Nautilus Biotechnology Stock

Good day and thank you for standing by. Welcome to the Nautilus Biotechnology Second Quarter 2026 Earnings Call. [Operator Instructions] Please be advised today's conference is being recorded. I would now like to turn the conference over to your speaker today, [ Chi-Yan Eag ] with the Gilmartin Group. Please go ahead.

Thank you. Earlier today, Nautilus released financial results for the quarter ended June 30, 2026. If you haven't received this news release or if you'd like to be added to the company's distribution list, please send an email to [email protected]. Joining me today from Nautilus are Sujal Patel, Co-Founder and CEO; Parag Mallick, Co-Founder and Chief Scientist; and Anna Mowry, Chief Financial Officer. Before we begin, I'd like to remind you that management will make statements during this call that are forward-looking 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 in the press release Nautilus issued today. Except as required by law, Nautilus disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward-looking statements, whether because of new information, future events, or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast on July 28, 2026. With that, I'll turn the call over to Sujal.

Thanks, [ Jian ], and thank you all for joining us today. We spent the last 9 years building what I believe is 1 of the most innovative platforms in life sciences. It produces a layer of biological insight that we believe does not exist anywhere else in the world today. This is the conclusion we're hearing from a growing number of scientists once they see our data, and it's the reason I'm confident about where this company is headed. We believe that a platform this capable has many possible applications. We've walked you through them on these calls over the past few years. This quarter, I want to focus on a deliberate strategic realignment of where we point the platform and on the reasoning behind it.

Let me start with the decision itself. We're moving a significant share of our R&D resources from our broad-scale application to our proteoform application. We're doing it for 2 reasons that reinforce each other. The 1st is genuine momentum. The scientific community is telling us directly in conference halls and in our own sales conversations that proteoform resolution is a critical, differentiated layer of biological insight and 1 we believe we can uniquely put in customers' hands today. The 2nd is that broad scale needs more time, and I'll come back to that in a moment. Let me say more about that 1st reason. Since launch, we have seen strong and growing customer enthusiasm for the proteoform approach and the unique insight it can deliver, including numerous additional customer-requested proteoform targets.

The feedback coming through our sales team this year has been consistent, and it represents what we believe to be a substantial commercial opportunity. Given the potential scale of that opportunity and our technical performance to date, we're significantly shifting resources across the company and putting a new roadmap in place to accelerate our proteoform applications. We're also going to lean harder into partnerships with pharma and academic institutions to push these capabilities further and faster than we could on our own. This is not a sudden shift. Anyone who's followed the company over the past 1 year will recognize the trajectory that's been pushing us in this direction. When we built our iterative mapping applications, we expected broad scale 1st and proteoform 2nd. Our platform matured in the opposite order, and we've been turning the proteoform dial up quarter after quarter.

Let me lay that trajectory out. 1 year ago, a preprint with our collaborators showed for the 1st time that we could measure tau proteoforms at a resolution no 1 had ever achieved. Next, we signed a collaboration with the Allen Institute for Brain Science to analyze human brain samples, spanning multiple brain regions, genetic backgrounds, and disease severities. Our alpha instrument at the Buck Institute for Research on Aging also began producing real biological data, and that data was presented at major scientific conferences, revealing biology in Alzheimer's that the field has chased for decades and never been able to see. In the 1st quarter, the Michael J. Fox Foundation funded us to build the next proteoform assay for Parkinson's, and Baylor College of Medicine became our 1st early access customer for tau. And now, in the 2nd quarter, we recognize our 1st revenue from both Baylor College and the Michael J. Fox Foundation grant-funded development work. We also selected AKT1 as our 1st oncology proteoform assay, 1 of 3 oncology targets that have now cleared our development criteria.

Now, let me come back to the 2nd reason, broad scale. Our broad proteome application is behind the timeline we set. In the 2nd quarter, we completed testing and determined that our assay configuration changes did not sufficiently improve probe candidate performance to support a 2027 general availability of our broad-scale application at our target specifications. We have an exceptional team working on an extraordinarily hard problem, and hard science is unpredictable. Some of the development efforts we are undertaking next, which Parag will describe in detail, are inherently long in duration, on the order of several quarters. In the meantime, we're moving the majority of our application-specific R&D resources into proteoform development, keeping a focused team on the most critical parts of broad scale to keep advancing the program and reduce its key technical risks. Shifting resources from broad scale to proteoforms will impact the pace of development in broad scale, but given the opportunity we're seeing in proteoforms, that's a tradeoff that we're willing to make.

Let me briefly touch on where this path could lead. As we continue to rapidly develop our proteoform portfolio and expand the capabilities of the assays, we believe new opportunities will arise that were not necessarily available to us with a broad-scale 1st format. 2 of them are worth planting a flag on, even though they're both very early. The 1st is the clinical market. Our original thinking with a broad-scale 1st path was that the Nautilus Voyager would primarily be a research-use-only tool. Our customers would make discoveries on that platform and then build their own high-throughput, low-cost test that they could carry into the clinic. What we're hearing now with proteoform capabilities in customers' hands is different. Customers are excited, and they believe for key markers and key disease areas, proteoform measurements are likely to translate directly into clinical research and eventually into diagnostics.

While it's not our current focus because there's no other platform that can make these measurements, it's conceivable that we could get pulled into the clinical market earlier than we planned, and we've begun to think about how to prepare for that. 2nd is pharma. As we expand our conversations with pharma, they are thinking hard about how to combine different data modalities with AI models and use the results to advance therapeutic development, building therapies faster with a higher likelihood of success. We expect that as pharma begins to further appreciate that our proteoform capabilities provide 1 of the deepest layers of biological insight into disease state and cellular function, we believe opportunities will emerge to partner with pharma to go after new targets, generate data sets to feed AI models, and to add bespoke capabilities to existing assays that meet their specific needs. I want to be clear, both of these are early.

And while we're not putting a plan or a timeline around either of them today, we are beginning to build toward them. Before turning it over to Parag, I want to reiterate that we have a platform that can deliver unique value to the market, and our customers are telling us that the most urgent need now is in proteoforms. Because of this, we've made a data-driven decision to concentrate on the value we can deliver today as quickly as we can. Parag will take you deeper into the science, and Anna will take you through the numbers before I close. Over to you, Parag.

Thanks, Sujal. I want to start with what we're hearing from customers, because it is directly shaping how we work. The heart of it is 1 word, resolution. Our proteoform assays measure the specific molecular states of a protein, its isoform composition, and its patterns of modification at single-molecule resolution. The sensitivity and reproducibility that we believe that existing affinity assays and mass spectrometry methods cannot match. What customers tell us again and again is that this lets them see biology that was simply invisible to them before. Critically, proteoforms are more than just additional protein detail. The specific form a protein takes often determines everything that matters about it, where it goes in the cell, what complex it joins, what pathway it activates, what phenotype it ultimately drives. This is 1 of the reasons the field collectively has struggled to make progress in diseases like cancer and Alzheimer's.

Without the ability to resolve biology at this level, the most important signals have stayed out of reach. Let me add additional color to the trajectory Sujal described. 1 year ago, our preprint with Genentech, Mount Sinai, and the Neural Stem Cell Institute showed for the 1st time that we could resolve the tau proteoform landscape at single-molecule resolution. Our alpha instrument at the Buck Institute then generated data at a median CV of roughly 5.5% against an industry norm closer to 25%. And that data showed that different ApoE genetic risk variants carry distinct tau proteoform signatures. This is a striking result that we believe is only measurable on our platform. ApoE is 1 of the best-known genetic risk factors in Alzheimer's, yet it had never been linked to tau at a mechanistic level.

And we feel that the difference we resolved is invisible to pre-existing proteomics tools. We have also found that model systems widely used in Alzheimer's research show markedly different tau proteoform landscapes from 1 another, a distinction that we expect could prove critical to how drug developers choose their models. These are exactly the kinds of biological differences that bulk methods cannot see and that iterative mapping was built to reveal. They are the kinds of findings that have led researchers to describe our data in their own words as, quote, a game changer and as something that, quote, will become critical to their work. Now let me talk about oncology and specifically why we are leading with AKT1. In Q2, we narrowed our oncology work to 3 candidates, AKT1, EGFR, and p53, and developed them in parallel. All 3 cleared our reproducibility and accuracy criteria and moved into development, which is in itself an important proof point.

It tells us our assay building methodology is now repeatable, not a 1-time success with tau. AKT1 is furthest along, and we expect that it will be 1st to market. It is a compelling place to start for both scientific and commercial reasons. AKT1 sits at a control hub for cell growth and survival signaling. There is already a multi-billion-dollar market in the AKT-targeted therapies, but those therapies have shown mixed clinical results, largely because patient selection relies on indirect biomarkers rather than direct evidence that the pathway is actually driving a given tumor. Proteoform-level resolution provides that direct readout. We anticipate it will be able to identify the patients who are truly dependent on the pathway. In other words, this is a way to improve response rates for drugs that are already on the market with exactly the kind of insight existing proteomics cannot reach.

That brings me to why we expect that we can expand the proteoform portfolio so quickly. Proteoform development is now bottlenecked by capacity, not by scientific uncertainty. We have what we believe is a proven template. We anticipate that the remaining unknowns on each new target are contained, so adding people should translate directly into more assay content and more capabilities delivered faster. The math is compelling. Our tau assay took about 5 years to build. Our 1st oncology markers reached that same technical bar in about 1 year. As we scale the team, we expect to add new assays at a cadence measured in months rather than years, growing from a small handful of assays today toward roughly 20 proteoform assays anticipated by the middle of 2028. That speed lets us be disciplined about where we go next.

We are prioritizing neuroscience, oncology, immunology, and cardiology. Within those areas, we look for targets with ready access to antibodies and a large market opportunity, which we assess through clinical trial activity, publications, NIH funding, and direct customer input. Encouragingly, the demand we're hearing from customers lines up almost exactly with the internal target list we had already built. The scaled-up proteoform development team will aim to qualify new antibodies, build controls and immunoprecipitation protocols, develop and qualify new sample types, and drive down the sample input required. Once we hit our performance criteria on a target, we plan to verify and validate the assay, bring in outside collaborators, and move to early access. The reallocation of our assay development resources does 2 things. It gives us the potential to bring new assay content to market on a regular, predictable cadence instead of in occasional bursts, and it is expected to pull forward the enabling capabilities customers ask for most.

In particular, lower sample input requirements and access to new sample types, including biofluids like cerebrospinal fluid and plasma. Biofluid access matters enormously because it is what unlocks the large majority of the biomarker market. Here is where that leaves the roadmap. Our tau proteoform assay stays in early access with general availability of consumable kits expected in mid-2027. Our AKT1 proteoform assay is anticipated to enter early access in late 2026 with general availability expected in mid-2027. The 2nd oncology proteoform assay is in development, also targeting general availability in mid-2027. We expect a 3rd oncology proteoform assay and continued expansion of the pipeline with additional kits reaching general availability expected in late 2027. For enabling capabilities, we expect to bring a roughly 100-fold reduction in required sample input to early 2027 and to enable cerebrospinal fluid for our tau assay in 2028.

You should expect a rolling series of announcements as new content and capabilities come online roughly every 6 months, increasingly driven by customer demand. Anna will connect that roadmap plan, including the instrument timeline and the revenue outlook. Turning to broad scale, the fundamentals of the program are solid. Our 2nd quarter work reinforced the core premise that iterative mapping with trimer-based probes can decode the broad proteome, but that assay testing made clear that our current assay configuration does not yet deliver the performance we need on the timeline we had targeted. Therefore, we have concluded it will not support a 2027 general availability at our target specifications. The remaining work concentrates in 3 areas. The 1st is our probe library. We have more than enough performant probes to move forward, but we need to increase their diversity through affinity maturation and inherently long lead time activity.

