensible space that supports pretty much whatever we want to do with our assay going forward. So we're very excited about that proof point. But not only have we used all of this work to develop these different components of the system individually, but we've brought it all together. So for the first time at the end of Q3, we brought all these elements together and performed our full dynamic sequencing assay. This is just an example trace right here. This is data very much like we would get from a platinum system, all with all the new elements.

So the new imaging system, the new consumable, the new dyes and the software that does the reconstruction, all working like it will in the final product. So a huge derisking of all the new elements. There's not really a lot of big technical questions out there about whether or not we can do this. It's really just a matter of execution from this point. And since we've been sequencing over the last couple of months, we haven't really had any time to do optimization yet of the system. We're really still using the same reagents and software for the most part that Platinum uses, but we have been able to measure the performance relative to platinum so that we have a baseline for where we're going to be from a -- not just from making it work, but a performance standpoint. And I'm very happy to say the performance is -- it's meeting our expectations of being significantly better than Platinum.

So for example, on the left, you'll see a plot about alignments per well. So that means if I take the same number of wells in Platinum as I do in Proteus and then see how many alignments I get out of the end from an equivalent amount of wells from those 2 systems, I'm getting about 1.8x as many alignments from Proteus as I do on Platinum. So the system is capable of producing more output from the same number of wells. And then on the right, those alignments are -- they're not just -- they're not equivalent. So the alignments from platinum tend to be longer and have more aligned positions, so they're more informative. So you kind of get to multiply all these things together, right? We're not only getting 40x more wells in Proteus, but those wells produce 1.8x the number of alignments and those alignments are more informative.

So it's a huge leap in the information content from the experiments that we run on the system. And again, I just remind everyone, this is without any optimization. We're just running things pretty much with the same conditions that we have on platinum. We have a lot of room to improve. Proteus consistently sequences deep into peptides. This is an important aspect of our system that is a unique capability for long-range structural information. So when we talk about PTMs and variants, it's important to have access to all the different positions, including deep into reads, and we don't see a significant limitation there that's fundamental to our system.

There's a lot of opportunity to improve this again, as we do more optimization of the system. Here, I'm showing reaching position 19 more than half the time. There's no reason we can't extend that with additional development. And very fundamentally and what's behind a lot of these improvements is just fundamentally better S&R for the Proteus system compared to platinum. We have a metric in our system, which is how easy it is to detect the binding events over the background noise that we have in the system, we call Pulse S&R. I'm showing on the top right, histograms of that Pulse S&R for both Proteus and Platinum. Proteus is in the dark blue. That Pulse S&R is about twofold higher than platinum. This is significantly more sensitive and accurate than the platinum detection system. This means, again, those wells produce more high-quality alignments, better accuracy, more sensitive for PTM variants.

But there's another like more obscure thing that may not be obvious, which is that the binding events that are hardest to detect are the short ones, the ones that are only there for a brief period of time. In Platinum, I'm just showing an example on the bottom right there where there's a tryptophan in the middle that we basically don't see it. And the reason we don't see it is because the binding is weak to that particular position. And we don't observe those events very easily on Platinum. We miss them most of the time. But the Proteus system without any optimization, and in fact, the software deliberately tries to ignore these short events because they're not very informative. But despite that, there's so much signal there that the software is finding that tryptophan position half the time. And there's a lot of room to improve the software to leverage the information content that's in the proteus data that's not present in the Platinum data.

So this is super important because getting to 20 amino acids, getting high coverage of all the different sequence motifs, we make the binders better so that we get more coverage, but Proteus is actually giving us a more sensitive detection system. So it's bringing the sensitivity up of the system so that we can get more on the low end as well, and we don't have to improve the binders as much as we would have to otherwise. So a big, big advancement to what we're capable of seeing. So where we are is that not only do we have all these elements working together, they're sequencing, and we've proven out our strategy and the new architecture, but the data is superior to platinum with very little optimization, and we expect a lot of additional improvements before launch.

We've used the data and learning from these prototype developments to develop specifications for the final product. So we are very confident in what the final product needs to be able to do to function and produce the full performance that we desire. So we're -- we've already designed an integrated system. The first integrated systems are expected to be completed in the first quarter of 2026. Those will then bring everything together. So the full workflow automation, integration of the imaging system into it, product like consumables, including for the reagents and that full field of view supporting the 20 million wells. So this will be -- we're very excited to get this, like I kind of can't wait. It's coming soon.

So in summary, compared to last year at this time when we were -- just had a couple of proof points, and we were pretty confident about the direction, now the transition to the new architecture is completely proven. The team is just executing right now towards a product launch at the end of next year. The architecture shows significant improvement in terms of not just the quantity, but the quality of sequencing output. You're not just getting the geometric scaling of the number of wells, we're getting additional improvements beyond that because the architecture has just fundamentally better performance. And we've aligned the launch of the product to coincide with improvements in biochemistry and library prep that will drive additional performance gains. So really like a huge leap in performance that we're going to get when this product comes out. So we're very excited about that.

So now I'm going to transition to the future technology road map. When we embarked on this new architecture, it wasn't just to make a Proteus instrument with 80 million wells, it was to put us on a new path that was more scalable. And so if you look at our long-term technology road map, the first Proteus instrument is really at the beginning of it. But it's really putting us on a path to a system that scales to billions of reads. As I mentioned before, that consumable architecture is designed to scale to billions of reads. In fact, we could probably make the chip for the Proteus to instrument now. There's other things we have to do to make that work.

There's about a tenfold scaling in the assay that's available just from assay improvements alone, and those are things we can do in the shorter term. And then there's some more advanced technology development we have to do to enable that scale up to 10 billion reads. And I'm going to talk about some of the different things that we are working on. Just like Proteus was an advanced technology development a couple of years ago, now we have some other things that will roll out in the future once we work them out. One of those things is super poisson loading.

The system today is dependent upon poisson loading. And what that really means is that we don't have a way today to prevent multiple peptides from loading into the wells on the chip. And because we don't have a way to do that, peptides load randomly, sometimes you get no peptide in a well, sometimes you get one and sometimes you get multiple. And it's really only the wells with one peptide that are useful. Those are the only ones that produce useful data. And it turns out that statistically, you can only get about 1/3 of the well, a little more than 1/3 of the wells populated with a single molecule in a system like this.

So we are working on a method right now to deliver peptide to the majority of wells. And this is about a threefold increase in the throughput of the system. This is something that could be a kit release for the first Proteus instrument. It doesn't really require an instrument change, but it is something that we're working on for the future. Another thing we can do to improve the throughput of the assay is to speed it up. Since we've launched the product, the duration of the sequencing reaction has been 10 hours.

Our focus has really been mostly about improving coverage and improving the information content that comes out. But as we make progress on that and we have coverage, we really want to get more throughput out of the assay. And one of the ways to do that is to speed it up. So instead of taking 10 hours to sequence one of those imaging spots, we can do it in 5 hours or 2.5 hours, and that enables us to sequence multiple devices in one after another and increase the throughput of the system. Without making the system a lot more complicated, it could be a drawer upgrade to the instrument. It would need a little bit more space for more consumables, but that's something we could roll in, in the future pretty easily.

And then finally, the next big leap because we do need another big leap to get to that 10 billion reads is a change to the sequencing chemistry itself. The current system is dependent on this random cutting process. It's a one-pot reaction. We put in the cutters and the binders at the same time, and they're both acting at the same time. And in that system, the cutting action is a random process. It happens whenever a cutter happens to diffuse in the well and cut one of the amino acids off. And I'm showing examples on the right, that's the same peptide detected in 3 different wells of experiment. And they all look different. But if you look close, the order of the colors is the same, right? They're all purple, orange, blue, green, yellow and so on.

Today, that's what we use, right? We use those events in order and the software detects the transitions between them and it figures out which amino acids are in the peptide. But not having control of that is limiting in terms of the scale of the system. It's a little more complicated for the software. The time on average tends to be slower because we don't want to go too fast and miss things. It also -- there's no way to look away from a region. So if you have a field of view that supports a certain number of wells, you can't look at one spot for a while and then go look at another spot for a while and then come back, you'll miss important information. You'll miss cutting events, you'll miss amino acid residues.

So in order to enable that scanning where we can take one field of view and multiply it over a much larger area, we need to gain control of this process. And so we have been developing a method that we call control cleavage. In this process, we gain control of the cutting and make it mediated by the system. So in this case, the imaging process is separate from the cutting process and is controlled by the reagents that are delivered to the consumable. And I'm showing an example of it here. In fact, this is data that we've collected with proof-of-principle experiments that we're doing. Again, this is like the stuff we're working on laying the groundwork for the future.

And you can see that same peptide and you can see we have these defined boundaries between the amino acids with specific cut locations. And this has all these benefits. They'll be able to speed things up. We'll be able to simplify the algorithms and make them more accurate because they'll know exactly where to expect the data for any given amino acid residue, and we can enable a scanning system because we can make those imaging periods, we know when they are, and we can scan during that imaging period without losing any information.

And so this enables something like a Proteus 2.0 instrument which would incorporate a high-speed scanning system and microfluidic delivery to cycle the reagents to the device. And this is what really lets us get to billions of reads because we can multiply that limited field of view across a large area. We also get to pack those imaging locations all together in one flow cell, which makes them much more efficient use of device area. And all of this is enabled by the controlled cleavage chemistry.

So something we're working on for the future, but it's really all in support of this vision of a long-term technology road map that gets us to billions of reads. So that's what I have. I'm going to turn it back over to Jeff now. Thanks for your time.

All right. Thanks, Todd. I think to maybe summarize, First off, we came about this time last year and talked about Proteus and this huge leap in architecture. And we said we would launch in 2 years. And I think during that presentation, I had made a comment about programs like this typically run 3, 4, 5 years. There was a lot of healthy skepticism, especially from our friends in the analyst community, which we appreciate that skepticism. But I think you see where that confidence came from. I think you see the methodical nature with which the team has tackled the problem.

I've talked before about the depth of talent we have across every function you need in R&D to pull this off. I think that shows up when you see the diversity of the things we've been working on. Similarly, I think we've talked about most of our investment is in product development, meaning things that will see the market be a product that customers can buy within the next year or 2. But we do have that small investment in the background of how we get to the end. And I think we showed that data today on controlled cleavage, not because we intend to launch that product tomorrow, but because whenever you're making progress, there's always folks who are going to say, well, this is going to be where they get tripped up. This is where they're going to get stuck.

And what we want to do is demonstrate we understand how it all comes together. We know how to get to that endpoint. And I think showing with very modest investment, we've made a huge leap on the chemistry side that gives us a very clear path. It's not just a vision of the technology road map, it's actionable. We can deliver on these things. Proteus is the big leap we needed, and then it becomes much more of a sort of an architecture of the consumable, how many spots do you put, how big, intersecting with the chemistry.

So maybe with that, the other part of the chemistry is not just cutting, it's how we detect the amino acids, and let's have John come up and give you a dive into this world, pretty fascinating world of data generation and how you do the development of these recognizers.

All right. Thank you. I'm John Vieceli. I'm the Chief Product Officer at Quantum-Si, and I'm going to give you an update on our progress towards detecting all 20 amino acids on our sequencing platform. So obviously, a long-standing goal and vision of ours is to enable the detection of all 20 amino acids and develop end-terminal amino acid recognizers, which are these protein binders with labeled dies to enable the detection of all 20. As Todd showed, what Proteus enables now or delivers is a detection system, coupled with these new dies and advances that we're making using AI for binder and protein design and protein structure prediction, we're in a position now to deliver on this vision, and I'll go through the details of how we're going to do that.

So let me lay out the road map for how we're going to get to 20. I'll give you where we are today and then how we're going to get to detecting all 20 amino acids on the platform. So if you're not terribly familiar, Todd gave a little bit of an overview on how the technology works, but I just wanted to just give an overview for anyone who maybe is less familiar. But essentially, we take proteins, we digest them into peptides. We immobilize those peptides on the surface of our kinetic array on the Proteus platform. We then introduce the N-terminal amino acid recognizers, which again are just die label proteins that bind to the end terminus of those peptides. We're measuring the fluorescent signal of those binding events, so they're coming on and off.