The 2nd is the machine learning layer, which keeps improving as we feed it more on-platform data. The 3rd is the assay architecture behind our configuration change, where we are working with our partners to stabilize the new assay platform so that we can detect true positive binding events more reliably. We are advancing these work streams in parallel. I am not going to put a new timeline on broad scale today, but the underlying science is sound, and the program keeps moving forward even as the bulk of our development effort now goes to proteoforms. 1 critical area to discuss is how we fit into the world of AI for bio. The field is racing to apply AI to biology, but that work is only as good as the data underneath it. The genome is a blueprint, but proteins are the machines that carry out the work, and their functional state is what determines how a drug binds, whether it is toxic, and which patients respond. This is precisely the layer today's models are missing because the data has never existed at the resolution and scale a model needs.

We believe that the data that is needed is the data our platform produces. I'll leave it there for now, but it is a meaningful part of why the proteoform work excites me so much, well beyond any single assay. The world is desperate for differentiated data at scale. Before I hand it to Anna, let me place this in the broadest context I can. Every major advance in medicine has been unlocked by a new ability to read or write biology. Sequencing the genome gave us the foundation to identify genetic diseases faster than ever before. Our growing command of gene editing through tools like CRISPR has begun to deliver real relief from once intractable diseases. I believe the proteoform resolution that iterative mapping uniquely provides is the next of those key breakthroughs. And then over time, it will translate into meaningful advances in how we understand and treat human disease.

With that, I'll turn the call over to Anna.

Thanks, Parag. Let me start with the commercial and customer picture, and then I'll take you through the numbers, the resource shift, and our expectations for the coming quarters. Our early access program continued to broaden this quarter, although the number of active paying projects is still small. Our sales team, which now stands at 3 people, including our VP of Global Sales, and the number and quality of institutions in serious conversation with us has grown significantly. The sales team is in the field every day and they describe a level of enthusiasm and receptivity that they say they have not seen anywhere else in their careers. A word of caution on the near term. This is a new team running new sales cycles, and converting early interest into signed paying engagements will take time. Turning to revenue, which we are reporting for the 1st time this quarter. Total revenue was $0.2 million. The majority of that came from grant revenue from our Michael J. Fox Foundation-funded alpha-synuclein proteoform assay, with the remainder in service revenue from our 1st early access program project.

As a reminder, the grant revenue funds development work, whose costs run through our R&D expense. Our early access engagements are designed primarily to give key opinion leaders access to our platform through a services model, not to generate meaningful revenue or margin at this stage. In practice, these are proof of concept studies. Customers are kicking the tires today with the goal that these early evaluations grow into larger ongoing engagements over time. For the full year, we are maintaining a revenue guidance of approximately $0.5 million. Total operating expenses were $15.9 million for the 2nd quarter of 2026, a decrease of approximately 7% from the prior year period.

Research and development expenses were $9.6 million, down approximately 8% from the prior year period, driven primarily by lower laboratory spending, lower stock-based compensation, and lower facilities costs. Selling, general, and administrative expenses were $6.3 million, down approximately 6% from the prior year period, driven primarily by lower salaries and related benefits, reflecting reduced incentive compensation expectations for the year, and lower stock-based compensation. Net loss for the 2nd quarter of 2026 was $14.5 million or 11 cents earnings per share compared to a net loss of $15 million or 12 cents earnings per share in the prior year period. We continue to manage both operating expenses and cash prudently this quarter, and our results came in better than planned. In fact, we now expect full year operating expenses to come in below prior guidance, representing year-over-year growth of less than 10%. We ended the 2nd quarter with $129.2 million in cash equivalents and investments, compared to $143.4 million at the end of the 1st quarter, reflecting cash usage of approximately $14.2 million in the quarter. Based on our current trajectory, we believe our financial plan supports a cash runway that extends into the 1st quarter of 2028.

Let me put some numbers behind the resource shift Sujal and Parag described. In headcount terms, we are effectively tripling the number of people focused on our proteoform development efforts while reducing the broad scale team by roughly half. That shift shows up in our application-specific R&D effort, which was previously weighted heavily on the R&D team towards broad scale and is now roughly 2/3 proteoforms and 1/3 broad scale. The remainder of the R&D team works on elements of the platform common to every iterative mapping application, foundational work that benefits proteoforms and broad scale alike, and that portion of the team is unchanged. Importantly, we are accelerating proteoform content and capability development and de-risking our path to commercialization, all within our planned spend envelope. Let me also connect the roadmap Parag described to the financials. In the near term, revenue is expected to continue to come primarily from grant funding and early access program services.

On the platform, we remain on track to place a beta unit this year. From there, we expect to open the Voyager platform for pre-orders in early 2027, with shipments beginning in mid-2027. Time to align with the proteoform assay consumable releases Parag outlined. That is when platform revenue begins. The inflection point in instrument sales and consumables pull-through comes as our portfolio broadens through 2027 and into 2028. We'll refine that outlook as our portfolio and customer pipelines mature. Finally, on capital, our cash on hand is expected to support operations into the 1st quarter of 2028.

That said, we anticipate some level of fundraising between now and mid-'27 to support our proteoform expansion and broader market development. We are evaluating a combination of debt and equity, and we intend to approach it in the most prudent way possible. To be clear though, we are not in a rush. We will raise when the combination of business catalysts and market conditions produces the best outcome for our company and our shareholders. Back to you, Sujal.

Thanks, Anna. Let me recap our priorities and why we believe this is the right strategic choice. We're putting the bulk of our resources behind proteoforms because that's where we can deliver unique value today. The message from our customers and the market is strong, and our plan is expected to expand our proteoform capability across more disease areas, more sample types, and more labs. We think this is also the fastest path to full commercialization. We believe that the science on proteoforms is largely behind us. What's left is execution, and that enables a more predictable timeline to general availability.

None of this diminishes broad scale. Measuring the entire proteome remains 1 of the large opportunities in our industry, and we intend to get there. We feel that the premise is sound, the remaining work is understood, and a focused team is staying on the hardest technical risks. What has changed is sequencing, not conviction. Proteoforms now, because the market is asking for them and we believe we can deliver them, broad scale when the technology is ready to deliver what customers need. We go into the 2nd half with a clear mandate and cash expected to last into 2028. Our focus from here is delivering a wave of new proteoform assays with expanded capabilities, working alongside key opinion leaders and early customers to generate data and biological insight that cannot be generated elsewhere and scaling our business in parallel.

We will keep you up to date as we go. Thank you for joining us today. And with that, we're happy to take your questions.

[Operator Instructions] Our first question comes from Dan Brennan with TD Cowen.

You've got 3 salespeople, $130 million in cash, and as you mentioned, like 7 quarters of cash, but you're looking to find the right time to raise. So just walk through how you guys titrate the ability to expand the teams necessary to drive the revenue traction you need in order to support the business. I'm just trying to understand. Anna mentioned some unlock events I think between now and mid-'27. Maybe can you just talk to a little bit about that pathway and kind of you know how you manage the burn versus the commercial opportunity.

Sure, maybe I'll tackle that, Dan. This is Sujal, and good morning to you. 1st and foremost, I think the way Anna and I think about this is making sure that the size of our commercial organization and those that are focused on talking to customers on a daily basis, making sure that team is right-sized for the serviceable opportunity that we have and being able to reach customers. 1 of the things, for example, that you see in our strategy is that the proteoforms that we are releasing today, even though they could be across oncology and neurodegenerative and cardiovascular and inflammatory disorders, it's concentrated in just 2 areas today. And that's to give us some efficiency in terms of who we're reaching out to, how we're going to market, what trade shows we're getting to. And so there's inherently efficiency built into this strategy to start with. And 2nd, beginning with the fact that the technology, this proteoform capability is so unique, what we're finding is that customers are very, very willing to have conversations to learn more about it.

And so we're pretty comfortable right now with the team that we have. And just so you have a full sense of what that team looks like, I mean, there's [ Amber Faust ], who's our VP of Global Sales. There's a roughly East-West type of sales rep leader on each side of the country. And then as well, we have a couple of folks in scientific engagement and scientific affairs who are out interfacing with customers on a daily basis as well. We feel very comfortable that that core nucleus is good for the neurodegeneration work we're doing with tau and with the early work that we're doing on oncology. It's not my expectation that we'll add to that this year, but certainly next year, I think we'll get to the point where the business will have grown to the point where it'll demand adding some sales capability.

Okay. Could you elaborate a bit on the uniqueness of the approach in cancer and neurology versus existing approaches? So you're saying you're going to see this pull from these customers because it's so unique and different, so maybe just elaborate a bit on just the key performance metrics about the platforms that are out there today doing this and then the economics to the instrument cost, the assay cost. I know you know as you look to launch in '27 I think the instrument was a $1 million instrument. Just wondering like how that you know kind of how the profile on the economics for customers will look.

So, maybe Parag will take the 1st half of that question and then I'll dive in on the.

Yes, absolutely. I think 1 of the critical aspects to think about, Dan, is that there is no other platform in the world that can measure proteoforms at scale. Full stop. The ability to discern a combination of an isoform plus multiple post-translational modifications is an attribute that is unique to our platform and our platform alone. And so we've heard from customers things like, literally, I have always wanted to be able to measure that. I believe this is critical to understanding how signaling works, what therapeutics are likely to work, what patients are like need to be targeted by looking at that combination of isoform and post-translation modifications together. And so that is an incredibly differentiated data type because we are literally the only platform in the world that can make the measurement at scale. And so when you start applying that to critical therapeutic targets, AKT1 being the 1 we're starting with, and then moving, as we mentioned, to other high priority targets, that this is something that from the customer side, they recognize immediately that this is an important measurement and something that they believe is critical to the core biological processes. And as a contrast, the existing players out there, either targeted or more broad scale, are focused dominantly on singular measurements, so antibody assays, measurements of total protein going up and down, and they lack this additional layer of detail that confers so much specificity to the measurement.

Thanks, Parag. Dan, to answer the 2nd half of your question, the feedback that we have heard from customers through a few different market research studies that we've conducted and a formal content analysis on pricing show that the platform's capabilities even with just the proteoform content, as long as there are sufficient panels to have an instrument busy, it supports the case for an instrument at roughly the $1 million price point, which is the price point that we have stated as our target and it continues to be our target. As we open the instrument and platform for pre-orders at the beginning of next year, before that we will announce our final pricing, so it might move up or down a little, but roughly a $1 million deal is what we expect for the instrument. And then, as we've previously said, depending on the assay and the target and so forth, the pricing might vary a little bit for the price per sample, but roughly a few thousand dollars a sample for kits for the platform.

Maybe I'm going to sneak in 1 of the, so how do we think about therefore you're focusing on the AKT1, it's a $1 million instrument. Could you get 10 customers next year, just any way to think about just given the cash and the burn and just trying to think about what the revenue opportunity could look like as you launch commercially and how investors get comfortable with that burn? Obviously if the revenue start to accelerate you know it gives people some confidence just kind of any anything you can help with a funnel I had to think about the early traction that you might be able to achieve over the 1st couple years with your 1st targeted assays.