And there's also aminopeptidases, which are present in the solution. Those periodically cleave off the N-terminal amino acid exposing the next amino acid in the sequence for detection. So here's an example of [ RLIF ] being sequenced on the system. So you see the detection cleavage followed by detection of the next amino acid. That leads to the plot on the top right of the slide. So that gives us a trace of those pulsing events.

We're able to color those pulses by the intensity and color ratio. So that gives us the recognizer identity. Certain recognizers do detect more than one amino acid. So we then get the amino acid identity through the kinetics of those binding events. So we take those on-off events. And from those, we can determine what amino acid was actually present there. So that's how we go from the fluorescent signal to the actual amino acid sequence of the peptide that was on that surface.

So since the launch of Platinum in 2023, we've been iteratively making updates to the sequencing kit. With each one of those kits, we either bring out new recognition capability or we improve on existing recognizers. The most recent release was in Q3 of this year. We came out with sequencing kit V4 that added recognition for glycine onto the AS binder, bringing the total number of recognized amino acids on the platform to 14 using the 6 recognizers that I have shown on the slide.

So one other way that is a little bit tangential, but I wanted to highlight that we have at our disposal, and Todd kind of discussed it as well, is just in the software and the analysis and improvements that we can make that also enable detection of more amino acids. So we've been working on that, making signal processing improvements, and we've been able to show that we can extract methionine binding events from our NQ binder. So we've now added methionine to the NQ binder. I showed a couple of examples of peptides that we run internally regularly on proteins with those methionine binding events. That, of course, now brings us to 15. We have an update that's coming out very shortly. We're working on the final stages of a library prep kit, V3. And with that will be a software release, which will enable the detection of methionine and bring us to 15 on the system very shortly.

So how do we get to 20 though? We're now at 15. And this sort of lays out the road map for how we're going to do that. Things may vary slightly from what I've shown here, but this is our internal data as of today and how we think we're going to get to detecting 20 ultimately. So let me share sort of where we are and what we have internally and show you how we're going to get to 20 amino acids. That will be done most likely with 8 recognizers that I have shown with the groupings of the amino acids on the slide. We already have a version of the R binder that has histidine and lysine binding. So that's shown in the traces there on the left and the center of the slide. That binder is in development. We're currently working on that, and we have data internally with those binding events.

We have a new proline binder. So that's the one shown on the right. That's a new binder that we've been developing, and I'll talk about that a little bit later on in the presentation, but we have been using AI techniques for protein binder design and structure prediction and been able to develop this proline binder. That leaves 2 remaining amino acids that we have to get to, which are cysteine and threonine. We have campaigns underway internally for the development of those. Most likely, the cysteine from preliminary data we've seen internally will be on the NQ binder. And we will be working on the development of a new binder for the detection of threonine, which we think will also bring along serine on detection of that.

So this is our pathway to getting to 20. We're accelerating our recognizer development pipeline. I'll go through that acceleration. We're going to heavily leverage AI and protein structure prediction methodologies to accelerate that development. We're scaling everything up. The goal is at Proteus launch at the -- in 2026 to be detecting 18 amino acids on the platform and then bring the full 20 to the platform in 2027. So we're going to have internal demonstration of that 20 in next year and then bring that to the platform in 2027. So that's our road map for getting to 20 amino acids. As Todd showed -- sorry, -- the detection system on Proteus has already been derisked. We have the 8 dies. They've been demonstrated on the Proteus prototype systems internally.

We have additional space, if necessary, if we need to make any changes and go to additional recognizers for any reason, there's space within this 2-dimensional plot to add additional dies if necessary. But we have the detection system. We have the dies and we have everything to support that road map that I showed on the previous slide using 8 recognizers on the platform. So let me go through the pipeline and sort of how we do this development and how we are accelerating it and how we think we've scaled up and we're going to be able to achieve that vision of delivering all 20 amino acids on the platform.

So I wanted to show this is sort of the evolutionary tree of recognizers that we have on the system and sort of how do we get these? Where do they come from? How do we evolve them? So this shows the current set of 6 that we have in the sequencing kit V4. And there's a couple of different ways that this happens, right? If you look at the top 3, they sort of follow this linear trajectory. We're making improvements to each one of those. With each improvement, we get better coverage. We see more sequence context with that recognizer, and we are constantly delivering improvements on those. And we continue to do that, always looking to improve the coverage of existing recognizers as well.

The other family that's at the bottom is a different pathway where we had this NQ binder. And with that, we're able to evolve -- keeping the same backbone, evolve the binding pocket to get recognition of new amino acids using that same backbone. So in this case, we were able to get the GAS and the DE binder by evolving the NQ binder to do those additional recognition events. So this is all protected by 27 different granted patents and applications. We obviously have a lot of expertise and long history of doing this and capability that we've developed over time. And I also showed on here sort of how we've evolved these from the kit iterations. So we had the V2 kit, which brought derecognition at the bottom there. V3, we updated 4 of the binders, so that gave us better recognition capability on some of those as well as bringing DE binder. And then the V4 kit was finally bringing the GAS binder to the platform.

So tons of experience on developing these recognizers, and we have a lot of different ways that we can do that. As part of all that development, we've also amassed what we believe to be the largest amount of data, both sequence and structural that we can -- for N-terminal amino acid binders that we can correlate to the kinetic data to the binding affinity and to the kinetics of these recognizers. And so we have tens of millions of binding data often with different peptides with different sequence context. We have structural data that we've mined from publicly available sources like the protein data bank, which I'll show in the next slide. We also have X-ray crystallography capabilities. That gives us about 1,000 different structures of proteins with amino acids bound in the pockets of those.

And then as we go through the pipeline, we obviously generate kinetic data as well. So we have both bulk kinetic data that we've generated and single molecule kinetic data. What all of this data enables us to do is feed it into AI models that can be refined to lead to the better prediction of new binders and also improvements to our existing binders. So we've amassed a huge amount of data that we can use to further drive this process. So this is just a quick example I wanted to go through.

We have done things like taking the protein data bank, searched it for all evidence of end terminal amino acid binding. We've then refined that search, looking for things that have a full atomic representation. They're exposed on the surface. They're just a single binding event. These are high-quality structures that we can then use both as scaffolds for new parents like for threonine and proline, but also for model training to refine binders. So these are the kinds of approaches we're using to mine existing information and feed that into our pipeline to accelerate things.

And then, of course, there's just been a huge amount of work in protein structure prediction and protein folding that's been done by both academia and industry. So Nobel Prize in 2024 was awarded for protein structure prediction and protein folding. Those have led to models that we are directly using deep language or -- deep learning models that we're using for the development of our binders. Meta AI, which was originally the Facebook AI research team developed evolutionary scale model. This is a deep contextual language model that you can take data and refine the model to do prediction for internal amino acid binders. So that's how we're taking the volume of data that we have and feeding it into models to lead to better prediction for proteins.

And then, of course, this is all on using NVIDIA GPU hardware acceleration. It's commodity hardware. We can scale it either internally. We can deploy in AWS on the cloud, and we can execute all of this modeling using their hardware. So we have not only our own data or our own expertise, but we have just a wealth of information that's coming from academia and industry that we can utilize to accelerate our pipeline.

So this is where we are. This is our pipeline. We have these different sources of data. We have combinatorial approaches. We have AI design. We have rational design, x-ray crystallography. We feed that all into our pipeline. We are scaling up the pipeline by about 4x relative to our historical amount of candidates that are going through. So we've scaled up all the different methodologies we're using, utilize more AI techniques, and we are funneling that down as we go through this pipeline, we do screening, then we get bulk kinetic measurements, we get single molecule kinetic measurements, right? And that leads to binders that we then put into production as well as feeding back into new designs. And this scale up is what's going to enable us to deliver on the vision of 20 amino acids on the Proteus platform.

So I just wanted to end with sort of 2 examples of how we've utilized this information and how we've arrived at some of the binders and recognizers that we have on the system. This is one example where we use X-ray crystallography and then combine that with combinatorial screening and AI approaches to arrive at the GAS recognizer. So what's shown on the left is the actual NQ recognizer, which we were able to obtain a crystal structure with a G-terminating peptide, which obviously is not the natural binding, but under crystallography conditions, very high peptide concentrations, you can get the structure.

And what that structure does is gives us insights into how would we modify this NQ binder to be able to recognize a G-terminating peptide. And so we went through that, got some hits from combinatorial approaches, and we're able to come up with the structure on the right-hand side, which basically filled that pocket, retained the G-amino acid binding capability, but also excluded the NQ binding capability, right? So we can basically take this atomic representation. We have atomic level control over these recognizers and getting the recognition what we want while also getting the specificity and excluding the recognition that originally had of NQ and tailoring it exactly to GAS. So that's one methodology where we took an existing scaffold, modified the binding site and we're able to get new recognition capability from it.

The other example that I wanted to go through was the proline recognizer that we've been working on. This was, again, largely coming from AI techniques that we've been leveraging. So we took a parent protein, put it through AI structure prediction models. That led to a hit. And the interesting part of that hit is it has 18 different mutations, which had we not used AI would have taken us a very long time to arrive at using any other method rationally or combinatorially. So this sort of proves the power of AI and that we can get these hits very quickly, and they're very complex and things that would have taken us otherwise a very long time to achieve.

One aspect that we are paying close attention to when we're doing screening is specificity. So what these traces show is that while this was a good proline binder, we also got a little bit of isoleucine cross-binding from that. And of course, we want them to be very specific. So we took the strategy with those 18 mutations and reverted each one one by one to the original parent amino acid. And what the plot on the right shows is this is the binding ratio between the proline and the isoleucine. And one of those amino acids was largely responsible for the isoleucine binding, and we could knock that out by reverting that single position, still retaining the proline binding capability, but removing the cross binding to the isoleucine.

So again, we have all these techniques, we have AI, we have combinatorial approaches. We have this whole pipeline that's all set up to enable us to deliver. So let me just summarize the path to 20 amino acids, our current recognizer pipeline. We've got the 14 in the V4 kit. We're going to go to 15 very soon. At Proteus launch in 2026, we'll be at 18 amino acid detection. We've scaled up everything by about 4x, and that scale-up is what's going to enable us to demonstrate 20 internally in 2026 and then release that on the Proteus platform in 2027.

We're heavily leveraging AI tools as well as our own screening data to refine these models. We're using combinatorial and rational design approaches as well in concert with that. And that's all going to accelerate the pace of recognizer development and deliver on the vision of 20 amino acids on the Proteus platform. I think that's it, and thank you for your time.

Let's jus slide out of there. So maybe just a couple of comments. I think the first one is you can't just start tomorrow and say, I'm going to use off-the-shelf AI tools and recreate what we just did. This -- the ability to accelerate now has a lot to do with everything we've learned over the last few years. Had I gone to the team 2 years ago and just said, go scale up 4x or 8x or 10x, just try to make this some sort of linear investment model where I tell you just double the people and double the output, you would have doubled the work and you would have doubled the output, but the quality and the rate of improvement might not have been any better.

You could have created lots of bad candidates that really wouldn't have moved you forward. You would have spent more money, you would have felt like you were being more productive, but you weren't actually being more productive. By having all of this data now and all the knowledge that our team has, you're able to leverage that so that not only does the pace of the activity pick up, but you do that with still retaining a high quality of the candidate. And it's really that intersection you need to have to speed up.

And if you think about what John and team intend to accomplish, we've been working on protein sequencing for many years as a company to get to 14, and we're going to close the remaining gap in the course of the next year. That acceleration comes from that data from all those learnings and from the sort of the core competencies and workflows that we've built inside the company over the last few years. So very excited about that rate of improvement and that progress.

And as that coverage gets to complete coverage, that sets up nicely for what Brian is going to talk about, which is what are all the things we can detect using this core technology? What's all the underlying rich kinetic data that's there? And how do you apply that to look at something like a post-translational modification that has huge implications in terms of biology research, biomarker development and so on. So with that, we'll let Brian come up and talk to you about that topic.