Yes, I think the way to think about that, I wouldn't necessarily kind of answer a question of how many customers or so forth. What I will say is if you go back through the remarks that Parag made in terms of the rollout of these different assays and as well for you and for investors, when we update our investor presentation and our SEC filings by end of October, day to day after market close. You'll also find a visual of our timeline. What you'll see is where we are with our tau assay, which we expect to have in general availability with the instrument launch, AKT1 as well. You'll see oncology proteoforms 2 and 3, which are slated for the middle of the year lined up with platform launch, and then slightly after for general availability for the 3rd. We've previously said that the ones we're working on today in development are AKT1, p53, and EGFR, so those are likely to be the 3 in oncology. From that point, you also see that as we move forward, that we continue to add proteoform assays, and on that chart you'll see us go through 5, 6, 7, 8, 9, 10 and so forth.

So there's a lot of content there. And then as well on that slide what you'll see is something Parag talked about in his opening remarks, which is that we have a set of enhancements to these assays, some enhancements that affect all the assays, some that are assay-specific, that enable us to introduce new sample types like cerebrospinal fluid for tau, that enable us to have lower sample input so we can support blood and oncology, and those types of advances are slated to be introduced on a steady schedule as well. When you take all of those together, we think that is a substantial commercial opportunity. And so for us, when you ask how many customers, I think that we're going to have plenty of customers on early access and I'm excited about that. I also think that we're going to have enough content to start to drive instrument demand. And, you know, with a roughly $1 million deal, that's the biggest lever on the top line in the near term. I'm not going to put a size and shape around that opportunity. But as we start to get into next year, I think we'll have more for you.

But, you know, in total, I think it's an exciting opportunity. It's just a little too early for us to put numbers around it.

Our next question comes from Subbu Nambi with Guggenheim.

This is Thomas on for Subbu. Maybe just to pick up there on pre-orders, other peers have noted academic markets appear to be largely stabilized. Curious the latest you've seen in that end market and just the confidence you have in customers having the funds to commit to pre-orders for full price instrumentation towards the end of this year and into next. Thanks.

Maybe I'll take that 1, Thomas. Let's 1st kind of separate the customers in the U.S. and North America more broadly. In the biopharma space where we are less active today but expect that we will begin to grow our book of business as we start to move these products through our roadmap, I think that what we've seen in conversations is that budgets are stable, that they're not affected by any external forces, and I think that some of the early results that we've seen out of the Dx and tools space and the larger caps have supported that. And that's what we're seeing as well. On the academic nonprofit research side where NIH funding and government funding is a significant factor, I think that what I've said before is probably what we're seeing now, which is that there's still a little bit of choppiness out there where, oh, I was expecting this much, but I only got that much. I think this is coming but it's a little delayed. But that choppiness is probably improving a little bit. And as well, as we think about the types of customers that we're going after on the academic side, there certainly is NIH dollars.

There are NIH dollars that are going into funding those projects for our customers. And we're continuing to see that they're getting funded, that they're having dollars available. And so I think that I'd say that that funding climate is improving a little bit, and we'll see how it is as we start to head into next year.

Great. And then maybe just to follow up on the revenue this year. Just curious what the split is for the 2nd half in terms of grant revenue, revenue from Michael J. Fox and then just what you can expect from the services side as well.

Sure, Thomas, I can speak to that. As you heard us say, we reported our 1st revenue with Michael J. Fox this quarter. That was the primary driver of revenue. And now that work is underway, I would anticipate that we would see fairly steady revenue coming from that, those efforts through 2026 or into 2027. Although the amounts might vary a little bit depending on the type of work that's being done in any particular quarter. We do have a sales team now and they're engaging with customers every day. In that case, I would expect some additional early access customers, although I don't anticipate that to be a major driver of revenue this year.

Thomas, 1 of the things I do want to add to that, just to point out so that you think about it from a modeling perspective and we think about our top line. Today, our sales team is doing early market activities around oncology, but largely they're out selling the tau assay. The tau assay today only supports brain tissue as a sample type. And brain tissue is a fairly rare sample in neurodegeneration research. And so, you know, roughly 9 out of 10 of those conversations is, holy mackerel, this is amazing technology. Do you support CSF or blood? And the answer is it's coming soon. So that's 9 out of 10 of our sales cycles. With oncology, the prevalence of tissue samples is much more normal, much more common, and the market size is larger.

So we think that in the near term, that puts oncology at 5 to 10 times the size to neurodegeneration not because of raw market size but because of sample types that we support. And we expect that enabling biofluids in oncology will be a little bit easier than neurodegeneration which is what Parag said that CSF support for neurodegeneration for tau specifically is something we expect in 2028, and for oncology we expect to be able to reach there earlier. And you'll see all of that on our roadmap, which will be in our filings at the end of the day today. With that, I would think about it as AKT1 being a significant unlock of serviceable opportunity for us, and so if that early access comes here, this year, as we start to enter the beginning of next year, I think that you'll start seeing the oncology business ramping significantly faster than neurodegeneration just because of the way that the various sample types supported rollout on our roadmap.

Super helpful. Thank you, guys.

[Operator Instructions] I'm not showing any further questions at this time. And as such, this does conclude today's presentation. We thank you for your participation. You may now disconnect and have a wonderful day.

Good day, and thank you for standing by. Welcome to the Nautilus Biotechnology First Quarter 2026 Conference Call.

[Operator Instructions]

Please be advised that today's conference is being recorded. I would now like to hand the conference over to our first speaker today, Ji-Yon Yi, Investor Relations. Please go ahead.

Thank you. Earlier today, Nautilus Biotechnology released financial results for the quarter ended March 31, 2026. If you haven't received this news release or if you'd like to be added to the company's distribution list, please send an email to [email protected]. Joining me today from Nautilus are Sujal Patel, Co-Founder and CEO; Parag Mallick, Co-Founder and Chief Scientist; and Anna Mowry, Chief Financial Officer. Before we begin, I'd like to remind you that management will make statements during this call that are forward-looking 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 in the press release Nautilus issued today. Except as required by law, Nautilus disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward-looking statements, whether because of new information, future events or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast on April 28, 2026. With that, I'll turn the call over to Sujal.

Thanks, Ji-Yon, and thank you all for joining us today. Before turning to the quarter, I'd like to begin by recapping the Q1 announcements we highlighted on our last earnings call. At that time, we discussed the launch of our Iterative Mapping Early Access Program in January, the debut of the Voyager platform to the proteomics community at US HUPO in St. Louis, Missouri, and our announcement of a collaboration with the Michael J. Fox Foundation and Weill Cornell Medicine-Qatar to advance development of an alpha-synuclein proteoform assay for Parkinson's disease.

We also highlighted our progress moving into the later stages of our broadscale assay configuration change and our plans to make 2026 a pivotal year focused on commercialization. We also outlined a series of key milestones for 2026, including progressing early access customers into active tau services projects, expanding early access in the second half of the year to include a second proteoform assay focused on an oncology target, introducing broadscale capabilities into early access later in 2026 and placing Voyager instruments externally through beta deployments. We also said we expect to initiate our commercial launch in late 2026 by opening the platform for preorders with customer installations beginning in early 2027. This would be followed by general availability of broadscale capabilities in the first half of 2027.

This quarter, I'm pleased to say we are executing well against that road map. Today, we'll discuss the meaningful steps we've taken toward commercialization, including building out our commercial team and growing customer engagement in the early access program. We'll also cover the scientific and technical progress we've made across our Iterative Mapping assay portfolio as well as how we continue to manage our resources prudently while investing in the opportunities ahead. A key priority for 2026 has been building the commercial organization needed to support launch activities. During the quarter, we welcomed Amber Faust as our VP of Global Sales, and we have since hired 2 additional sales team members. These are experienced industry veterans thoughtfully selected for their expertise and commitment to the field of proteomics, and we're excited about the depth of expertise they bring.

With this team in place, we believe we are well positioned to engage prospective customers ahead of our commercial launch. Building on the successful launch of our Iterative Mapping Early Access Program in January, we're pleased to report growing momentum in customer interest for the Tau assay and for custom assay development. Inbound interest has been steady and broad-based, spanning academic centers, nonprofit research institutions and biopharma organizations. Today, we're excited to reiterate that last month, we announced our first named EAP customer, Baylor College of Medicine. Combined with our existing collaborations, we're pleased to be working with several academic institutions with deep expertise in proteomics and disease research.

This is a meaningful milestone. We believe that it reflects the excitement top-tier institutions are placing in the Voyager platform and marks an important step in translating our development progress into active real-world scientific partnerships. While these early engagements are not intended to drive near-term revenue, they are designed to enable real biological discovery, support publications and grant applications and ensure our workflows and data outputs align closely with customer needs. Importantly, we are beginning to receive requests to expand similar offerings into oncology-focused targets as well.

What has been particularly encouraging is the quality of customer engagement we are observing. Researchers are increasingly recognizing how Nautilus' single molecule analysis of proteoforms and proteoms produces unique and highly differentiated data. We view this data as critically important across a variety of biological questions and also as a powerful foundation for training next-generation AI models. Taken together, we believe these developments represent meaningful steps towards commercialization and reinforce our confidence that we have a highly differentiated platform and are addressing important unmet needs in the market.

On the technology front, we continue to make progress advancing the core Voyager platform designed to execute a diverse family of Iterative Mapping-based assays. On the targeted proteoform assay front, we moved forward with our oncology proteoform target down selection process, narrowing our focus to the highest priority candidates for our next Early Access Program expansion. On the broadscale front, we continue to advance our assay configuration changes and improve assay performance. Parag will walk through these technical updates in more depth. With that, I'll turn the call over to Parag.

Thanks, Sujal. Overall, Q1 was a productive quarter for our product and scientific teams. From the Voyager platform development perspective, we made meaningful progress across our assay portfolio. In addition, we gained greater clarity on the remaining work required to reach our next assay development milestones. Critically, we are also increasingly applying the platform to generate biological insights not accessible to existing proteomics technologies, which drives enthusiasm and engagement from the scientific community.

In addition to our ongoing platform and assay development activities, we continue to advance exciting studies with our collaborators. These studies highlight the unique insights enabled by Iterative Mapping and by the Voyager platform. During Q1, we continued supporting the Buck Institute for Research on Aging and the Allen Institute for Brain Science as they advance findings towards publication. We believe that these projects have generated the most extensive and quantitative view of the Tau proteoform landscape to date. These studies now span multiple genetic risk factors, brain regions and disease severities, clearly demonstrating that Iterative Mapping can reveal biology beyond the reach of conventional proteomics.

Taken together, these studies show that our data is not only technically robust, but biologically meaningful. We believe this new class of proteoform level information can deepen understanding of disease mechanisms, uncover novel therapeutic targets and enable more precise biomarkers, ultimately helping improve drug discovery and development. Among the most exciting results were findings from the Buck Institute performed with the Alpha instrument at their site. They specifically examined the relationship between the gene ApoE, which is strongly associated with risk of early onset Alzheimer's disease and proteoforms of Tau.

The specific linkage between ApoE and Tau was previously intractable to study. The Buck Institute's data revealed for the first time distinctive proteoform distributions associated with ApoE mutations. We look forward to them sharing their findings in a forthcoming manuscript submission. Progress on Proteoform assays was strong in Q1. During the quarter, we formalized our service lab capability to process customer samples, an important operational milestone as we support the Iterative Mapping Early Access Program. Underpinning this milestone, we completed a formal verification and validation study of the service lab and also standardized our customer-facing data and results packages so that researchers receive consistent publication quality outputs.

The assay as performed within our service lab passed verification, demonstrating that it met our requirements for accuracy, dynamic range, reproducibility and stability. We look forward to sharing initial biological findings from our early access program engagements in future quarters. In parallel, we advanced our alpha-synuclein proteoform program under the Michael J. Fox Foundation funded collaboration with Weill Cornell Medicine-Qatar. During Q1, we made early progress on assay development using commercially available affinity reagents. Although custom reagent development from our Weill Cornell collaborators experienced delays related to the ongoing conflict in the Middle East, we progressed the assay with commercially available reagents and will incorporate collaborator developed reagents as they become available.