Thank you, Jeff. So today, I want to walk you through our vision for delivering PTM applications on Proteus. I'll discuss some of the advantages of doing single molecule detection for PTMs, walk you through 3 approaches that we are developing to get very broad access to PTMs across the proteome and then walk you through examples of how we're doing this in practice on the road towards Proteus launch. So first of all, what are PTMs? PTMs are chemical modifications to the side chains of amino acids that can have a dramatic effect on protein function. And there are an enormous variety of PTMs. It's estimated there are around 400 different types of PTMs in the body.

In proteomics, though, there are really only a handful of PTMs that are of very high interest because they're either abundant or they're implicated in disease states. And these are things like phosphorylation, which is involved in cancer signaling pathways, glycosylation, which, for example, is involved in regulation of the immune system, and ubiquitination, which controls protein degradation and is important in neurological diseases. So proteins really are the -- sorry, PTMs are really the determinants of protein function.

And in proteomics, researchers have come to understand that it's really not enough to look at which proteins are present in a sample. Researchers really need to know for the next generation of proteomics, what PTMs are present in those proteins. Unfortunately, current methods in proteomics run into a lot of challenges when it comes to PTM detection. We can sort of categorize current approaches into 2 categories, mass spectrometry and affinity based. With mass spectrometry, quantitation of PTMs, so what fraction of a given protein or peptide is modified is a very difficult question to answer. There's also the challenge of ambiguity in detecting the actual site that is modified.

So you might have a signal that tells you that a PTM is present, but pinning down where it's actually located can be difficult in many situations. And related to that, when there are multiple PTMs within the same peptide, that can create a really difficult situation for mass spec to deliver an answer on where those PTMs are. On top of those challenges, you have this workflow and analytical complexity with mass spec data and that, for example, limits clinical adoption. Affinity-based platforms can have the ability, in some cases, to detect thousands of proteins, but they provide no PTM or proteoform information.

And other techniques in the affinity-based space require -- they can see PTMs, but they require site-specific and protein-specific affinity reagents for every single protein, as Jeff pointed to earlier, and that results in this enormous proliferation of reagents and expense to access PTMs more broadly across the proteome. So what -- in contrast to that, what are the advantages for PTM detection using single molecule sequencing. The first is the way that we're sequencing proteins on proteus, the nature of the assay is inherently quantitative. We're essentially counting single molecules. So you get a quantitative readout.

Another aspect of the sequencing approach is it's inherently specific where we get sequential information and we detect a PTM so we understand exactly where it is in the peptide. Related to that, that gives us access to more complex scenarios where there are combinations, which is quite common in the protium combination of PTMs and potentially variants in the same peptide that might be impossible to approach with other techniques. It's much more straightforward with the single molecule sequencing approach. Those advantages sort of sit on top of this platform that's really easy to use for customers. It doesn't have all this workflow complexity and the data analysis is straightforward.

Another really critical advantage is that it doesn't require site-specific and protein-specific reagents for every protein and PTM. As I'll walk you through, we have developed approaches that provide universal access to PTMs anywhere where they're located in the proteome. So what are those methods that we're developing? There are 3 main approaches that we're developing that can be used either independently or in combination to achieve very broad access to many different types of PTMs no matter where they're located in the proteome. And those approaches are first, using kinetics, so we -- and I'll walk you through examples in subsequent slides of each of these. Using the kinetics that result from the presence of a PTM to detect it.

The second is pre-recognition. And here, we use a universal PTM affinity reagent, which can be an antibody that detects PTMs anywhere where they're located in any peptide regardless of its length or sequence. And the third method is direct detection. So this is where we have a recognizer in the sequencing process itself, which could be one of our standard recognizers or one that we engineer specifically for a given PTM. And it recognizes a PTM when it's at the end terminus just like our recognizers do for any other binder or any other amino acid.

So to walk through each of these methods in a little bit more detail with kinetic detection of PTMs, the important thing to understand is that a kinetic response to a PTM is an inherent property of the recognizers that John discussed. They interact with the N-terminal amino acid. But when they do that, they also make contacts with downstream amino acids, and those contacts inevitably result in changes in the kinetics of that interaction. It's kind of a universal biophysical phenomenon that we see all the time in our assay. What that means is that many different types of PTMs result in these detectable kinetic changes. Examples of those would be things like phosphorylation, methylation, oxidation and many others.

And our customer are actually using kinetic detection now in some cases to look at peptides that have this complex combinations of PTMs and they can see which PTMs are located in these complex arrangements just based on kinetic data. With pre-recognition, the important thing here is that using a labeled affinity reagent, we can detect a PTM anywhere in a peptide. And this allows for a few kind of interesting benefits. The first is we can combine affinity reagents for different PTMs in the same mix and do a pre-recognition step where we can detect multiple different types of PTMs in the same peptides in parallel.

A great example of that is a method we're developing that we call the Pan-phospho detection, where we can recognize all 3 of the major types of phosphorylations in the proteome, phosphoserine, threonine and tyrosine in one assay. And what happens here is the proteins are loaded on the chip. And for a short period of time, the peptides are exposed to this affinity reagent that binds to the PTM. And then that reagent is washed out or that combination of reagents is washed out and then we sequence the peptides.

This method also has the benefit of being extremely sensitive to stoichiometry, which is something that other techniques really struggle with. And that results from the -- just the nature of the output of the assay, it's a very, very clear pulsing pattern when we see on and off binding of these affinity reagents to the PTM. And for end-terminal detection, the important thing here is that this doesn't involve any change to the workflow that doesn't even require a pre-recognition step. This is simply sequencing the peptides in the presence of a binder that binds to a PTM [indiscernible].

So like I said, those could be -- I'll actually show you an example. Those could be standard recognizers that are already in the kit that also bind to naturally unmodified amino acids or they can be engineered for specific types of PTMs. This has an advantage of being really useful for de novo sequencing applications because we're getting that direct and terminal detection.

So now I'd like to walk you through some examples of using these techniques in practice. So the first is kinetics. Here, we have 2 peptides. One has a tyrosine at position 3 and the other one has a phosphotyrosine. And what we see here is changes in the pulse duration, which is one of the key kinetic parameters of the recognition segments leading up to the position of the PTM, right? So the presence of the PTM is changing the way that the binders bind on and off to the peptide on the way of the reaction getting to the location of the PTM.

For example, here, you can see the pulse duration of the arginine decreases from 1.3 to 0.5 seconds. We see other kinetic changes. We actually, in collaboration with a lab at UVA published a paper where we use this technique to detect triple myosin proteoforms. To give you an example of just how broad this approaches to different types of PTMs, here's an example where we use the same technique for detecting citrulline. Citrulline is a PTM of arginine, and it's very difficult to detect by mass spec because there's a very small mass difference between the modified and unmodified forms. But here, where we have an arginine at position for in the peptide or citrulline at position 4, we get these sort of dramatic changes in pulse durations at multiple upstream positions that tell us where that PTM is located.

But actually, the information is much richer than that. It goes beyond pulse duration. So just to give you an example of one position in this particular peptide, the leucine before the citrulline shows changes not just in pulse duration, but also intra-pulse duration, which is the time between the binding events of the leucine recognizer to the peptide. And it also shows changes in the RS duration, the recognition segment duration that is -- that essentially measures the rate of cleavage of the amino acid. So these multiple kinetic parameters are changing at multiple upstream positions in a very straightforward and predictable way, and our software can really leverage that rich source of information for accurate and sensitive and very broad PTM coverage.

To switch to pre-recognition, Here's an example of using pre-recognition that demonstrates how this technique can be applied to PTMs that are located anywhere in a peptide and in any sequence. So we've taken here multiple synthetic peptides that have phosphotyrosine at known positions, either at the end terminus at internal locations within the peptide or just adjacent to the C-terminus, which is where we link the peptide to the chip. And we have -- in this case, it's an antibody that recognizes universally phosphotyrosine, and we do this pre-recognition step for these peptides simultaneously on the same chip. And we're able to detect phosphotyrosine with this very high sensitivity no matter where the PTM is located.

We took that technique and recently applied it in a collaboration with a company called Carna Biosciences, where we're probing a panel of important kinases. And with kinases, phosphorylation -- tyrosine phosphorylation status is a really important indicator of protein activity, and these proteins are used in drug development assays. So that's quite important. So here, what we've done is -- I'm just showing one example, protein tyrosine kinase 2b. You take this kinase, digest it as we normally do for our proteins, load the peptides on the chip and expose them to the PY antibody, in this case for 30 minutes.

This allows us not just to detect tyrosine phosphorylation at multiple peptide positions, but also to sort of pinpoint the location and determine quantitatively what fraction of those sites are actually modified. And again, that's really difficult information to get with other techniques. And then we can take that sort of mapping and frequency and map it onto the full length structure of the protein.

And finally, to give you an example of direct and terminal PTM detection, what we found with -- actually with the NQ recognizer that John was talking about that now with software improvements and things like that, is recognizing methionine. We found that it also directly recognizes oxidized methionine, which is also called methionine sulfoxide. And that's an important PTM in multiple diseases. So what you can see here is we have a protein called IkBa that we've digested, loaded on the chip. And in one of the peptides, there's a methionine at position 4.

And what we see are 2 sort of different phenotypes of kinetic signatures for this peptide. One has really short pulse duration but still detectable for the methionine at position 4 coming from the NQM recognizer. And the other one has this dramatic shift, the increase in pulse duration. And that is due to the impact of that chemical modification to the methionine when it's oxidized. So we have very clear direct N-terminal recognition of a PTM with a recognizer that we already have. And of course, like I said, this could be applied with other types of recognizers that we can use our pipeline to develop.

So to summarize, our path to broad PTM coverage on proteome really involves 4 key areas of development. The first is recognizer development, which John went over quite thoroughly. It's very important for PTM applications because ensuring that we can see all 20 amino acids at every position, that is what gives us the information to detect the PTMs using these approaches that I outlined. The second is higher output on Proteus and also combined with longer read length. That's going to enable deeper proteome coverage and more sensitive PTM detection because we're getting more reads, and we're going to be able to look at more proteins than we currently can on.

Another development area is on the software side. So as I've indicated, we're really getting a super rich source of information from the kinetics when PTMs are present. And it's really ideal to take that data and train AI models that will allow us to create software that can pinpoint and automate the detection of these post-translational modifications. And finally, of course, we're continuing development on these 3 methods: kinetics, pre-recognition, direct detection to achieve the broadest PTM coverage across the proteome.

Thank you, Brian. As we move into my presentation, I think one maybe point to make there is that competency we built internally, how do you take massive amounts of data, use AI to train and improve our recognizer pipeline. You can sort of see the thought process that Brian is bringing to the table with now how do we do the same thing in mine, the richness of the sequencing data we generate to uncover more and more things to detect these PTMs. So some of these core competencies that get built for internal purposes can translate over time into applying those to our product to improve its capabilities.

So I want to talk a little bit about what have we learned in the commercialization of our first-generation Platinum and Platinum Pro. How are we taking those learnings and thinking about and applying it to the requirements for Proteus and I think tie it to what you're hearing today around where our focus is with the chemistry and with PTMs. So the first thing is by having this technology in the market, we have been making improvements. And every time we make improvements to the technology, we learn about a new application, we learn about a new thing a customer wants to do. And those improvements in amino acid coverage and lowering the sample input as we expect to do with the new library prep kit, all of those things port over directly into Proteus.

So none of that work is lost. It's all directly portable. You then intersect it with that higher sequencing output with the ability to read deeper into the peptide and with a consumable that has just a significantly more favorable cost of goods and you really get to that sort of inflection point in terms of the total technology picture. But it's also commercially, how do we think about going to market. With Platinum, we went to market as sort of a general technology. We said we've got this protein sequencing technology. It can do the following things. How would you like to apply it with customers.

Now over time, you've seen us do some application-specific work. Barcoding is a good example. We were in biopharma. They started to work on this peptide barcoding application, and we applied that and created a kit to sort of make that more efficient. We were really sample prep agnostic. There are -- it's thousands and thousands of different reagents people use to prep samples in proteomics. I think if you've come from the DNA world, you underestimate how complex the sample prep is in proteomics.

In DNA, you can pull down your DNA, your RNA or all of the nucleic acid and then the magic of PCR to sort of level out the playing field, bring up the low abundant things and see them. That doesn't exist here in the proteomics world. And we tried to put that aside. We tried to let that be more of a thing the customer defined and then would flow into our platform. And while that can work, that's -- it takes a lot more work to onboard a customer. It takes longer to scale that up. And if you want to go after really difficult, valuable things like super low abundant biomarkers, integrating those things is a far better approach to bring products to market.

I mean we market it sort of to all comers. That's pretty common. Go out there, talk to researchers, see who's sort of interacting with you, who has an interest in the technology. That works in the early stages, that works with those early adopters. But I think we've learned a lot about really what segments to target, how to focus to get a depth of application to really drive the platform purchase and then the eventual pull-through of reagents. So the other advantage of being in the market is when you're not in the market, you sort of rely upon classic tools where you do various forms of market research, voice of customer. These are sort of the phrases we like to use as marketers.

But when you're in the market with a commercial product, like we are -- we have a scientific affairs team, lean and mean group, but they did something recently called the Platinum Pioneer grant. So this is us actually just working with customers to understand what are you trying to accomplish? What capabilities does it require? And this is really meant for us with our current platform to identify people who would get a certain amount of reagents to do some work with and publish their results. So this is part of the market development activity we do with the Platinum Pro.

But you can mine this and see what I talked about at the beginning is what's happening. The complexity of the types of analysis tools customers need shows up in this data. So more than 50 researchers submitted detailed proposals. And when I say detailed, I mean, they told us we wanted -- I'm trying to study the following thing. I need to detect the following types of things in the sample in these proteins or these PTMs. And when you mine those, you see 2 things that tie back to where we started. One is more than 50% of the applications need 3 or more types of protein analysis, meaning they can't complete their work by just doing protein ID or just looking at a PTM or just looking at a pull-down protein versus maybe a mixture. They need multiple sets of capabilities.

And when you get into PTMs, so if you look at the proposals that wanted to work on PTMs, which is a very large number of that 50, 65% more need 2 or more. That means very few applications to solve difficult biological questions are as simple as just detect phosphorylation or just detect methylation. They need to sort of tackle these problems that are very complex and be able to do it. And again, absent a platform that can do all of this, it leads us to where we started, which is people try to then own multiple different platforms. And that means a lot of the work just stays in the core lab.

So we know this data from our customers. We also know the word academic medical center. We use these phrases a lot as we all interact. We're selling to academic centers. We're selling to biopharma, we're selling to industrial. I could do this type of a map for every single one of those segments. And this is something, again, very difficult to tease out when you're doing market research, very very easy to tease out when you have people going in and calling on these institutes every single day. So I'm just taking one example, again, I could do this across other segments, but let's take an academic medical center. So they've got research labs doing very basic biology research. This could be very fundamental work. It could be even single molecule, just biophysical type of work.

So they have a huge range of application interest. They're typically very low infrastructure. Most of these folks send to the core lab. And they tend to be lower utilizers. The labs are smaller, less staff. So their work sort of ebbs and flows. That core lab, that's exactly where we started today talking about those are the folks who have the luxury of having the infrastructure and the dollars to own lots of different pieces of equipment. The publication that Brian talked about some of the other ones that have entered the market from people using our tech is often them using our Platinum Pro as a complement in the core lab to other technologies.

Translational labs, as we get more -- why are we pushing towards PTMs, why are we pushing in that direction? Well, as Brian described, that's where the functional part of biology is happening. That's where the disease biomarkers, the therapeutic responses, the risk of recurrence, these types of analysis or studies people want to run. That's really in that translational lab. And what do we mean by that? That's somebody who's got a foot in research and a foot in clinical practice.

And then you have clinical labs. These are folks who are just doing routine testing. And I think when people think proteomics, they often think, oh, immunoassays or that tau biomarker, they're going to run. There's also a long list of esoteric -- what get called esoteric test. I showed you sickle cell disease. Well, there's a list of more than 25 different hemoglobinopathies that today get done clinically to treat people, and they're cobbling this together using technologies like capillary electrophoresis or HPLC.

So overlay that with platinum based on the capabilities of that platform. And when I say capabilities, I mean what's the amino acid coverage, what's the level of automation, what's the throughput, what's the sequencing output? All these things we've been talking about with Proteus. What do you sort of see, right? Well, a very low-cost platform, pretty simple workflow, automated data analysis. It had a draw into basic research and what were the reasons, right? It could solve their technology problem. They had a low capital cost, so they could take control over their research. They didn't have to send to a core lab. They were able to afford to do this on their own, implement the work.

That's great in terms of a proof point of if people could access the technology and we think about Proteus, we don't want to be a $1 million piece of equipment because there are all these other labs who would want to in-source. But these folks were a good beachhead for us, but they are lower utilizers, right? They buy, they run the kits, they publish and then not until they start their next study. Core Labs, we've been largely a reflex testing technology, right? Someone's -- one of the papers from Northwestern, they were doing work on phosphorylation. They used our tech to resolve ambiguous cases to try to reduce the false positive, false negative rate.

So an important tool, but we were sort of relegated into more of a reflex environment. And similarly, on the translational side, Brian mentioned the study in osteoporosis with University of Virginia, again, getting used where we had the capability, we found access into the translational labs. And then the clinical lab really not accessible with the current platform, both from -- mainly from the standpoint of sort of automation and just total sort of end-to-end workflows. People don't do the heavy lift. I spent a long time in clinical before coming here. You have to provide a very buttoned-up product from sample all the way to report to really go into those environments. They don't have the sort of the developmental capabilities that some of these other labs have.

So now take those learnings that we've been getting in the field and overlay it on what you heard today. Why move to a nano well array? Why scale up the sequencing output? Why have more samples per run? Why have this time frame? How do we get more chips run through the machine in a period of time? Well, it comes down to these points, right? More samples per run with more output. We know that in those translational labs in some of those core labs, we're going to have to scale those attributes of our technology to move from sort of a reflexive position to a primary position.

Building upon what Brian talked about, some people might want to run a lot of samples with a little bit of information, but others might want to do very deep analysis, a complex mixture, look for a very rare event like a variant or a PTM. Well, having a lot more sequencing output enables that. That's something you are limited by in our current platform with only 2 million wells on the chip. And then multiplexing as we think about maybe lower cost applications, basic protein identification, the ability to take advantage of all this real estate, combine it with multiplexing technologies to really lower the cost per sample in those more cost-sensitive applications, something feasible to do with both the output and the cost structure of the Proteus chip, something we can't really do effectively based on the output and COGS of our current chip.

So it opens up some sort of commercial opportunities or pricing opportunities to access certain markets that might be complementary to sort of the core desire to be focused more on PTMs and variants. Again, tie out to what we heard, why get to 20 amino acids as fast as possible and focus on PTMs. Well, if you dive into that data, dive into those pioneer grants, that's -- this is what people want to do, right? They want to look at PTM profiling. They want to look at multi-PTM profiling, especially in those core labs and the translational labs. Single amino acid variants, interesting opportunity, both in translational, but also potentially into the clinical space.

Sequencing of variable regions of antibodies, you look at some of our biopharma customers, some of our industrial customers, they'd love to be able to do that, but that requires that expanded coverage. That requires that depth of sequencing to really look at those variable regions, something not accessible today with Platinum and Platinum Pro, but will be feasible as we move into Proteus. And then biothreat detection and surveillance, we talked about on our last earnings call that our instruments are deployed in the Department of Defense today.

We think that work that's going on there, we have visibility to it. We know that they're going to publish some data. I assume they won't publish everything. But there's an opportunity there to continue to scale up the capabilities that, that market needs to really think about how -- what's the future of biothreat detection look like. And we think the sequencing coverage, the output, the automation, all these things play well into where we believe they might be going. You never get told the full picture, but we believe those attributes will sort of dovetail nicely.

Automation matters. So I like to put things in sort of numbers. So if I wanted to take a Platinum Pro today as a customer and I wanted to run 4 samples, I get the kits, I unbox them, get down to the nitty-gritty of this, right? Someone would have to handle about 30 different reagent tubes to process those 4 samples. If you go into a lab doing mass spec, doing other things, they wouldn't sort of flinch at this. They're used to handling lots of reagents. They're used to doing a lot of pipetting. It's for our product, we're acknowledging here. It's over 100 individual steps to process a sample.

Again, in those basic biology labs, there are people doing gels. There are people running HPLC. They're taking samples over to a mass spec core lab. They're cobbling together lots of different things to do their research. But as we were thinking about the scale up in the output as we were thinking about the coverage in PTMs and the markets it might unlock, we wanted to automate, and this is really the reason why flash forward to Proteus, those same 4 samples, now you just take this reagent tray, and you load your 4 samples and you stick it in the machine, you add the chip, you add a tip box, you hit a button, it's over. There's no more pipetting. There's no reagent formulating. There's no mixing. All of that's happening in the machine. So the level of automation of the lab workflow is significant with the Proteus platform.

And then the other thing I mentioned in the beginning, that ties through is really applications, the sample prep and enrichment and also the application of AI, not just to our internal recognizer development program, but also to the analysis of our data. For any people who follow genomics in the early years of the revolution of NGS, it was largely software provided by the company. Over time, that opened up, and there were lots of companies who built analytic tools on top of that sequencing data.

I suspect the same type of thing could happen here. But we also are thinking about it in terms of what are some of those clinical applications? Could we marry up with someone who's doing the enrichment that we could marry with the capability of our sequencing and deliver a validated workflow and go tackle some of those challenges. So we've been building up over the last few months sort of a pipeline of potential partnerships across all 3 of these areas and wanted to today sort of provide insight into a couple of those. We expect to provide more information coming forward here on the other ones that are in the pipeline.

But here's a couple of examples. And Brian mentioned the first one, Carna Biosciences. This is an interesting application of our technology into much more of an industrial setting. So these folks are a leading provider of assay-grade kinase proteins into biopharma drug discovery. They're looking at our technology as a way to evaluate and sort of validate the phosphorylation profile of these proteins. This could potentially be useful for their customers to have this information and have it in a quantitative way when they're buying products.

So this is an opportunity for us to -- this isn't necessarily we're not selling Carna products, but can they leverage our technology? Can they improve or in any way, enhance the offering to their customers? And depending on how the data shapes up in the collaboration, could we work together with sort of complementary reach to bring sort of these types of solutions into the market. And then flipping to the right-hand side with [indiscernible] people who follow mass spec probably recognize the name SISCAPA. That is a company that has made enrichment for mass spec for many, many years. It's widely used as an enrichment technology in mass spec. They have created another entity within that broader holding company focused very exclusively on ultra-low abundance biomarkers.

Think your cytokines, think your interleukins, things that are historically very, very difficult to detect and very unreliable to measure quantitatively. They're at such a low abundance. Well, they've been developing some interesting technology to enrich for those that we're now working with them to combine, do their enrichment folded into our library prep and ultimately into sequencing. And now you can start thinking about, is this a way to create a very accurate low abundant biomarker panel. There's a lot of clinically relevant biomarkers that are at these levels.

This could be a very interesting way for us to couple a technology, validate that whole workflow and bring it to the market rather than going and saying, "Hey, sequence these things and you need to figure out Mr. or Mrs. customer, what to do on the upfront," this brings it all together and brings that buttoned-up package as we think about, again, moving beyond basic research and core and into translational and clinical. We think these types of partnerships can enable very interesting analysis in terms of what the data will likely prove, but also creates a way to actually reasonably implement it. It eases that sort of onboarding process.

So again, sticking with academic, again, we could do this for other segments of the market, but let's focus here for a minute on academic. How do we see everything you've heard about today with Proteus play out compared to what you saw a few minutes ago in terms of Platinum and Platinum Pro. So we think the basic research lab will still want to access this technology. Now we don't intend to price this instrument at the $100,000 sort of price point that Platinum is at. So some of these folks might not be able to in-source, but they might want to send to the core lab who has that.