Despite this timing shift, the program is on track scientifically, and we view this collaboration as an important opportunity to further demonstrate the breadth of Iterative Mapping beyond Tau. While much of our current momentum is in neurodegeneration, it's important to emphasize that Iterative Mapping is a highly general approach and not limited to neuroscience. We see meaningful long-term potential across oncology, immunology, cardiology and beyond. In Q1, we made meaningful progress on our oncology proteoform down selection process. After evaluating multiple candidate proteins across key oncology indications, we have narrowed our focus to a prioritized set of targets that we believe offer the strongest combination of biological relevance, assay feasibility and customer interest.

Examples of proteins we are examining for developing proteoform assays include EGFR, AKT1 and p53. Proteins like these have been prioritized from a larger field of candidates because they represent a wide spectrum of proteoform complexity that is clearly connected to disease processes of interest in pharma and across biomedical research. Critically, they are among the most clinically relevant signaling proteins in cancer biology. EGFR is a well-validated oncology target with numerous approved therapies and known resistance driving proteoforms. AKT1 sits at the nexus of the PI3K mTOR pathway and is implicated in a broad range of tumor types with multiple emerging therapeutics. And p53 is the most frequently mutated gene in human cancer. Across each of these targets, proteoform level resolution is essential to developing next-generation therapies, targeting and optimizing existing therapies and generally accelerating drug development pipelines.

Given our progress in Q1, we believe we are on target for having one oncology-focused proteoform assay enter early access in the second half of 2026, consistent with the time line we have communicated. We believe oncology represents a compelling next market opportunity, providing access to a broader customer base while also aligning well with the capabilities of the Voyager platform to deliver proteoform level resolution and highly reproducible measurement in complex biological systems. In summary, we have made significant progress on both transitioning our existing Iterative Mapping-based proteoform assay to a commercial offering and expanding the portfolio.

This quarter also saw good progress on advancing our Iterative Mapping assay for broad-scale proteome analysis. As a reminder, the core components of the Voyager platform are assay agnostic, relying upon the same instrument and software stack. The primary differences between the assays are in the consumables. Consequently, advances in the maturity of targeted proteoform assays carry over to supporting broadscale assays. This quarter, we saw advances in key components of our broadscale assay configuration, including in our flow cells, surface chemistry and computational models that are expected to form the basis of our launch configuration. We have seen performance improvements with each iteration and side-by-side comparisons of our new assay configuration versus the prior configuration show meaningful gains in critical areas, including our ability to increase the percentage of our affinity reagent catalog that is compatible with our assay configuration.

In previous quarters, we have mentioned that we were concurrently iterating our assay configuration alongside testing a large portion of our affinity reagent catalog on new configurations towards the goal of increasing the percentage of our catalog that is compatible with our assay configuration. Concretely, our current catalog consists of thousands of probes that have been shown to bind to trimer epitope targets. However, this is the first step in a rigorous characterization process that includes verifying probes bind in a given assay configuration with strong differentiation between on-target and off-target binding in a single molecule context. In addition, extensive profiling is performed to define models for which epitopes each probe recognizes. We require each of these criteria to declare a probe to be assay compatible.

In Q1, we nearly tripled the number of probes that have been qualified as compatible. The major driver of this increase has been the newer assay configurations and our work testing a larger portion of the catalog through these configurations. Outside of these studies, we also achieved our largest number of high-cycle decode experiments to date. Furthermore, we have been continually stepping up the complexity of our sample inputs and are now routinely including lysate mixtures and full lysates in our large-scale experiments.

Additionally, we are now actively developing a validation pipeline for single molecule identifications, an important commitment to scientific rigor. Because the Voyager platform may identify proteins at levels not previously observable, we are focused on ensuring we have robust methods to validate those identifications and benchmark them against orthogonal analysis methods. We expect to provide further updates as this work progresses through the year. Overall, we believe the progress this quarter reflects maturation of the Voyager platform across both commercial-ready targeted applications and next-generation broadscale capabilities. With that, I'll turn the call over to Anna to review our financials.

Thanks, Parag. Turning to our financial update. We continue to demonstrate prudent management of both operating expenses and cash, and we remain on track or better against the full year guidance we previously provided. Total operating expenses were $16.1 million for the first quarter of 2026, a decrease of 14% from the prior year period. Research and development expenses were $9.7 million for the first quarter of 2026, a decrease of 16% from the prior year period. This decrease was driven primarily by a $1.0 million decrease in salaries and related benefits related to the reduction in force implemented in the first quarter of 2025, with the remaining portion coming from reduced development costs, lower facilities costs and lower stock compensation expense.

General and administrative expenses were $6.4 million for the first quarter of 2026, a decrease of 12% from the prior year period. The decrease was primarily due to a $0.6 million decrease in stock-based compensation expense, along with a $0.3 million decrease in salaries and related benefits. We ended the first quarter of 2026 with $143.4 million in cash, cash equivalents and investments. Cash burn in Q1 2026 was $12.8 million, which benefited from lower spend overall and $1.1 million in cash generated from stock option exercises.

Based on our current trajectory, we still believe our financial plan supports a cash runway that extends through 2027. With respect to revenue, recognition associated with the Michael J. Fox Foundation grant has moved more slowly than originally anticipated due to delays related to the ongoing conflict in the Middle East. However, we continue to expect approximately $0.5 million in total revenue for the year, with a greater portion now shifting into later quarters. Overall, we remain confident in our financial plan and believe our capital position supports execution against our strategic milestones. Back to you, Sujal.

Thanks, Anna. To close, this quarter represented another period of solid execution against the plan we laid out for 2026. We're making meaningful progress towards commercial launch through the build-out of our commercial team, growing our Iterative Mapping Early Access Program customer engagement and improving market awareness. At the same time, we're advancing the Voyager platform performance overall, improving the science behind both our targeted and broad-scale offerings and expanding the proteoform portfolio into additional disease areas such as oncology.

We remain focused on the milestones we previously described for 2026 and believe the work completed this quarter keeps us on a strong path toward launch readiness. I'm proud of what the team has accomplished and grateful to our collaborators, customers and shareholders for their ongoing support. Thank you for joining us today. With that, we'll be happy to take your questions. Operator?

[Operator Instructions]

Our first question comes from the line of Subbu Nambi from Guggenheim.

My first question is how many customers are actively submitting samples through tau early access today? And what's the sample throughput being like?

This is Sujal. So to answer your question, so the only launch EAP customer that we've announced so far is Baylor College of Medicine. But the EAP pipeline, the service offering is being used for a number of collaborator samples. And Parag can comment on a few of those names that he had mentioned in the prepared remarks.

Absolutely. So I think amongst continued work with the Allen Institute, the Neural Stem Cell Institute and others are actively ongoing.

Perfect. Beyond Buck, Allen and Baylor, how many active engagements do you have in the pipeline right now? You mentioned you have exposure or interest from both academic, nonprofit and pharma, but I was just wondering about the mix there.

Yes. What I would say is that -- so one, it's important to recognize that Amber Faust, our VP of Global Sales, just joined us, I think, just about 2 months ago here. And we have 2 additional members in the sales organization. So a team of 3. That team came together last Monday and yesterday. And so it's still very early in the development of our commercial sales organization, but we're really excited to have what we consider to be a full team right now.

As we are beginning to prospect for customers for the Tau Early Access Program and as well starting to build the early pipeline, for our oncology targets. The sales cycles are a little bit different between academic and pharma. We've got a few very engaged on the academic side that are very interested in moving forward on the tau side of things. And we're just starting to see some really interesting and compelling activity from pharma, and we're looking forward to the sales team that's just been hired to pick up those engagements and start to build that pipeline further as we move through the year with tau early access and as we enter early access for our oncology proteoform in the second half of the year.

Super helpful. And I know this is all early, but just trying to get a sense of early engagement -- my last question, when a pharma company evaluates the Nautilus technology, what's the typical diligence process look like? Are they asking for a head-to-head comparison against any existing solution? Or are they evaluating this as a net new capability?

Yes. Parag, do you want to take this one and then I can add some color.

Absolutely. I think one of the things that we're seeing very clearly is that it's incredibly apparent to people that our platform is hugely differentiated relative to existing platforms, both mass spectrometry and typical affinity-based platforms. And so oftentimes, the conversations really are about the diligence is them looking through our submitted manuscripts, asking us many technical questions, really digging into how the technology works and the data that we've generated so far. There is significantly less interest in head-to-heads, I would say, because it's clear that the data that we generate is very different than the data that comes out of existing platforms.

Yes. And this is Sujal. Just to add one comment to put a fine point on this. I think having been at US HUPO myself in the last quarter and talking to a lot of prospective customers and KOLs, I think that the thing that's most exciting for the folks that I talk to is that the data that we generate with this Tau proteoform assay and that we will generate with our future proteoform assays is data that isn't reasonably collectible with any other method on the planet. There's no other way to gather this data.

And so what that gives us is it gives us a very unique conversation and a very powerful conversation to have with the customer, which is very different from other newer entrants in the Dx and tool space where they come in with technology that might be cheaper, it might be higher performing. This is net new biological insights that the world hasn't seen that increasingly, as we look at our collaborators' work seems to be incredibly relevant to disease pathology and incredibly relevant to human health.

Our next call comes from the line of Dan Brennan of TD Cowen.

This is Kyle on for Dan. I just want to start maybe on the oncology side. I guess, what's the reception been so far on oncology samples? And is Baylor ready to run them on site?

Great. Well, so as I kind of mentioned, the reception from potential customers to the EAP program capabilities, tau assay capabilities has been really incredible. If you'll recall, today, we have a tau services offering. That means customer sends us a sample, we analyze it in our facility, and we send back a standardized report package to the customer. And as Parag mentioned in the prepared remarks, that is the service offering that has now fully completed verification and validation and the first set of official EAP customer samples that will go through, i.e., not including our collaborators, which are already going through will be the Baylor College of Medicine, which will happen shortly.

You'll also recall, not from this earnings call, but from previous ones that we have one alpha unit that's been in the field for approximately a year, maybe a little bit over a year. That alpha unit is physically in the lab at the Buck Institute for Research on Aging. And so when the Buck generates data, the Buck is generating on their own instrument, all of the other engagements for early access will be through our service offering until we reach the second half of the year, where we do expect in late Q3 and Q4 to begin placing a few beta units with additional customers to prove out the on-site capabilities, the kits, the shipping and work through final bits of feedback ahead of a planned commercial launch as we hit the end of the year with first instrument availability and shipping in the beginning of next year.

Got it. And then maybe just on the broadscale assay configuration. It sounds like it's progressing well there, but are there any technical hurdles that you still have to overcome before it's ready for launch?

Maybe I'll take this one, Dan. I think as we've messaged and you're correct in your assessment, we have definitely made tremendous progress on that assay configuration and the set of iterations of configurations that we've been working through. In addition, we've made tremendous progress on characterizing the library and how it is performing in these iterations of the configuration.

In terms of technical work, I think as we went through with the tau service offering, once we had the assay up and running and stable and we're very happy with its performance, we then went through an incredibly rigorous verification and validation process as well. And so as we look forward, that's really the work that we're looking forward to is getting to a place where we are happy with the performance characteristics of the assay and then have done the full suite of verification and validation before we place it in customers' hands.

Thank you very much. This concludes our question-and-answer session. At this time, thank you for your participation in today's conference, and this does conclude our program. You may now disconnect.

Good morning. Dan Brennan, TD Cowen, Life Science Tools & Diagnostics Analyst. Day 1 of the 46th Annual TD Cowen Healthcare Conference. Pleased to be joined here on the stage with Co-Founder and CEO of Nautilus, Sujal Patel. So Sujal, welcome, and thank you.

Thanks, Dan, and I appreciate the invite to the conference.

Terrific. And we have Anna Mowry in the audience, the Chief Financial Officer.

So maybe just to start off, the zooming really far out, and then we'll go into your progress on technology. I thought it would be interesting to understand from your perspective, where Nautilus fits into the proteomics ecosystem, if you will. What do you consider some of the differentiators or things you're trying to solve for, if you will?

Great. Well, that's a good place to kick off. Maybe I'll take a second and back up because I don't know how familiar the audience necessarily is with the proteomic space. One of the things -- just in the story form, one of the things humanity has conquered in the last couple of decades is we've conquered measuring the genome. I can take a drop of your blood, I can tell you what 99.9% of your DNA is. It's accurate, reproducible, it's fast and cheap. The problem is your DNA doesn't really change from the day you're born to the day you die. It doesn't contain the real-time state of what's going on in your body. And because of that, it has limited utility in therapeutic development in precision medicine.

Us as an example, 95% of our FDA-approved drugs target proteins, not genes. And so measuring proteins is the next frontier. Proteins do all of the work in your body. They make up the vast majority of the functional parts of your cell. And we, as a scientific community, do not understand proteins very well. Proteins have a lot of complexity. There's 20,000 different gene encoded proteins. We don't have good instrumentation that can measure all those proteins sensitively and sample and reproducibly. And then more complex than that is that once a protein comes out and it's transcribed and it's in your body, it gets modified by lots of different chemical processes, picking up modifications in different forms. And if you don't understand those forms, you don't understand biology well.

Nautilus is a company that is trying to develop a brand-new platform to comprehensively measure proteins in sample. That is, what is the gene encoded protein, how is it modified? And we're using an approach that is an approach that's developed by my Co-Founder, Parag Mallick, who is Stanford faculty and is a very unique and different approach that hasn't been tried before. And I'm sure as we continue our conversation, we'll get into it. Nautilus itself is about 9 years old, and we are in the process of building a benchtop instrument that delivers easy-to-use proteomics to any biologist who wants to measure the proteome comprehensively from a sample. That's very different from the state-of-the-art in the proteomics space.

The gold standard in proteomics is a complex workflow that sits in front of the mass spectrometer, which is an instrument that is used all over in metallurgical analysis, food safety, chemical purity, but it's used in this proteomics use case using a complex set of preparation steps ahead of it. We sell billions of dollars of mass specs every year into these protein discovery environments, yet that tool doesn't really provide reproducible comprehensive results. And we're out to build this platform that comprehensively measures the proteome.

Terrific. So maybe next, and we can keep going down that vernacular, if you will. So what proteomic applications will the platform enable or unlock today, both on the proteoform side and then on really the broadscale proteome side that maybe aren't possible. So again, speaking to you kind of alluded to some of the drawbacks, but maybe go one level deeper of kind of what you'll seek to do with both of these technologies?

Yes. Let me discuss -- you use the word applications. Let me discuss the word applications in 2 different ways. One, I'll describe our applications, which you mentioned, right. Broadscale, which is what we call comprehensively measuring all the genic proteins in a sample or proteoforms, which is a specific use case. Those are cases [indiscernible] customers have their own use cases for [indiscernible]. Proteomics is used in a wide variety of drug development process upfront to take cells that are healthy, take cells that are sick, you want to understand it in a significant level of detail, what are the differences between them, what cell surface proteins are potentially biomarkers that are indicative of disease, what are my potential targets which I might be able to drug to have a positive impact on a disease? That target identification step and understanding what's going on, that step is already significantly hamstrung by existing technologies, which can't see all of those biomarkers sensitively. They can't see the rare things that are differentiating healthy and sick cells.

Next stage of drug development. Once I've got compounds, there's a lot of work that goes into understanding the mechanism of action of those compounds. What are the effects on the proteins in the cell when exposed to a compound? What are the secondary effects on other organs in the body, so toxicity, cross-reactivity types of applications? These are all very critical steps upfront in drug development that would have a massive impact, hopefully, positively, if you could use a platform like ours, to dramatically reduce the cost and efficacy of that drug development process.

In diagnostics, that same sort of use case exists, right? How do I find a sensitive biomarker that's going to be indicative of disease or stage of disease? How can I monitor therapeutic response by looking at what's going on inside of the patient's proteins. All of these types of applications are significant applications that our customers have identified as pain points because existing technologies are not adequate.

So when you think about what our technology does to map on top of that, right, the primary thing that our customers want to do in a lot of these types of applications is understand. If I have a sample, maybe it's 100 to 1,000 cells, it's like a standard sample size in pharma. I want to understand what are all the proteins in here and what are the proteins and how do they change as different disease states are present. That primary use case is what we call broadscale. And our value proposition in that use case is that we have an instrument that's far more sensitive, that's far more reproducible than what's out there today, which means that you have more actionable results, and the results coming off our system are more comprehensive. The mass spectrometer-based workflows and the other types of products that exist in the market, they still really can't effectively see more than maybe 1/3 to 1/2 of proteins that are in the sample. They can't see [indiscernible] its detection threshold. You see 100 to 1,000 molecules [indiscernible]. And these are critical questions in biology that we can [indiscernible].

The other application of our platform is one that we have begun to take to early access this year. And this is an application that helps to zero in on proteins of interest and look at the modification landscape of those proteins. And so for example, in early access this year, we launched our Tau assay, which is capable of measuring 768 different forms of one single protein, the tau protein. Tau protein is a critical protein to study in neurodegenerative diseases, like Alzheimer's disease. And we have an assay that is capable of measuring 768 different forms of it, which is revolutionary. No one has ever seen all those forms of tau. And no one has understood because they've never seen it. How is that related to your likelihood of getting Alzheimer's disease in the future, the disease progression? How is that related to the therapeutic programs that have been attempted. And how we might -- we'd be able to impact that. This proteoform use case is really interesting because the data that comes off of it has never been seen by the world. It's a use case that's a little different than broadscale.

Every protein I want to go after, I have to build a new assay, that takes us some period of time. We did announce on our earnings call last week that we have a second marker that we're working on in oncology. And then we announced earlier than that, that Michael J. Fox Foundation and Weill Cornell, Qatar, our collaborators and Michael J. Fox is funding an initiative to study alpha-synuclein, which is the key biomarker in Parkinson's disease, so another neurodegenerative marker.

And so we have more activity going on there as we build this portfolio of proteoforms. And we think in the long run, a single platform, which we showed for the first time last week to the scientific community, a single platform that we're going to release at the end of the year is capable of running all these proteoform assays and our broadscale assays in one single machine.

That's a lot. It is -- yes, if you're successful, it sounds like it's going to be quite exciting. Maybe just go back to U.S. HUPO. You presented some latest updates on the Nautilus platform, I think on the proteoform side. Just speak to some of the key takeaways from the presentations.

Yes, that's great. So HUPO is the Human Proteome Organization conference. They do it twice per year. They do World HUPO, which is generally international, and then they do a U.S. version of it. The U.S. version was last week in St. Louis. And it was a really exciting opportunity for Nautilus because for the first time, we showed the instrument to the scientific community. And so on the earnings call, what we talked about was that we have a number of proteoform assays that are moving through early access to general availability this year. We have an instrument that will reach launch by the end of the year, with generally available placements at the beginning of next year. And we announced that our broadscale capabilities, we expect to launch those in early access in the second half of this year, general availability, first half of next year.

So we've got a lot of things to talk about. Scientific community got to see our instrument for the first time, which was really exciting to demonstrate that. And it was a really important proof point because Nautilus is building something that is very difficult to build, very easy for the customer to use, but the task of building what we're building is very hard. And so for the scientific community, this was a massive tangible step where they see the instrument, they could use the touchscreen and operate it. I think at 4:30, there's a proteomics panel, Birgit Schilling, who's our PI at the Buck Institute and in the audience here, will be speaking.

Birgit was at our event and saw the instrument. Now she has had the instrument in her lab in alpha form. Buck Institute has the only alpha of our instrument since April of last year. And so she has lots of information that she'll share. And then as well, Birgit at U.S. HUPO presented some really exciting data using her biological samples and our instrumentation and her operators, generating interesting biological data. I'll save that data for her to talk about. But really exciting progress.

Okay. Maybe the data at HUPO, as you just mentioned, was proteoforms, I believe it was proteoforms of tau. And you kind of talked about kind of several new biomarkers, which may become available or in progress. Just could you speak -- and you've already alluded to one, but just how do we think about -- we're not putting the cart for the horse. How do we think about kind of how quickly you might come out with additional biomarkers on the platform?

Yes. So let's just like just separate those 2 use cases, right? So broadscale is a use case where we build it once and sell to everybody. Proteoforms, we're building assay by assay. And the criteria for building these assays today is, number one, an important biomarker where there's significant drug programs and drug development dollars behind it and an area where the forms of proteins likely have a difference in terms of the protein's function in the cell or its degradation or its distribution or any of the sorts of characteristics. So areas of interest are neurodegeneration, among a lot of other areas, neurodegeneration, oncology, autoimmune, inflammatory, cardiac.

And so what we've done is we've taken a set of 200 or 300 potential interesting markers. We've mapped on that availability from our partners for antibodies that target different site-specific modifications so that we don't have to build those today. And we've stack-ranked those. We probably have 20 that are kind of on our hit list. I mentioned that we're going to do an oncology marker next. We're actually -- like there's 5 markers that are all great markers. We don't actually even know yet which one we're going to do. We're going to test the antibodies and whichever one is the fastest path is the one that we're going to pick first, and then we'll probably tackle another oncology marker right behind it.

And from there between neurodegeneration and oncology, alpha-synuclein will come out the other side. And then we may move to another area. We may continue to double down on those 2 areas. But I think that when we think about this long term, we think about this as a steady road map of proteoform assays. And in the long run, we think that having a large portfolio of proteoform assays plus an instrument that does broadscale makes it a really compelling value proposition for the customer.

And in terms of the first tau, 700 different variations of it, what's been the early interest? I would think that's such a hot area, and there's an established understanding and awareness, and there's a lot of pharma companies and researchers chasing that. So I would think offering this, you would generate a lot of leads. Just any color you can provide on the funnel, what you've heard from customers on that front?

Yes, that's a great question. So once we've started to show this data, which we started showing in a preprint last year, Birgit presented data at World HUPO last year as well, which was very early data off the platform. There's been a tremendous amount of interest from the scientific community. Now a lot of that interest is in early research because this is data that no one's ever seen before. No one ever thought you could measure 768 proteoforms of tau.

There's been a raging debate for decades in the Alzheimer's disease research community, is the pathology of tau driven by random hyperphosphorylation, or is there a pattern of how kinases got you to particular forms? In our first data sets, we started to see evidence that there could be a pattern there. Like incredibly exciting, but it's going to take some time to develop, partially because some of these folks have to now apply for grants. Some early innovators like the Michael J. Fox Foundation saw what we're doing and said, "Hey, I have to jump on and do this for alpha-syn."