So the opportunity to continue to cultivate that volume and ensure it ends up on our technology within a given institute is something we'll keep a focus on. Some of the larger basic research labs will certainly have the capacity to purchase, but some smaller ones might not. The Core lab really stepping out of that reflex tech or that I'm solving for the edge case problem you can't do and moving into more of the high-value applications. The ability to do broad PTM profiling is a clear opportunity in these laboratories, being able to do increased throughput is important. One thing about a core lab is they tend to have batches of samples.

So being able to do higher throughput, larger quantity helps fit. And we can really move more towards a frontline platform instead of being that secondary or reflexive platform. And then you put all this together and some of these ideas around and partnerships with workflow validation and sort of end-to-end sample to report, and we can make very meaningful progress into translational labs and we believe even into clinical labs. I think this time last year, we thought clinical could be 5 years or more out. I think with the right partnerships and the right validated workflows, this is something that can pull forward in terms of our time to access these markets with Proteus. I don't think it's a 5-year thing. I think this can be pulled back in time.

Again, are we going to take on the single protein biomarkers? That's not where we'll focus. We'll focus more on those complex esoteric tests that have high value but are difficult to do today and are underserved. But again, an opportunity to be in another type of lab who's a consistent utilizer, consistent run rate so that in total, you get sort of the level of depth you need to really drive the adoption of a higher-priced platform into this market segment.

And again, we've done these types of maps over every segment that we're in today with the Platinum and Platinum Pro system and really understand how many call points do we have and what do each of those call points need in terms of capabilities. So again, playing off of that. So we're in academic research today. We're in some pharma biotech defense, very recently into agricultural. I think the commercial or industrial sort of fits with sort of where the Carna Biosciences side of the world is.

So we really see this opportunity to take that approach, that deeper profile of each account and apply it over top of each of these segments. And the one thing that we've learned in each of these segments is the ability to see PTMs to sequence deeply. These are the capabilities that unify all of these. People are looking for -- in the translational space, the presence of a PTM may be indicative of a disease or not or treatment response or not. Well, in the same way in an industrial setting, that can also show a process that's out of control.

So someone's endpoint is different, but the capability they need is very similar. So we think we've brought that together and have the right requirements in there that we can take that approach we just walked through with academic centers and translate that out into other segments of the market. So what's that mean? How do we get from here to the end of 2026? So obviously, a huge milestone to have announced that we sequenced on Proteus on that prototype, and Todd took you through that data. We feel very good about that top line you see running across and getting us to that launch. So those fully integrated systems delivered and operational.

So that's that fleet of machines we'll use that will really allow Todd to take that data that you saw and the teams to take that data and now optimize -- the sequencing chemistries optimize the workflows and performance to get even better performance than you saw today. Again, we're already exceeding the current platform, but we expect to continue to improve upon that. Get out into Q2, we should be doing end-to-end sequencing. So those fully integrated machines should be seeing samples coming in and us getting sequencing results coming out of those machines.

So that sets us up then to work with some external customer collaborators. We're calling it customer collaborators because the point of this is not necessarily to sell these people an instrument. The point of this is put an instrument in a select number of very sophisticated places who have the other methods available and do some comparison, really put some mileage on this technology, make sure the results we demonstrate internally get demonstrated in somebody else's hands. And we want to run that a little earlier than you might run sort of a classic early access program because in the event we learn something, we want to be able to fold that into this program and make sure we accommodate for anything we learn before we get out into Q4 and execute on the internal validation studies and the launch.

Before hitting commercial ones, I'll bring your attention right below the launch one out there in the fourth quarter of next year, building off of what John said, we expect that we will demonstrate that we're capable of detecting all 20 amino acids by the end of next year. That we -- again, we expect 18 of those will be in the launch kit. And with this demonstration in hand by the end of next year, we'll be able to roll through one upgrade to the chemistry to get to all 20, and we'll be able to do that in 2027. So a pretty significant leap from 14 today to that point, all either by launch or within that first year of launch.

Commercially, I put up the milestones. I'll tell you that we may move these around, meaning we may pull some of these back over what's here, but this is our thinking right now. And the reason we might pull some of these back is as we're in the market and customers are starting to hear more, we're already getting questions about what's the list price going to be because I'd like to think about how I budget for it. So right now, we've pegged to release that list price in the second quarter. We may decide to pull that forward a little bit to -- for those customers who are trying to do budgetary quotes.

But we think that's an important thing to release both to set sort of the expectation in the market, but also to give people sufficient time to work through budgets, work through if they need to file for a grant or anything like that. When we get out into the third quarter and we've done some of the work with those external customer collaborators, we expect to share a more detailed update on what capabilities are going to be there at launch. So which of the PTMs will we be capable of? What's the sort of the coverage looking like, the depth, these items that Todd was talking about.

We'll start to provide some insights into what do we think that's going to look like at launch, again, helping build for the customer into that launch. We have an installed base of users. We have people using our system now under the placement program. Those folks are going to want to see an upgrade program. We hope that we can upgrade many of those people. So we'd expect to release that upgrade program in the third quarter. Again, might pull that forward depending on what we hear from customers as we continue to move throughout the year. I'm sure this event will spur some interest and might spur some of these conversations.

But again, I see that as a positive if we need to pull some of those events forward and give that to customers. If they're thinking about how they move to Proteus, we think that's a net positive in terms of our long-term success. So we wouldn't be disappointed by having to do that, and we'll just sort of listen to the market and make those sort of moves as we need to. So really just to tie out, I think it's -- what we really wanted to demonstrate today is Proteus, not only did we make a leap and that technology works, but we made that leap and have that vision and that road map that's very actionable to deliver on the long-term game here, which is eventually people are going to want that billions of reads and de novo sequence samples. This isn't just a vision.

This is something we've actioned, something we've been executing on, and we believe the Proteus architecture is the starting point of that, but intersects with these other items. We're going to continue to use Platinum Pro as a market development tool. Again, that doesn't make the revenue line today jump. But as we talked about on our last call, right, we were able to put 12 placements into the market in just a couple of months and over half of those in academia. These are the folks who get engaged, get using the tech that then are the ones who are going to want to know about the list price and the upgrade program and these types of things.

So we think that's a tool not only to get data into the market, but very useful as we think about building the early sort of set of customers who would want to buy a Proteus machine in that first year of launch. We got to execute. There is a lot of work to do. We think that optimization work is going to only improve performance, but we have to go do it, and we have to finish that work. I think the plan is there. The team, you can be the judge of that for yourself. This is the 3 key leaders in the group. I can tell you that the depth of talent below these folks across all the disciplines would sort of surprise you to the upside of how deep we are and how talented we are across the board.

So I have high confidence that they'll do that, but we'd be remiss if we didn't focus on that execution. That partner ecosystem we talked just about a couple today, we've got things in flight with multiple other groups. Again, really anything to do to accelerate application development, deliver sample-to-report workflows that may allow us to access some of those translational or clinical opportunities. And then we'll keep that modest but targeted investment going on the technology sort of development pipeline, right? We want to bring Proteus to market.

We want to build upon its capabilities that Todd talked about with faster sequencing and with getting more throughput from that device, but we also don't want to lose sight of having the next intersection point, that next leap. We want to be the ones always making the big leap on technology ourselves, not waiting for a competitor or somebody else to make a move. We'll continue to keep that lead. We'll stay focused primarily on development programs, but keep that sort of targeted investment in the background on the road map.

So with that, we'll stop there, and we're glad to take questions. I think we -- I forgot to bring the mics, I apologize. Just for the webcast, if you can ask a question into the microphone, that will help us.

Kyle Mikson from Canaccord Genuity. So thanks for the good presentation. So on the pricing of the box, you announced that like kind of early next year, you were saying, I mean, I guess it's going to be more than final. But either way, the consumables are important as well. So when you think about like price for amino acid, price for peptide, how are you -- like how do you sort of think about that? What do customers -- how do customers think about that and what do they want? And then also kind of on that note, the super poisson unloading relative to the 30% to 40% single molecules in each filled into a well, basically mobilized into a well, how much further can you take that? Can it be 60%, 70%? Or could it be closer to 100%?

Okay. I'll take the first one, and I'm going to let Todd start walking up here, so you can help on super poisson. I don't want to mess up your math. So first of all, on the list price front and the consumables. So yes, we're obviously not going to be at $100,000. We think $1 million for a piece of equipment like this is just sort of way too high. It would sort of limit the number of people we can sell to. So if I had to give you sort of a general range finder, we think it's probably in that $300,000 to $500,000 is where the machine is likely to fall. We're going to refine that as we're working with customers, and we'll have a more definitive position on that. But we think it's going to fall more in that range.

In terms of consumables, so let's start with what we've seen and then how that informs what we think about. So when we are tackling -- when we're trying to do an analysis that people have other ways to do, we see more pressure on pricing today. So pricing today is about $500 a sample. If we're trying to do something that they have other technologies that can do, we see more pricing. But then when we're solving a problem like the publication Brian talked about where we're looking at an isoform they can't do with mass spec or we're resolving the ambiguous PTM results from a mass spec run, we don't see really any pressure on that pricing.

So I think as we're thinking about consumable pricing, we're thinking a lot about might we have application-specific pricing or do other things to sort of just try to mirror the customer in terms of when are we offering that value and the customer is comfortable paying for it versus when we might have to be more price sensitive and compete with other tech. So we haven't really decided the model exactly yet, but that's what we see in the market today. The more we skew towards PTMs, high-value biomarker panels, the more I would expect that our ASPs will be able to be retained.

Either way, the other component not to lose sight of in the gross margin calculation is the cost of making this consumable is going to be significantly lower than the cost of making our current one. So we can have quite a bit of price sort of range finding by application and have stronger margins than we can achieve today with our current tech. Maybe on super poisson, so where can you sort of get to with that, Todd? We're about 33% single molecule loaded. What would it look like in a sort of an optimized world?

I don't really have a definitive answer today. It is still an active advanced technology development. I don't really have data to share today. I know from past experience and other systems, we were able to push that pretty high. We were able to push it above 90%. This is a single molecule world. Things tend to be a little bit more challenging. Proteins are chemically diverse that might introduce additional challenges. My expectation would be that when we initially come out with it, it could be getting to that 60% range. And then over time, we continue to improve with additional kit releases and improvements to the workflow. I expect that over time, we'll be able to get into that 90% range, but it may not come out all at once like that. It may take a few iterations to get there.

Yes. I think while we hand the mic for the next question, I see a hand up. You have a follow-up there, Kyle, go ahead.

So on the PTM for either of you guys, I think like 400 is what you mentioned in the body that are -- there's a few that are relevant though. So how many will you kind of launch, I guess, launch with those capabilities? And what's the timing? I don't think it was on that slide with the time line of stuff.

Yes. So we haven't decided exactly what we'll launch with. What we did talk about on the slide, I'll see if I can reverse it here. So the launch capabilities we will have in Q3, so we'll lay out sort of like what will the device be capable of. This is going to cover not only the types of PTMs, but it also will give more insight into will there be library prep improvements and other things that get married in. So we'll sort of share a comprehensive sort of launch capabilities update in that Q3 time frame.

You are correct, there's a long, deep list of PTMs. That list probably shortens down to 20 or less when you get into the sort of the really biologically important ones. We're out right now doing work with our existing customers and some prospects of Proteus to really understand how to prioritize those. Obviously, phosphorylation, we showed a lot of data here. That's high on our list and something we would expect to have. But which of the other ones we tackle is really subject to some of this work we're doing, trying to, again, find the ones that are important, actionable in terms of their biological question and ideally are very difficult to sort of access or do with other tech, right? That's the best place to intersect.

So that might cause our list to look a little different than the prevalent list if you just did the literature prevalence from 1 to 20, but it will be targeted to what those customers are saying. So I think more to come on that as we progress next year and roll out sort of launch capabilities. Okay.

This is RK from H.C. Wainwright. So I have 3 questions, so maybe I can go one at a time. So we just talked about pricing and where it could fall. I'm thinking about the market. With the Platinum and Platinum Pro over the last 2 to 3 years, you have generated a market for this sort of product. How much of an overlap is there from the platinum to Proteus in terms of the market itself? And what additional market could you start tapping into with Proteus? So that's my first question.

Okay. So I'd answer it in a couple of ways. I think if you look at those basic biology labs that have a Platinum or Platinum Pro, I think there'll be some of those that will be of a scale to acquire an instrument in that price point, but some of those will obviously fall out. They're too small. They don't have that level of funding. So I think some overlap there, but I think it's more modest. I think as we look at core labs, translational biopharma customers, defense customers, I think when we look into those other segments, early sort of intel would suggest many of those folks probably based more on the capabilities of Proteus than anything else are likely to want to move to a Proteus platform.

So I think we'll -- we're going to continue to have these discussions. That's why we want to release certain information at certain times. But I think the capabilities of Proteus is bound to be the main decision-maker more than it is necessarily the segment or the type of work they do. But if we just look at those pioneer grants, if we look at the types of things people are publishing on, it would suggest that there could be pretty significant overlap between -- outside of the basic biology lab between that Proteus, that platinum base and the future Proteus base.

So the next question is for Todd, he was talking about signal-to-noise ratio. If I go back and think about my days and Lab, sample preparation is a huge part of that, I would think. So how do you overcome that so that you can maintain a uniform SNR?

Let me start, and then I'll give it to Todd. So the first thing I'll say is on the highest value applications, I think our tilt at this point from our experience in the market is going to be towards having sample prep partners where we have, in some way, characterized and validated the performance of their reagents in front of our product. If you go out today and buy an enrichment kit for name your favorite protein and you buy it from 3 different people, I can assure you you're going to get 3 very different sort of purities, concentrations, what other things come along for the ride. It's -- we have an application development team that interfaces with customers daily, and we see this.

So I think where possible and where it's a very important application or where we want maximum control over the performance in terms of the claims we can make, I think you'll see us have partners and steer customers to using certain kits in front of our technology. I think more fundamentally on the technology point, I'll let Todd talk about how he thinks about this aspect.

Sure. And I think Jeff's answer is really the most important part of the answer because the sample prep aspect and the noise that comes from other things in samples, that really does drive more into how we deal with the sample, how we get it into the system. The SNR that I presented in the presentation is about we've immobilized the peptides on the chip, and we have our binders in solution and they're binding to the N-terminal amino acid. And it's that fundamental like level of signal that we detect over the background noise in the system. And that really has more to do with the background from the binders that we have in solution, the background from the imaging system, and those are fundamental aspects of the system we have a lot of control over.

So we really define that SNR component, and it gives that very sensitive detection. The other component from the sample prep is, well, we could have a bunch of off-target chip on things on the chip that we will also be sequencing, and we have to tease that out. And a lot of that goes to how we prepare things that we sequence and the software on the back end, how we process it. So I think there are a little bit 2 different SNRs.

Thank you. The last question from me. So there's a lot of advancement, which has been achieved, obviously, both on the recognizer side and the PTMs and whatnot. So if you want to keep Platinum as the annuity going forward, how can -- or all these improvements, can they be taken back to the Platinum and Platinum Pro and still be used in those missions?

So I think there's 2 answers to that. One is from a sequencing chemistry perspective, a lot of the sequencing development we do is still on platinum. So we know these capabilities work there. I think the question we have to sort of work through as we lead up to the sort of the platinum upgrade and sort of goes to your first question, which is what's the overlap is really what will that overlap be and how many people are going to want to move anyways and then sort of what then is the remaining base and what's the cost and value of maintaining now 2 different architectures, 2 different product lines. I think we don't have any definitive plans right now to say, hey, we're ending platinum on someday. We don't have that type of -- that level of thinking.

But I think we're going to let this sort of conversion or upgrade path probably inform that before we decide to make it backwards compatible in terms of doing the development to bring it on board. But the fundamental chemistry, the fundamental algorithms, those things could work on either platform. One just looks at lifetime and one looks at color. So they could go there. It's really more that question of the overlap in those bases. Obviously, there's a lot of benefits to customers to move the Proteus. There's a lot of cost benefits for us to [Technical Difficulty] move weigh all those factors.

It's Scott Henry with AGP. From a big picture, with the new technology, the challenge is always to find the inflection point where you could reach exponential growth where things take off. And it sounds like what I'm hearing today is that you think PTM could be the driver that has larger mass appeal than what the customers are asking for. And it sounds like going from 2 million wells to 10 billion is incrementally and helpful, the same with going to all the amino acids. Is that the right takeaway? Do you think that is the key driver?

So I would intersect the amino acid coverage with PTMs because those things together sort of are amplifiers. You sort of -- the better the coverage, the more data and sort of richness of information you get, the more things you can identify. If you take a step back though and maybe answer it from a customer perspective versus the technology perspective, I would tell you that PTMs are the thing that are of biological relevance and importance and are very difficult to do. When you talk with customers, yes, I can point you to a lab that has the highest-end mass spec machine, has amazing infrastructure, custom pipelines, all kinds of different things that can do a lot more than the average mass spec lab with the same piece of equipment.

So we do think PTMs is a major sort of opportunity in terms of its importance and it being underserved, but we do need to intersect the coverage with it to get sort of the bump we want in terms of performance. But I think if we do what we described here today, that would be the jumping off point, we think, for Proteus is really being able to do broad PTM profiling.

Great. Now with regards to getting to 20 amino acids, what is the risk profile of that challenge? Is it blocking and tackling? Or is it pretty predictable?

John, do you want to take -- I'll give you my first answer, and then I'll let John add a little color, which is if we were -- if we thought it was a big architecture leap like Proteus was, we didn't talk about Proteus until we were comfortable that we understood sort of the risk matrix in the list. And we -- and while it wasn't derisked when we came here last year, we had enough confidence that we could get there that we talked about it. I think we -- similarly, is it 0 risk? No. But I think we were comfortable that we sort of have control over this enough and have a sort of a robust process that we can get there. But maybe John can talk about sort of how he thinks about it and manages through it with the team.

I mean I think what I was showing in the slides was we have demonstrations of how to get from A to B, we've done it. We can make -- go get new binders, we can take existing ones, modify them. So I think all pathways are open. And so I think I agree. I mean the risk profile is low. The only part is I can't exactly anticipate how it's going to turn out. I don't exactly know how it's going to go, but I'm confident that we'll get there. I've seen the internal data. We're already at 18. We have them. We have to just close the gap.

I think the hard thing for the guys and the gals doing this work to predict is always -- I think John laid out again sort of -- if you remember back to his presentation, he said, "Hey, here's the 8 recognizes I think I'm going to need, but don't hold me to the exact combination." I think that's that sort of how question. But again, if we weren't comfortable that we could do it, we -- I think anyone who's interacted with the company for the last 3 years, if we didn't think we could pull it off, we wouldn't be sharing it here today. We would have taken a more muted position on path to 20.

Okay. Great. A final question. Just when we model out the launch curve for placements, it sounds like at some point, customers will be waiting for Proteus. Is that a fair assessment that 2026 platinum sales will probably flattish. There will be sales, but the bigger focus will be that 2026 launch. And any comments how you would expect Proteus to launch? Will it be early adopters? Or will it more wide scale? Just curious your op.

Sure. And some of this, Scott, will bring out in more wholesome sort of updates as we get to some of these commercial milestones in Q3. I think the first part of your question, I think it's fair to assume that as more information gets out about Proteus, especially those external customer collaborators start talking about it, that obviously has a muting effect on the current platform. But I think that's okay. We have a certain number of machines already built. We can use those via placements and get data generated and get consumable usage. So maybe we don't capture the top line of having sold an extra platinum. But if we have a user of the tech who then wants to upgrade, we'll get to capture that when we get to the Proteus launch.

So I think it's a good trade-off to make for sort of short-term top line over the longer term sort of potential to get more people on to Proteus earlier in its life cycle. I think in terms of how to think about the modeling of that, we're not really able to provide guidance on that yet today. Again, I think as we go through these dialogues, as we start to release information, we'll get a better feel for who's going to be an upgrader versus who's a net new address.

And I think that will play a lot into how we start to try to provide guidance to the Street on what the adoption looks like because obviously, converting somebody where you've done that work where they're already a believer in the tech is a lower burden than it is to go get a brand-new address. So I think we'll learn a lot over the next sort of couple of quarters and have visibility into what do we think that mix might look like at launch.

Puneet Souda from Leerink Partners. So Jeff, thanks. I'll wrap my questions into one. When you look at the 20 amino acid detection, how much of a fidelity do you have across them in terms of performance? Are you detecting them at the same performance level? I think that's an important point. And then when you look at the PTMs, phosphatidylserine antibodies have been around for a while. And the combined -- what I'm trying to understand, are you combining kinetic with those to actually enhance the performance?

And what does that mean for your gross margin, both in terms of what the output is and what it means for gross margin if you're going to employ more of those binders and antibodies? And then last one around the positioning of the product. On one side, you've got Orbitrap, the timsTOFs, you've got the low-plex immunoassays on one hand, but the high-plex, you've got the PA and Olinks and aptamers and other technologies. So just thinking about all of that, how are you positioning the platform?

Okay. So go back to coverage. So I think you picked up on a very good, I think, sort of like next level detail, which is your -- which is why we talked about demonstrating 20 and then having it in the kit because there's a difference between sort of demonstrating and having enough of the coverage of that amino acid every time it shows up in the proteome. So we think there's -- you got to have some cycle to convert that and get into the kit in '27. I think John focused mostly today on just specifically how do we detect all 20. But what he didn't talk about, but is something his team actively works on is they're always looking to up the coverage of any given recognizer.

So some of those recognizers have been evolved for a long time. So they have very high sort of sequence context. Some of the ones have less, and those are actually being evolved in parallel. So it's not exclusively just new. It's about just moving everything up to maximize all the sequence context you can see. That also wraps in with what Todd talked about, which is sequencing depth. So those 3 things together, maximize it when it's present, maximize the depth you can get and detect all of them. Those 3 together is what gets you to sort of the maximum coverage. And all 3 of those things are being worked on.

We just sort of focused mostly today on helping people understand this wasn't going to take us 3 more years to detect all 20. We were going to get there sooner. In terms of the positioning of the product, so I would agree with you that there's sort of different markets and different ways to cut it. I would say our view on PTMs, on variants and some of these other types of analysis in ultra-low abundant biomarker panel is really trying to focus our tech where we think it will have stand-alone value in the face of those other technologies.

What we're not standing here today telling you is we're trying to figure out how to do 10,000 proteins from plasma to go compete with Orbitrap because we think it does a pretty nice job of that based on the data. We're not trying to necessarily today go compete with Olink, who says, I'm going to give you 5,000, 6,000 proteins from this sample and give you relative abundance. We think those are great. Those are needed, but we think downstream of that, there's lots of work to now explore those panels they identify for PTMs and these other things that they can't do, and that's sort of the place to go fit in rather than chase a 5,000 biomarker panel that now we're sort of like in the margin of, well, we're better at this, they're better at that, and you don't really have that differentiation and some of the opportunity to maybe differentially price.

So that's why you hear us moving, again, both from our own assessment of the market, but also I think it shows up in the customer data. They're not asking us to give them a 5,000 protein panel. They're asking us to help them look at methylation, acetylation and phosphorylation on this protein because they can't do that. So I think competitively, it makes sense. What the customer is saying sort of ties to what -- sort of where the competitors tend to be really good right now, and we're mindful of that when we're coming to market. We'll let RK have another.

Actually, it's a corollary to a question that Scott asked. So do you need to have either 18 or 20 amino acids and the enough number of PTMs for Proteus to be a useful technology? Or what you have is good enough to get Proteus to be launched?