So it's beginning to build. But as a company, we've been running very capital efficiently. Up until today, there was not a single salesperson in the company. So we have one now. And so we're just now beginning to build that capacity. So building the funnel is basically from scratch at this point. And as well, I think, as I mentioned in the earnings call, we got to launching that Tau assay to early access a little earlier than expected as well because it's performing incredibly well. And so with that, we're a little behind on sales capacity, but we're just getting started on that. I think that this year, we'll see some of those early projects build, and then we're going to move those projects into grant proposals and further funding.

One of the things I do want to highlight, though, is that the move out of neurodegeneration to oncology is driven by the fact that we are in tau, not because we did some great market research study and said, "This is the best place to go first." We're here because we started working with Genentech 4 years ago, and they really wanted to study this, and it was a great joint learning experience for us. Tau might be a tiny step out of sync with where early drug program development is for the data that we're going to put out. But we think oncology is a really great fit for the type of data that we're going to get off of the platform and where drug development programs are that could be impacted by it.

And so I think I'm super excited about what's going on in neurodegeneration, but I'm maybe even incrementally more excited about oncology as we start to get through the second half of the year.

Can you just elaborate a little bit on that, like why you think the marriage between where the market is and what the technology enables, maybe oncology is even like a faster lane, if you will?

Yes. So I think that there's kind of 2 parts of it that I would highlight, right? One is that on the neurodegeneration side, these -- the disease biology is extremely complicated. And we don't yet have the capability to analyze biofluids, CSF, blood. We only are dealing with tissue samples. Tissue samples for a brain that's afflicted with AD, these patients died. And so samples are hard and getting an impact out of what we're doing is going to take a little bit more time, right?

In oncology, there is a belief in the scientific community, at least folks that I've talked to and that I know our team has talked to that the modification landscape and the proteoforms of some of these key markers is critical to understanding therapeutic response and biology of these diseases. And our system, this predominant sample type today that we're working with, is cells and tissue. That's an easy sample type to get from tumor biopsy. And so there's a lot of alignment on the sample side and a lot of alignment on the biology.

And then remember, if the sample is easy to get and we are able to understand the proteoform landscape in great detail. It's not just about drug development. It's understanding what therapy should I give the person based on what I'm seeing in terms of the proteoform that exists. Like these sort of precision medicine use cases, I think, are much more tangible earlier for us in oncology than in neurodegeneration.

And in terms of the platform, whether the proteoform or the broad scale, in terms of working with different matrices, is there any barrier towards working on different matrices over time? I mean, right now, you're in tissue, but how will that evolve you think?

Yes. I mean, so for our broadscale capabilities, we will have the capabilities to do cells and tissue. We'll have the capabilities to do blood. And then over time, those capabilities will get more and more complicated. Some customers want to do a preparation to only look at cell surface proteins. Some want to do some sample preparation, minimally on blood to reduce albumin or some of the proteins that are really abundant that take up space on an experiment that is unnecessary. So those -- that's the road map on the broadscale side.

On the proteoform side, every marker has a little bit of a different sample preparation associated with it. And so when we think about a product for tau, a product for oncology marker, number one, it's a combination of our assay and the sample preparation techniques that go and come together. And so for example, on tau, our internal team has developed a protocol for sample preparation from frozen tissue that enables us to analyze these proteoforms of tau. Birgit's lab at the Buck Institute has been using that protocol. For the oncology marker, we'll have a similar sample prep that's kind of bundled up with it.

I got it. Okay. So maybe one more on the proteoform side, and then we'll get kind of zoom out for the broadscale. But on the proteoform side, you mentioned how well the technology early on is working. Like how would you define -- I guess, even on the tau product, how would you define success? And we'll ask Birgit this later today. But like, what are the features? What are the measurements? Obviously, if there's new discoveries made, terrific. That will take years. But just analytically, like from a quantitation standpoint, maybe, what are the measurements that you'll -- the customers you think will look at to say, "Wow, this really is delivering what we thought, and it's very differentiated and unique."

Yes. Well, let's just address -- you said it your thing, but I'm just going to say it out loud, right? Ultimately, our job is to enable our customers to make discoveries and positively impact human health. And I don't know that will happen in tau. I don't know that will happen in the first oncology marker, but I am certain that out of the hundreds of markers that are out there, many of them will have relevant proteoforms that are significant discovery that positively impact human health. So that's our end goal. It's going to take years, yes, but that's the end goal.

One of the things that gave us a lot of comfort around this Tau assay was that we did a lot of validation studies, and we far exceeded our own metrics in terms of what we would want to get this thing into early access. First of all, if you look at the preprint that we had, we did a set of studies to build up to real biological samples, studying organoids, human -- mouse brains, looking at human control patients and AD afflicted patients. And when we did those analyses, one of the things that we saw was we saw incredibly, incredibly tight CVs, very little variation, high reproducibility in the samples. And when we did spike in studies that would take particular forms and increase their ratio and a mixture, we saw exquisitely accurate reproduction of what we expected coming in.

Just to give you a sense, if you looked at our preprint and looked at the variation in our data across different operators, different reagent lots, different instruments and different chips and flow cells. So change all the different things in our system, the variability is 5%. Our product management team when they were building the spec for this product set that at 25% because that's what everyone else can do. 25% is like a norm. And we accomplished 5%. It's the [ highest ] variation that you saw on the system. It gives us a ton of confidence that there's really great data quality coming off of the system. And for our customers, data quality is absolutely critical.

One of the things you see in proteomics from some other vendors is you see these 10,000, 20,000 cohort studies that are being done. A lot of the studies are done that way because the variation is so wide. You analyze the same sample twice and 30% of your IDs change, like you have to run a lot to go and get data. So if you could deliver more accurate data, it's really transformative to a customer. And that's the most exciting thing that I think not just I'm excited about, but as I was at HUPO last week and I talked to the scientific community, the things that they were excited about in our early results.

Terrific. So maybe just we have 6 minutes left. Maybe I'll ask one more, not big picture question, but talking about the broadscale discovery platform, which you've said throughout kind of the last year or 2 as we've followed the company, like that's really -- the proteoform is exciting, but the broadscale really is where you think the real massive opportunity is. So you've talked a lot about what are the milestones ahead of feeling good on that launch and now you've got that launch in the second half of the year. Just again, remind us in terms of what we need to see between then and now, what your level of confidence is on those time lines?

Yes. Let me just slightly modify your statement, and I'm going to tell you that, that broadscale, I believe, is the inflection point for our top line because it unlocks a sale that is looking for additive data to the mass spec-based traditional workflow in a similar price point, accessing a similar budget pool. We think that's the revenue inflection point. When I was at HUPO, 2/3 of the people I was there said, "I love what you're doing on broadscale, but oh my God, I love even more what you're doing on proteoforms" because this is data that is net new to the world, no one has seen before. So I think in the long run, the proteoform business, particularly when you combine the 2, is going to create an incredibly powerful and sticky business model for us. So that's kind of setting the stage.

In terms of broadscale, there has been a ton of complexity over the course of 9 years in getting to the point where we can get broadscale out in the marketplace. And at the beginning of 2025 on that first earnings call, one of the things that we said was, hey, we're going to need another year because we had to go through a pretty significant assay configuration change, which was focused on getting more of the reagents that we've -- proprietary reagents that we've been building to function correctly on the platform. And for those that have listened in on our story, you know that, that broadscale depends on us building a set of 3 -- maybe 350, 400 proprietary reagents that map each molecule.

And these affinity reagents are antibodies that we call multi-affinity probes. They bind very short regions of the protein in a nonspecific manner. It's a very specific class of antibodies that we have spent almost 9 years developing techniques to build. Not enough of those antibodies work on our platform. We have thousands of candidates, very little yield. And the reason was that the assay configuration needed to change to allow more of them to work. So we went through a hard process in 2025 that took a little longer than we'd like to get through that assay configuration change. And as Parag on the last 2 earnings call has talked about, we've begun to sort of move through validation steps in our new configuration.

We've been able to decode simple mixtures of proteins, 10 proteins, 15 proteins. We've been able to identify proteins that are present in cell lysate, and that's an important step. The next important step for us will be to be able to accurately quantify some reasonable number of proteins, 500, 1,000, 2,000 out of some complex sample like cell lysate. That's not an endpoint by any means, but our system combines these data points together computationally in an exponential manner.

So by the time that I have 2,000 or 3,000 proteins, 500 or 1,000 proteins, it doesn't matter what, more than half the work is done. The assay configuration change will have been done and stable. And we are using that marker as kind of the benchmark for which we will say, "Okay, we're ready to get the early access program announced for broadscale, start signing up customers." And by the time that we are ready to analyze the first sample, we'll have a greater number of proteins ready to go. And so that's an important milestone for us and through investor conversations, I know it's a milestone that a lot of investors are looking at as well because that shows the whole thing has come together.

So the goal of that or the plan for that, if there's a second half launch, second half could be December, it could be August, sometime between -- before August or December, we would see this announcement, I guess?

Those are good bookends, yes.

Okay. Just in terms of -- we have 2 minutes left. So how do you -- like how do investors contemplate then kind of the road map then for the company over the next couple of years? Like cash on the balance sheet. You're at this point. Maybe speak a little bit how much you spent to get here. And as you begin to unlock these opportunities, kind of what happens? How targeted do you go just to make sure things are on track? Like how quickly can you ramp? Things like that?

Yes. Yes. I mean you asked a question, how should investors think about it? I would take a more broad view, first of all, like I want investors to think about Nautilus as a company that is building something bold, hard and disruptive, right? And those are companies that when they succeed -- which I am confident we will. When they succeed, they have a transformative effect on markets, right? We're not an incremental sample prep system. We're not yet another assay that looks like Olink, which now Thermo Fisher owns.

We are a net new approach that's doing something very different. It takes a lot of capital and a lot of time to do that. And we have been very, very careful with our cash and our balance sheet and very careful with our development so that we have the capital on our balance sheet, which is there today. We ended with $156 million of cash at the end of last year. We have the capital that we need to finish building our broadscale capabilities, deliver on the entire road map I discussed earlier, build a commercial team and launch. We have capital, as we've stated through 2027, not into, but through 2027. And we have what we think is a good plan forward for capitalizing the business as we continue to grow and move towards cash flow positive after launch.

So that's kind of how I think about the important markers for investors.

Okay. Well, we've got just maybe a few seconds left here. So I mean, I don't know. How would you wrap it up in terms of -- we've talked about key milestones. We talked about products. We've just talked about kind of the future. How would you like to wrap up from here, the Nautilus story?

I mean I would just encourage investors who want to learn more to reach out to me, our IR team, Anna Mowry, our CFO, is in the audience. We'd love to talk to you about the company and count you among our shareholders. So thank you.

Terrific. Thank you, Sujal. You got it. Thanks for being here. Thank you.

Good day, and thank you for standing by. Welcome to the Nautilus Biotechnology Q4 2025 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, Ji-Yon Yi, Investor Relations. Please go ahead.

Thank you. Earlier today, Nautilus released financial results for the quarter ended December 31, 2025. If you haven't received this news release or if you'd like to be added to the company's distribution list, please send an e-mail to [email protected].

Joining me today from Nautilus are Sujal Patel, Co-Founder and CEO; Parag Mallick, Co-Founder and Chief Scientist; and Anna Mowry, Chief Financial Officer.

Before we begin, I'd like to remind you that management will make statements during this call that are forward-looking 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 in the press release Nautilus issued today. Except as required by law, Nautilus disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward-looking statements, whether because of new information, future events or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast on February 26, 2026.

With that, I'll turn the call over to Sujal.

Thanks, Ji-Yon, and thank you all for joining us today. Before turning to the quarter, I want to briefly remind everyone of what we're building and why we believe it matters.

Nautilus was founded to address a long-standing challenge in life sciences, the lack of technologies capable of comprehensively measuring the proteome with the sensitivity, scale and reproducibility needed to fully understand biology and disease. Our proprietary Iterative Mapping methodology is designed to analyze single intact protein molecules at scale and generate highly reproducible digital protein counts. This methodology is delivered through the Nautilus platform, an integrated system of instrumentation, consumables and software, which can support both broad-scale proteome analysis and targeted proteoform characterization on a single platform. Over time, we believe this data foundation will unlock new biological insight, integrate more effectively with other omics modalities, support next-generation AI-driven discovery in human health and medicine and ultimately help accelerate the development of new therapeutics and diagnostics.

With that context, Q4 marked a strong close to 2025 as we continue to make tangible progress towards commercialization, deepen external validation and build momentum with leading research institutions. A key highlight of that progress was our presence at the US Human Proteome Organization Conference, or US HUPO in St. Louis, Missouri this week, where we publicly unveiled the Nautilus Voyager instrument in dramatic fashion to a large audience of influential researchers and prospective future customers, providing the proteomics community with its first tangible view of the instrument we've been building.

The response was highly positive and reinforced the strong interest we're seeing from researchers seeking a new class of protein measurement technology. Importantly, when designing Voyager, we were intentional about creating an instrument that looked and felt different, one that conveyed sophistication and innovation while still being approachable and easy to use. We wanted an instrument that reflected the ambition of what we're building while also fitting naturally into modern research environments. And the feedback we received confirmed that this balance resonated strongly with the community.

Building on the capabilities of the Voyager instrument and supported by the encouraging tau data we've seen emerging from our early collaborators, we elected to launch our Early Access Program for Iterative Mapping in January earlier than previously communicated. This milestone represents a meaningful step in Nautilus' transition from development to active customer engagement, enabling partners to submit samples, receive data and provide feedback in a streamlined manner.

Initial customer response has been encouraging. And while these early engagements are not intended to drive near-term revenue, they are designed to enable real biological discovery, support publications and grant applications and ensure our workflows and data outputs align closely with customers' needs, an approach consistent with how many transformative life sciences platforms has successfully entered the market.

The Early Access Program will begin with our Tau proteoform assay and establish a foundation for future assay expansion covering additional proteoform targets and broad-scale applications.

Importantly, we believe this early access launch also reflects a forthcoming diversity of assays for our platform beyond tau. For example, in late January, we announced a collaboration with Weill Cornell Medicine-Qatar and The Michael J. Fox Foundation focused on alpha-synuclein proteoforms in Parkinson's disease. This MJFF-funded project, $1.6 million in total with $1.2 million coming to Nautilus, combines Professor Hilal Lashuel's deep expertise in neurodegeneration with Nautilus' ability to measure proteins and their functional variants at the single molecule resolution. Understanding alpha-synuclein proteoforms is a priority for MJFF, and we believe this collaboration is a strong example of how Iterative Mapping can be extended to additional high-value proteoform targets and disease areas over time.

On the technology front, we continue to make strong progress as we moved into the later stages of our broad-scale assay configuration change. This work is designed to better align with our expanding probe library and improve overall platform performance. We're now seeing the first data from the updated assay on new chips and early readouts are encouraging. Parag will walk through these technical details in more depth, and I'll return later to discuss how this progress informs our expectations for 2026.

Taken together, these developments reflect steady progress towards commercialization grounded in real samples, real data, real customer engagement and increasing external validation. Throughout 2025, we remain disciplined in how we invested our resources, meaningfully reducing expenses while continuing to advance our most important technical and strategic priorities. I want to recognize our scientific and engineering teams for their continued focus and execution.

With that, I'll turn the call over to Parag.

Thanks, Sujal. I'll now provide an update on our technology and product progress, including what we're learning from our development work and the external validation we're seeing through collaborations.

Overall, Q4 was a strong quarter of execution for our product and scientific teams. We continue to see growing validation of the Nautilus platform through both internal development and external partnerships. Importantly, we are increasingly moving beyond demonstrating that the technology works and towards applying it to obtain remarkable biological insights, not possible with existing proteomics approaches. This shift from capability to meaningful application is an important marker of platform maturity and a central focus for the team.

Collaborations continue to play a critical role in validating the platform and demonstrating real-world relevance. During the quarter, we completed work with the Buck Institute for Research on Aging, culminating in the presentation of novel tau biology at World HUPO and most recently at US HUPO, and we are now supporting our partners as they prepare their findings for publication.

In parallel, through our collaboration with the Allen Institute for Brain Science, we analyzed human brain samples spanning multiple brain regions, genetic backgrounds and disease severities. We believe this work represents the most comprehensive and quantitative Tau proteoforms landscape study to date. Notably, we are observing clear differences in Tau proteoforms patterns across disease severity and brain regions, signals that are not detectable using conventional proteomics approaches and that may help explain variability in disease progression and clinical outcomes. We also anticipate that such insights may be essential for developing the next generation of therapies for neurodegenerative diseases.

Stepping back, what stands out is that the data emerging from these collaborations is not only technically robust, but biologically compelling. With each additional study, we gained confidence that Iterative Mapping is enabling access to important biology that has remained out of reach for existing technologies. We believe this new class of proteoform level data has the potential to drive real-world impact by deepening our understanding of disease mechanisms, revealing new therapeutic targets and enabling the development of more precise biomarkers for diagnosis, patient stratification and treatment monitoring.

Ultimately, our goal is to demonstrate to the broader scientific community that this represents a transformative foundation of information, one that can help accelerate drug discovery workflows and improve the probability of success in developing new therapeutics.

From a platform development perspective, we made meaningful progress across both our broadscale assay and our proteoform assay portfolio, while also gaining greater clarity on the remaining work required to reach our next milestones.

Starting with the broadscale assay, we continued advancing our assay, including advancing the assay configuration change we have discussed previously and are now routinely employing our new configuration. During the quarter, we achieved several encouraging milestones, including performing our largest scale experiments to date, which demonstrated Iterative Mapping-based decoding of proteins from increasingly complex mixtures, including cell lysates.

In addition, we made good progress on hardening the fabrication process for our new flow cell configuration, and showing assay performance characteristics such as increased on-target binding that give us indications our new assay configuration will enable an expanded affinity reagent library. The work completed in Q4 helped validate key elements of the new configuration and clarify the primary levers needed to drive further performance improvements as we scale towards complex biological samples.

Progress on Proteoform assays remains strong. The Tau Proteoform assay continues to track as our first early access offering, and we remain on schedule to begin processing samples through the Early Access Program by the end of Q1. Verification and validation activities are largely complete, and the assay is meeting our requirements for accuracy, dynamic range, reproducibility and stability, marking an important step as we transition tau from development into a high-quality commercial-ready product.

In parallel, we formally initiated our proteoform expansion pipeline. As Sujal mentioned, we launched an 18-month collaboration funded by The Michael J. Fox Foundation to develop an alpha-synuclein proteoform quantification assay, extending the platform into Parkinson's disease. This program includes development of a pilot assay focused on key post-translational modifications, optimization of enrichment and sample preparation workflows and application of the technology to human brain and biofluid samples. We view this collaboration as an important opportunity to further demonstrate the breadth of Iterative Mapping beyond tau and to expand our proteoform capabilities into additional high-value disease targets.

While much of our current momentum is in neurodegeneration, it's important to emphasize that Iterative Mapping is not limited to neuroscience. We see meaningful long-term potential across oncology, immunology, cardiology and beyond. We are currently evaluating multiple oncology-focused candidate proteins with the goal of having an oncology-focused proteoform assay enter early access in the second half of 2026. We believe oncology represents a compelling next market opportunity, providing access to a broader customer base while also aligning well with the capabilities of our platform to deliver proteoform level resolution and highly reproducible measurement in complex biological systems.

Overall, Q4 represented a strong quarter of technical execution as we continued advancing our Voyager instrument and end-to-end platform. We made meaningful progress on the broadscale assay configuration change and began generating initial data from the new approach while also advancing our proteoform portfolio with tau on track for early access sample processing by the end of this quarter. At the same time, the growing body of externally generated data from collaborators like the Buck Institute and the Allen Institute continues to validate both the robustness of our measurements and the unique biological insight enabled by Iterative Mapping.

Taken together, these developments reflect continued platform maturation and reinforce our confidence in the technical foundation required to scale our assays, broaden our target portfolio and support future commercial deployment.

With that, I'll turn the call over to Anna to review our financials.

Thanks, Parag. Turning to our financial results. We continue to demonstrate strong operating discipline in Q4 and throughout 2025. Total operating expenses were $15.4 million for the fourth quarter of 2025, a decrease of 23% from the prior year period and $66.8 million for the fiscal year 2025, a decrease of 18% year-over-year.

Research and development expenses were $41.1 million for fiscal year 2025 compared to $50.5 million in fiscal year 2024, representing a decrease of $9.4 million or 19%. This decrease was driven primarily by a $4.5 million reduction in laboratory supplies and equipment expenses, reflecting operating efficiencies, lower development-related costs and continued cost optimization efforts.

We also saw a $2.4 million decrease in salaries and related benefits, driven by savings from the reduction in force implemented in the first quarter of 2025, along with a $1.9 million decrease in stock-based compensation expense.

General and administrative expenses were $25.7 million for fiscal year 2025 compared to $31.0 million in fiscal year 2024, a decrease of $5.3 million or 17%. This decrease was primarily due to a $3.9 million reduction in stock-based compensation expense, along with a $1.3 million decrease in professional services, largely attributable to lower legal and consulting costs.

We ended the quarter with $156.1 million in cash, cash equivalents and investments. Cash burn in 2025 was $50.2 million, down from $57.8 million in 2024, reflecting the benefit of lower headcount and development expenses.

Looking ahead, we expect total operating expenses for the full year 2026 to increase as we continue investing in platform development, support the expansion of our Early Access Program and advance commercial readiness activities. We currently anticipate total operating expense growth of approximately 15% to 20% in 2026, and we expect full year 2026 cash burn to be in the range of $65 million to $70 million. Based on these assumptions, we continue to believe our financial plan supports a cash runway that extends through 2027.

Following the launch of our Early Access Program in January, our initial customer engagements are primarily with academic key opinion leaders seeking early access to the tau offering to support exploratory research and grant applications. While we expect modest services revenue later in 2026, we anticipate the primary revenue ramp will begin in 2027 once we start shipping instruments.

As a reminder, instrument placements drive our recurring consumables business and together, they create a scalable top line. We believe the instrument and consumables ramp will accelerate meaningfully once both our proteoform and broadscale capabilities are generally available, enabling customers to deploy the full power of the platform and driving broader commercial adoption.

As Sujal noted earlier, we also announced grant funding from The Michael J. Fox Foundation to support development of an alpha-synuclein proteoform assay. Under this agreement, we expect to receive approximately $1.2 million with development and sample analysis work occurring over approximately 18 months across 2026 and 2027. Revenue will be recognized as the underlying work progresses.

Back to you, Sujal.

Thanks, Anna. As we wrap up, 2025 was a year of meaningful progress for Nautilus as we continued advancing the platform and began transitioning toward external engagement. That momentum carried into early 2026 with the launch of our Iterative Mapping Early Access Program and was further highlighted this week by the debut of the Voyager instrument at US HUPO, where we introduced the system directly to the proteomics community. Together, these milestones represent important steps in putting the platform into the hands of researchers.

Looking ahead, we expect 2026 to be a pivotal execution year. We plan to begin progressing early access customers into tau services projects, expand early access to include a second proteoform assay focused on an oncology target and introduce broadscale capabilities into early access later in the year. In parallel, we expect to place Voyager instruments externally through beta deployments as an important validation step ahead of commercialization.