Yes. I think the answer to that question is we're going to -- we -- so first of all, the fundamental capability, and I'll tie it back to Puneet, I missed one part of your question and just sort of spurred my thinking now. So the coverage component of amino acids, the better the coverage we have, the more of the PTMs we can do via kinetics. And then the less we would need a specialized recognizer or some sort of other affinity reagent. When we use an affinity reagent though, the nice thing is we need very little to be able to see it at a single molecule level.

So some of the work Brian showed in phosphorylation, when we've used some of these off-the-shelf reagents, we can use them at very low concentration. It's sort of in the noise of sort of the cost of goods of building a product. But our tilt as a company, right, our bias wherever possible, will be to do as much of the PTMs through the kinetic signatures as possible. We use these other tools when we want to maybe optimize for a certain use case or capability the customer is asking for that we don't yet have in sequencing.

So to your point, though, RK, I think our view is the 20 amino acid coverage is the foundational thing we got to do. That opens up how we apply it. When do we apply it towards PTM 1 versus 2. And I think that goes back to my earlier point, which is we're spending that time with customers right now. Phosphorylation is obvious. It's -- that's why we show data on it where we've been doing a lot of work in the area. We've been doing work, as Brian showed, both in kinetic signatures and with pre-recognition. That all underlies what customers are trying to do, what some of the partners like Carna are trying to do.

So it's informed by that. So obviously, phosphorylation is something that's top of the list. But how we allocate our time between now and the launch to bring on the other PTMs really comes back to this sort of prioritization we'll do with customers on which ones will add the most value to them. So we expect it to be more than just phosphorylation, but exactly what it is, we don't know that answer today. But we are focused on what you're asking, which is what is the totality of capabilities? Because again, PTMs is a part of it, but if we can do an ultra-low like an interleukin or a cytokine, those -- that's also an application very difficult to access with other tech.

So I think we're looking at the totality of things we can do, things we can partner to deliver to answer the exact question you're answering, which is make sure when we get to the Proteus launch, we have a wholesome set of capabilities to drive the adoption of the platform. We're definitely very cognizant of that, and that's where the focus is.

All right. With that, I think that's the end of the questions. Again, for everyone in the room and those online, thank you for joining us today. We appreciate your interest in Quantum-Si, and we look forward to future updates. Thank you.

Good day, and thank you for standing by. Welcome to the Quantum-Si Third Quarter Earnings Conference Call. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Risa Lindsay. Please go ahead.

Good afternoon, everyone, and thank you for joining us. Earlier today, Quantum-Si released financial results for the third quarter ended September 30, 2025. A copy of the press release is available on the company's website. Joining me today are Jeff Hawkins, our President and Chief Executive Officer; as well as Jeff Heyes, our Chief Financial Officer.

Before we begin, I would like to remind you that management will be making certain forward-looking statements within the meaning of the federal securities laws. These statements involve material risks and uncertainties that could cause actual results or events to materially differ from those anticipated. Additional information regarding these risks and uncertainties appears in the section entitled Forward-Looking Statements of our press release. For a more complete list and description of risk factors, please see the company's filings made with the Securities and Exchange Commission. This conference call contains time-sensitive information that is accurate only as of the live broadcast date today, November 5, 2025. Except as required by law, the company disclaims any intention or obligation to update or revise any forward-looking statements.

During this call, we will also be referring to certain financial measures that are not prepared in accordance with U.S. generally accepted accounting principles or GAAP. A reconciliation of these non-GAAP financial measures to the most directly comparable GAAP financial measure is included in the press release filed earlier today. With that, let me turn the call over to Jeff Hawkins.

Good afternoon, and thank you for joining us. On today's call, we will provide a business update and review our operating results for the third quarter of 2025. After that, we will open the call for questions. I will begin with a reminder of our 3 corporate priorities. To accelerate commercial adoption, to deliver on our innovation road map and to preserve our financial strength.

Our first corporate priority is to accelerate commercial adoption. Our revenue for the third quarter was $552,000 as top line results continue to be impacted by the capital sales headwinds in the market. As a reminder, during the second quarter, we announced the launch of an expanded set of instrument acquisition options that allow customers to have our instrument in their lab and purchase and run consumables without having to find the capital dollars to acquire the instrument upfront.

Since launching this initiative, we have had 12 new customers implement our platform and all have made their initial reagent purchases. Importantly, more than half of these new customers are in academic labs, a segment that has been very difficult for us to access in 2025 due to the NIH funding challenges. We are very pleased with these early results and expect to continue to offer these alternative options going forward since we view our growing installed base, not just as a revenue driver, but as a strategic moat. We continue to believe that with every new lab that implements our platform, we will see increasing consumable sales, scientific validation and customer advocacy. We also believe that many of these customers will be strong sales opportunities for our future Proteus platform.

One example of the strategic value of the placement program is the initiative we announced in June of 2025 with the Broad Institute. The goal of this placement was to enable researchers access to our single molecule protein sequencing technology, both within Broad Institute and across the greater Boston Life Science ecosystem. I'm pleased to report that this initiative is progressing well. We have two active projects underway now and another two in the final stages of study design. We would expect those two studies to be initiated soon. In addition, we have executed on educational seminars with local researchers to build a funnel of additional research study opportunities that can leverage this instrument placement in the coming quarters.

Turning now to scientific affairs. During the second half of 2024, we communicated that we were increasing our investments in scientific affairs with the core focus being to build our Scientific Advisory Board and develop a pipeline of publications to demonstrate the value of our technology. Developing a publication pipeline takes focus and effort over an extended period of time before it yields results. During 2025, we have had 5 manuscripts submitted for publication. Two of those have been published in peer-reviewed journals and the remaining 3 are in the review process. Additionally, we have a strong pipeline of activity with more than 5 manuscripts being drafted now and another 8 studies actively generating data that will fuel the pipeline of publications well into 2026.

Beyond these initiatives, we continue to monitor and evaluate several partnership opportunities that may assist in accelerating certain components of our development activities, spanning from new customer applications to sample preparation and enrichment and applications of artificial intelligence tools that could extract deeper insights from the protein sequencing data our system generates. We remain very confident in the long-term market opportunity in proteomics, the initiatives we are executing on commercially to accelerate awareness and increase the size of our installed base and the technology road maps we are executing against to capitalize on the market opportunity in front of us.

Our second priority is to deliver on our innovation road map. We continue to make solid progress across all of our development programs. Most importantly, today, we announced that we have successfully completed sequencing runs on a prototype Proteus system. We communicated this goal at the start of the year as it represented the single most important milestone for the program to achieve in 2025. And it is not just a single prototype. We have multiple prototype systems performing sequencing and are excited about the quality of the data we are seeing at this stage of the program. As we continue to mature the platform and work through the optimization of our sequencing chemistry on Proteus, we expect the data quality to continue to improve. We look forward to sharing more of the early sequencing data in addition to other proteus program updates at our Investor and Analyst Day on November 19.

Turning now to our version 4 sequencing kit. We are pleased to share that we achieved the commercial launch of this new kit in early September and completed our first shipments to customers during the third quarter. As a reminder, this new kit includes increased amino acid detection capabilities and the addition of a new enzyme that is engineered specifically to provide high-efficiency cutting of the amino acid directly preceding a proline. This is important because Pine is abundant in many vital proteins, such as membrane proteins, antibodies and transcription factors and protein-rich. Proteins are well known to be difficult to analyze by mass spectrometry. In addition, as part of the version 4 sequencing kit launch, we released an expanded set of 24 barcodes that allow customers to increase the multiplexing level of their experiments while maintaining the same level of analytical performance they have experienced to date with the original set of 8 barcodes.

Moving now to library preparation. Our version 3 library preparation kit has entered our internal validation process and remains on track for launch by the end of 2025. We are pleased to share that this kit remains on track to lower the sample input quantity requirement by at least 100-fold as compared to our current library prep kit. This lower input concentration requirement is expected to allow our customers to be able to process a broader range of biological samples and to study biologically relevant proteins that are a much lower concentration than our current library prep kit can accommodate. When combined with the V4 sequencing kit, we believe that customers will experience a meaningful level of improvement in overall system performance and be able to pursue some of the more complex biological sample work that to date has been difficult to do with our technology.

Finally, I would like to update you on our amino acid recognizer development program. As we have previously shared, our recognizer development program has designed and screened millions of candidates over the past few years. As part of that process, we have amassed what we believe may be the richest set of data in the industry about how mutations inserted into engineered proteins affect their binding to N-terminal amino acids, the kinetic properties of those binding interactions, binder specificity, stability and many other features. We are very excited about our ability to leverage this proprietary data set in combination with advanced artificial intelligence tools to efficiently scale up the recognizer development program and significantly shorten the time line to full proteome coverage as compared to our historical trajectory. We look forward to sharing more about this topic at our Investor and Analyst Day on November 19.

Our third priority is to preserve our financial strength. While the capital headwinds in the market are expected to continue to impact short-term commercial results, we are optimistic about the early traction we are seeing with our placement program and the opportunity to continue to grow our customer base using this approach. We firmly believe that a large installed base of active users is a strategic advantage that will position us well for the future launch of Proteus and ultimately create long-term value for our shareholders.

Finally, we believe that the current capital market has and will continue to impact otherwise good companies and product lines. We believe our strong balance sheet positions us well to execute on strategic opportunities that may arise based on the current market environment. We will continue to monitor and review all potential options that could accelerate or be additive to our long-term strategic initiatives, including opportunities that could broaden our participation in the overall multi omics marketplace. I'll now turn the call over to Jeff to review our financial results.

Thanks, Jeff. Now I'll review the details of our operating results for the third quarter of 2025. Revenue in Q3 2025 was $552,000, which consisted of revenue from our Platinum line of instruments, consumable kits and related services. Gross profit was $194,000 and gross margin was 35%. As I've said in the past, our gross margin percentage will be somewhat variable for the foreseeable future as we work through our continued commercialization efforts and may be impacted by the timing and mix of instruments versus consumable sales. Our margin has also been impacted and may continue to be impacted by the acquisition costs and accounting adjustments to underlying inventory, some of which predates the commercial launch of the Platinum line of instruments.

For the 9 months ended September 30, 2025, revenue was $2.0 million and gross profit was $1.0 million and gross margin was 52% -- adding to what Jeff mentioned earlier, our year-over-year revenue was impacted in the third quarter by continued capital market headwinds driven by uncertainty in NIH funding affecting the macro market. We were impacted partially in the first quarter by this concept but have felt the full effect in the second quarter and third quarters. By introducing the alternative capital acquisition models, including the placements Jeff referred to, we will continue to broaden our installed base. While these placements do not generate instrument revenue associated with the delivery of the unit, the underlying consumable volume creates revenue and more importantly, awareness and customer data as volume increases.

Turning to operating expenses. GAAP total operating expenses for the third quarter of 2025 was $40 million compared to $28.5 million in the third quarter of 2024, while adjusted operating expenses were $21.4 million for the third quarter of 2025 compared to $26.0 million for the third quarter of 2024. For the 9 months ended September 30, 2025, GAAP total operating expenses were $96 million compared to $78.9 million in the same period in 2024 and adjusted operating expenses were $68.1 million compared to $72.3 million for the same period in 2024.

Overall, adjusted operating expenses decreased year-over-year. This decrease continues to highlight our very tight cost controls we have for the organization while still funding innovation and significant development progress of our Proteus platform and other programs that did not exist in the same period of 2024. Of note, included in our GAAP total operating expenses for the third quarter is an expense of approximately $13.6 million that represents the accounting adjustment of a net termination payment and related asset write-off associated with the lease facility in New Haven, Connecticut that would have originally expired in 2032.

In September, we settled our previously disclosed dispute with the landlord regarding unreimbursed tenant improvement funds and as a part of the settlement, terminated the lease. The net incremental cash outlay associated with this termination was $10.2 million. By terminating this lease now, we saved over $24 million of future operating expense associated with the lease.

Next, our dividend and interest income in the third quarter of 2025 was $2.6 million compared to $2.7 million in the third quarter of 2024 and $7.4 million in the 9 months ended September 30, 2025, compared to $9.1 million in the same period in 2024. Overall, this change is reflecting lower interest rates year-over-year as well as relative lower invested balances. As of September 30, 2025, we had $230.5 million in cash, cash equivalents and investments in marketable securities.

Regarding 2025 guidance, we expect adjusted operating expenses will be $96 million or less and total cash use will be $103 million or less. Previously, we had indicated that we would utilize $95 million of cash, which was before we completed our termination and settlement agreement related to our New Haven facility. This updated number of $103 million is inclusive of the net $10.2 million payment under the lease termination agreement, meaning outside the lease termination, we are falling below the previously communicated $95 million of cash, highlighting our continued focus on most efficient use of our cash possible. This lease termination payment is not expected to affect our long-term cash position or runway because, as I mentioned, we will now avoid over $24 million of operating expenses associated with this terminated lease.

In late September, we filed a Form S-3 shelf registration statement for $300 million total capacity and also an at-the-market facility or ATM that utilizes $100 million of that shelf capacity. These 2 vehicles are intended to provide capital capacity for the company to support business and strategic initiatives and are ultimately appropriate good housekeeping to have in place. Going forward, we will continue to ensure the company is appropriately capitalized to execute on strategic plans and maximizing value for our shareholders.

As a company, we are fortunate to have broad ownership of our stock, which includes at present, roughly 38% retail ownership. Having this broad ownership is one of our strengths, and we appreciate the interest and support in Quantum-SI. I do monitor major retail message boards to understand what new or compelling concepts might be important to our retail holders, and we'll do our best to address these questions and concepts in future calls and presentations. Two comments that have come up periodically surround overall company ownership of management and directors and why certain management team members have recently sold stock in relation to Form 4 filings.

First, as of the most recent look, our management and Board collectively held approximately 18% of the total outstanding stock of Quantum-Si, showing our continued deep investment in the success of the company. Regarding share sales, as you know, part of the management team's total compensation is provided via equity grants, including restricted stock to continue to align management incentive with shareholder value and return. As these restricted shares experience scheduled vesting events, a certain number of vested shares are mandatorily sold as part of our stock plan design to cover estimated withholding taxes, which is the reporting that can be seen via Form 4s.

Looking back for 2023, 2024 and 2025 year-to-date, no ongoing reporting management team member has sold company stock outside these mandatory redemptions to cover taxes for vested restricted shares. Again, we appreciate the broad ownership and interest in the company, and I am always available to have discussions regarding the company's strategy, development, programs or anything else to more educate our shareholders. Now I'll turn the call over to the operator to open the line for questions.

[Operator Instructions] First question comes from Kyle Mikson with Canaccord...

This is Alex on for Kyle Mikson. So to start, could you elaborate on what you discussed at the Investor Day in November? And importantly, we provide some key updates on the development of the proteus sequencer? And when might we see some data generated from this instrument? Moreover, do you think that the enhanced performance and throughput of this instrument should unlock new applications that increase the utility of protein sequencing across multiple end markets?

Yes. Thanks, Alex, for the question. So at the IR Day coming up here on November 19, in our prepared remarks, we said we'd provide more of an update on Proteus, including some of that early sequencing data. So to your point, that will be your first look at the data we're generating that we mentioned today. We'll provide an update on our recognizer development program and very specifically where are we at with that program. Where do we think we'll be in terms of our proteome coverage at the launch of Proteus and when do we think we'll get to all 20 amino acids. So a few big sort of data points out there that we expect to provide more clarity on how we're thinking about getting to those key milestones.

And I think to your last point, part of our Investor Day, we would expect to provide sort of a view of the milestones that we would achieve and be able to talk about throughout 2026. So some of those could be R&D oriented in terms of progress with Proteus and others of those will be more commercially oriented, things like early access sites, list pricing of the machine, those types of milestones. So we'll give sort of a good calendar of milestones for 2026 sort of on that road to launch of Proteus at the Investor Day as a way to give you sort of a way to measure where we're at and how we're progressing against that launch.

Great. Switching gears a bit. The DARPA has initiated the PROS program to demonstrate molecular readers can accurately read a broad range of amino acids and PTMs in sequence for unknown protein samples. Just curious if you're able to comment on any level of involvement plus interest you have in this program.

Yes. So we're aware of the program, Alex. We've participated in some of the industry and academia sort of interactions, advisory boards, sort of roundtables, whatever you might want to call them on the topic. DARPA has a -- if you read the PROS program, it has a pretty heavy tilt towards trying to build a micro system, which is essentially some very sort of portable sort of approach. That's not really what we're building. So we're certainly engaged with DARPA and have engaged in that process. But I'm not sure that our approach, which is really seeking to have the sort of throughput and capabilities that you need in research and translational labs that doesn't really perfectly match that sort of micro system strategy.

I think the other important thing to remember, we've talked on previous calls, we have instruments in the major Department of Defense labs right now. Those are in military labs that do proteomics research. Those folks have been leveraging our technology to work on their initiatives. I suspect some of those are -- they underlie what perhaps DARPA is trying to achieve with PROS. And we are aware that those customers are looking to, over time, release some of the data and findings that they're getting with our technology. So we might not be a perfect fit for the PROS project as described, but very importantly and where we're really focused is supporting those existing Department of Defense installed machines and really supporting those customers who are doing the work of really looking at how to apply these technologies in their areas of sort of strategic importance.

And one last one for me. On placements this quarter, can you break down just either quantitatively or qualitatively the bulk of them was biopharma, academia? And then just in terms of end markets and customer types, are you seeing some bright spots? And where are you continuing to experience, I guess, continued pressure?

Yes. So I think as we mentioned in our prepared remarks, the one advantage of opening up sort of the different ways to acquire our platform is it really did give us access to some of those key academic centers, both here in the U.S. and in key areas in Western Europe that we had more challenges getting into recently, certainly the ones here in the U.S. with the NIH funding. So more than half of those placements went into academic labs. The other half were sort of split across a mix of pharma and biotech and even into ag or agricultural sort of testing. So a good mix, but a little more than half of those in the academic setting.

I'd say what we're seeing in the market is -- hasn't changed dramatically. Biotech and pharma is still moving forward and making capital purchases, albeit on a longer sales cycle. We see a sales cycle in that segment that's around 9 to 12 months. It's a pretty long cycle. But once in, they're a good sort of routine user of the technology. I'd say academia has been sort of the slowest area with the challenges around the capital side. Again, placements sort of opening up that opportunity. But amongst our installed base and this placement base, people do have consumable budgets.

So as I mentioned in the remarks, all of our placements, those customers have purchased their initial kits. So we are seeing consumable budgets there. It's really more the capital side, and we're going to keep using the placements to drive more penetration into all the segments, but obviously, a pretty heavy focus on getting deeper and deeper into the academic setting. The big advantage in that setting, if we think about sort of the bigger goal, right, to really show the validation of the tech and build the momentum into Proteus is academic labs are prolific publishers. And some of your pharma and biotech customers don't tend to publish as much of their findings. So that placement program really is key to getting to those customers, not only for them to get comfortable with the tech, but to really have that flow of data into the market through publications.

Our next question comes from Scott Henry with AGP.

A couple of questions, if I could. First, historically, fourth quarter has been an up quarter over third quarter, but a lot of different variables this year. I don't know if the shutdown impacts some of your customers, I don't know. But I just want to get your sense of how we should think about that typical seasonal trend from third quarter to fourth quarter?

I would say, if you think industry sort of historical, I think you your sort of analysis is correct, you tend to see some improvement in the fourth quarter. I think in what we might call normal years where we haven't had some of the geopolitical challenges, the NIH funding uncertainties, sometimes Q4 can really be a healthy step-up for businesses. I think this year, based on everything we're hearing from our colleagues in other companies, what we're hearing from customers, I think it's we're not going to see that huge upswing. I think we might see a modest improvement in Q4 as maybe a few people who have budgets are able to use them, but I don't expect it to be as sort of a significant of a step-up as maybe we've even seen historically Q3 to Q4.

Okay. Great. And on the political front, I know we are waiting to get an NIH budget. Do we have any updates there? And how does the shutdown impact that funding?

Well, where it last left off that we saw was the proposals that we're routing on the congressional side certainly looked to retain NIH funding at sort of a flat to more marginally down from the prior year, certainly a much better potential outlook than what was proposed by the administration. But obviously, with the shutdown, there hasn't really been any progress moving those resolutions forward through Congress. Obviously, the focus is clearly on some sort of way to reopen the government through a continuing resolution. So not really any more to say other than at least what was moving through the congressional committees was more positive.

I think the other item, Scott, that we've talked about before, and I know others have talked about, the other thing that's out there that no one really has a good beat on yet is what will -- once that budget is in place, how will the administration and sort of payments of those grants go? Will we see a more steady, consistent sort of set of behaviors there? Or will we continue to see some of the rescissions that we have observed earlier this year in 2025. Some of those rescissions sort of create a chilling effect on academic customers. So I think that's still something to be seen. But first, we need to get through this shutdown process, so those bills that were moving through the process that look to retain a better level of funding than originally thought get actually enacted into law and can move forward.

Okay. Just the final question, certainly, great milestone as far as running sequencing runs on the proteus. The question is, what are the hurdles left, the key hurdles between where we are now in getting to market launch?

Yes. I'll give you a little flavor here. We'll get into it in more depth at our Analyst Day, and we'll have some of our key R&D leaders there, Scott, and you're more than welcome, obviously, to ask questions and they can answer that from their perspective. I would say the first thing to say is we announced this program in November of 2024, and we said we would launch it by the end of '26. So slightly more than 2-year program, which in our industry, it should not go unsaid that, that is sort of an extraordinarily aggressive time line for such a big sort of platform evolution. I think it's a testament to the quality of R&D teams, leaders sort of processes that we have here that we've achieved this milestone on time, and we laid this milestone out almost a year ago now and have hit this milestone. So we're very excited about the milestone.

I think as you look forward, we have to now scale from prototypes into fully integrated systems. You have to harden those systems off and move those through into the manufacturing sort of processes and bring up, you can do this at scale. You have the integration with the chemistries and optimization for that platform. So a lot of what I would call integration, manufacturing bring up, optimization and really then intersecting the hardware and consumable with all the work we're doing in library prep and with sequencing. So we'll talk about some of these different sort of parallel streams that we will look to have all intersect at the launch of Proteus. But I think the -- this milestone is important because it says we have an architecture that works. We have the ability to use our current chemistry on that. So I think that takes a big risk off the table as compared to brand-new platforms that haven't yet demonstrated this functional level of performance.

Next question comes from Charles Wallace with H.C. Wainwright.

This is Charles on for RK. Sorry if I missed it on the call, but could you share how many academic centers have entered the placement program? And is there an internal target that you guys are trying to reach in this program?

So the data we gave was of the 12 placements we made in the quarter, a little more than half of those were academic. In terms of a target, we don't really have a target, Charles, for how many accounts we want to try to access. I think our view has been be in the market with our sales folks. When there's opportunities to sell capital, we do it, but where we think it's a very important center, an opportunity to generate great data and get it published, we can leverage this placement program. We expect to continue to do that in the fourth quarter. And I think in terms of -- if you flash forward, what are we going to do in 2026, I think we're still sort of pulling our plans together there for exactly how far would we continue to push this placement program during 2026. I suspect we'll continue to do it in some fashion, but we haven't really set a sort of a ceiling or a target number.

Really, what we're focused on are those high-value important sort of academic centers or even into other segments in biotech, that pipeline of publications and really trying to look for the folks that with experience with our tech would be good targets for Proteus. We want this to also really help us build a pipeline as we go into the Proteus launch later this year. So continuing with the program as is. And as we get into early '26, we'll be able to provide a little more color on if there's any sort of caps we're going to put on that or how we're thinking about it throughout '26.

I'm showing no further questions at this time. I'd now like to turn it back to Jeff Hawkins for closing remarks.

Thank you for joining us today. We look forward to sharing more updates on our Proteus program, the -- recognize the development program and other R&D pipeline initiatives at our Investor and Analyst Day on November 19 in New York City. Thank you.

Thank you for your participation in today's conference. This concludes the program. You may now disconnect.