We expect to initiate our commercial launch in late 2026 by opening the Voyager platform for preorders with instrument installations at customer sites beginning in early '27. At launch, we expect general availability to include the Voyager instrument, our Tau proteoform assay and a second proteoform assay. We anticipate general availability of our broadscale capabilities in the first half of '27 as we continue expanding our platform's assay portfolio.

We're encouraged by the momentum we continue to see from collaborators and partners applying Nautilus' Iterative Mapping technology to complex disease-relevant biology, and by the steady progress we've made across our assay development and operational priorities. Together, these efforts position us to begin translating years of investment in what we believe will be meaningful scientific and ultimately commercial impact.

I'm proud of the work that our team has accomplished and grateful to our collaborators for their partnership and trust. With a strong foundation in place and a clear path forward, we remain focused on disciplined execution as we advance the platform towards broader deployment.

Thank you for joining us today. With that, we'll be happy to take your questions. Operator?

[Operator Instructions] Our first question comes from Subbu Nambi from Guggenheim.

There was a lot of focus on the technical milestones you achieved in Q4 that provide you with the foundation for further technical improvements. Building off of that, I have a couple of questions. What comes next? By that, I mean, what are the next milestones and what metrics materially get better building off of the technical milestones you achieved in Q4? And second, have you shared these milestones with any of the key customers, especially those focused on tau? And if so, have these new developments catalyzed the path to placements?

Thanks, Subbu. I'll take that one. I think there are a couple of key sets of technical milestones, and I'll try and describe each of them. One of the really key technical milestones was the completion of the final studies of the Tau proteoform assay to make sure that it was ready and an incredibly performing assay for our Early Access Program. That data has been shared back with early customers. They're excited about the quality of the assay and really thrilled that we're -- at the data that we're able to produce.

The second set of progress were on instrument readiness. And as we mentioned, coming out of our evaluation instrument at the Buck, the data we learned from that. And internally, that was really what positioned us for the announcement of the reveal of the instrument at the US HUPO conference earlier this week, and tremendous excitement about folks really being able to get their hands on the instrument and see it was great.

I think the other aspect that we've been discussing in terms of moving forward are the expansion of the proteoform platform to additional targets. We mentioned alpha-synuclein and an oncology-focused target. And I think the people are -- remain very excited about proteoforms across domains. And so seeing progress towards other proteoforms validating that the platform is not just a neuro platform, but is a platform that can apply across different domains is something that we've heard a lot of positive excitement about.

And then on the broadscale side, as we mentioned, the expansion of both the scale of assays that we're performing as well as the further progress on the configuration change. I think all of those things are really key contributors. As we look forward, what we're looking at are levers like increase -- further increasing on-target binding, minimizing off-target binding. We continue to progress working on assay stability of the new configuration chips that are stable over hundreds of cycles. All of these are challenges that require optimization, not innovation.

[Operator Instructions] our next question comes from Dan Brennan from TD Cowen.

This is Kyle on for Dan. So starting with this year, I know you said no material contribution from early access in terms of revenue and a modest contribution later this year from service and reiterated the commercial launch for later this year. But do you anticipate any revenue at all from a commercial launch later this year? I think the Street was modeling a few million dollars in revenue all the way out in the fourth quarter. And then maybe building off of that, have you discussed anything new around pricing for the Voyager instrument?

Kyle, I can definitely give you a little bit more color there. As you reiterated, we don't see our early access engagements as a major driver of revenue that although we do expect some modest services revenue later in the year, our revenue for 2026 will really come from two sources. First, I'm anticipating a portion of The Michael J. Fox grant funding to be recognized as revenue in 2026 with the remainder flowing into 2027. While the work that we do for that grant may vary depending on the quarter, I think it's reasonable to expect some revenue coming in from that.

On top of that, with a handful of early access customers converting to revenue within the year. I'm looking at a target of closer to, say, $0.5 million for 2026. The revenue ramp tied to instruments is really coming in 2027. On the pricing front, we don't have anything in addition to any changes from what we've talked about previously.

Got it. And then maybe can you just give a little bit more color on how the Early Access Program is going, maybe some of the feedback you've received from these early customers? And then I guess building on that, can you speak to how your sales funnel is building ahead of the commercial launch later this year?

Yes. Let me tackle -- Kyle, let me tackle, this is Sujal. I'll tackle the commercial pieces of that, and Parag can give you some of the early feedback because really the early feedback is just from the Buck Institute and the Allen Institute who've been working with us in the very early stages of the early access or the late stages of their collaborations.

In terms of funnel, when we launched that Early Access Program, one of the things that we said in our prepared remarks was that we elected to launch it earlier than previously communicated. And that is because the data quality and the excitement that we are seeing from customers based on the early data from the Buck and from the Allen Institute, and our own internal data as well as through our partners who were -- who worked with us on the preprint that is out now, which is MSCI and Mount Sinai. All of that data was really exciting. We elected to get out to launch.

Now it's a little bit earlier than we were thinking. It's important to point out, we have absolutely 0 sales capacity in the company right now. There's not a single salesperson in the company. And so the funnel build is something in earnest that we really just began. And so HUPO was a great opportunity to get in front of a lot of potential customers. And in earnest, we will begin the sales capacity build this quarter and then continuing through the year with just a few targeted headcount. And so it's a pretty much a surgical strike sort of approach, right? It's not going to be a lot of commercial build, but we'll start to see that funnel build.

Parag, do you want to talk about the feedback that we've received?

Yes, absolutely. I think a highlight of the US HUPO meeting was very much Birgit Schilling's presentation of her latest data, looking at both different brain regions of -- that complemented across these 3-xTg mice models. And then a study where she was looking at genetic alterations that predispose people -- well, either predispose people to Alzheimer's disease or are protective. And that has been a really big open question in the field about why there was this link between this gene called ApoE and Alzheimer's disease, what actually occurred, how was this linked to tau. And her data this proteoform level detail really highlighted that those genotypes potentially led to changes in tau phosphorylation and that was a critical predisposing factor. Now it's very early data, but it is exciting to have a tool that can allow us to finally see what the downstream consequences of this either protective or extremely deleterious mutation might be.

And so I think we've heard from other folks at the conference, both how excited they were to see the data, how much they appreciated the quality of the data that the story itself and the multiomic link was extremely exciting to them and something that they want the ability to be able to forge those connections and see things they haven't been able to see before. So it was really exciting to get that feedback from the community.

I am showing no further questions at this time. Thank you for your participation in today's conference. This does conclude the program. You may now disconnect.

Good day and thank you for standing by. Welcome to the Nautilus Biotechnology Third Quarter 2025 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 speaker today, Ji-Yon Yi, Investor Relations. Please go ahead.

Thank you. Earlier today, Nautilus released financial results for the quarter ended September 30, 2025. If you haven't received this news release or if you'd like to be added to the company's distribution list, please send an e-mail to [email protected]. Joining me today from Nautilus are Sujal Patel, Co-Founder and CEO; Parag Malik, Co-Founder and Chief Scientist; Ken Suzuki, Chief Marketing Officer; and Anna Mowry, Chief Financial Officer.

Before we begin, I'd like to remind you that management will make statements during this call that are forward-looking 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 in the press release Nautilus issued today.

Except as required by law, Nautilus disclaims any intention or obligation to update or revise any financial or product pipeline projections or other forward-looking statements whether because of new information, future events or otherwise. This conference call contains time-sensitive information and is accurate only as of the live broadcast on October 28, 2025.

With that, I'll turn the call over to Sujal.

Thanks, Ji-Yon, and thank you all for joining us. Q3 was another important quarter for Nautilus. We made meaningful progress across our scientific platform and operational priorities as we continue our disciplined path toward commercialization. Last quarter, we published a preprint showcasing our iterative mapping method and demonstrating the power of our platform to measure proteoforms, distinct forms of proteins with unprecedented resolution. That manuscript was accompanied by an announcement of Tau focused collaborations with investigators from the Neuro Stem Cell Institute and with Joel Blanchard's lab at Mount Sinai Medical Center.

These collaborators were central to generating the intriguing biological data shared in that manuscript. In addition to these partnerships, I'd like to call attention to 2 other exciting partners. The first is the Allen Institute for Brain Science. As highlighted in our July 30 press release, that collaboration aims to examine how Tau proteoforms vary across brain regions as a function of disease severity. Ultimately, such projects may enable the use of proteoform biomarkers to predict the course of Alzheimer's disease. We're excited to have already begun generating the first data sets from their samples.

One other key collaborator is the Buck Institute for Research on Aging. As a world leader in aging research, they have deep experience in Alzheimer's disease research and are excited to examine how Tau proteoforms contribute to disease progression and therapeutic efficacy. I'm particularly thrilled to share that Dr. Birgit Schilling, one of our collaborators at the Buck Institute, will be presenting her results at the Human Proteome Organization's World HUPO Conference in November marking the first public presentation of externally generated Tau data measured on the Nautilus platform.

In addition to being an acclaimed aging researcher, she is also an eminent proteomics KOL and recently served as President of U.S. HUPO. Our session with Birgit at World HUPO will highlight both key technical aspects of the Tau assay such as reproducibility and also intriguing biological findings that were only possible using the Nautilus platform. I'd like to call attention to the fact that the results in our manuscript and the results that Birgit will be sharing are based on real-world biological samples, not only model samples composed of recombinant proteins or peptide.

We believe our presentation at HUPO will not only validate the technical readiness of our assay, but will also underscore the potential for our platform to drive meaningful biological insight, something we consistently hear is a top priority for researchers in this space. We view the results from our early partnerships as clearly demonstrating our platform's unique ability to measure proteoforms at an unprecedented level of precision and resolution. This is especially important for targets like Tau where the combination of isoforms and post-translational modifications have a profound impact on disease progression.

We expect that the Nautilus platform's unique ability to quantify complex mixtures of proteoforms at the single molecule level will prove an important tool for driving biological insight. Collaborations with institutions like the Buck and the Allen institutes are emblematic of the caliber of researchers and institutions that are now engaging with Nautilus. This quarter, our pipeline of potential collaborators has expanded significantly including academic centers, nonprofit institutes and biopharma companies.

These researchers are eager to explore how Nautilus can bring new clarity to neurodegenerative disease biology and also eager to explore proteoform-based precision biomarkers for Alzheimer's disease and related tauopathies. These researchers also understand that studying Tau requires resolution beyond what traditional platforms can offer and recognize that our approach is uniquely suited to identify the modified forms of Tau that may drive disease progression. We're also seeing increased interest from additional partners eager to expand into new disease areas and novel proteoform targets reflecting both the maturity of our platform and the unique insights it enables.

The conversations we're having are with premier researchers and institutions at the forefront of translating molecular insights into impactful diagnostic and therapeutic advances. The growing engagement we're seeing reinforces our belief that Nautilus is becoming a key enabling technology for the next generation of biological discovery. We anticipate that several of these discussions will lead to active engagements when we launch our early access program in the first half of 2026. Initially, customers will gain streamlined access to our Tau proteoform assay.

Select partners will be able to submit samples, receive data and provide feedback, similar to our current engagement with the Allen Institute. These early engagements will primarily focus on generating high-quality data and validating our platform. We expect only limited revenue in the near term. However, this validation is essential for building momentum and opening broader commercial opportunities, including the expansion of our assay for other proteoforms of interest. Over time, we'll expand our early access to offer support for both targeted proteoform assays and for broadscale proteomic studies.

Our aim is to make each early engagement an opportunity to build credibility, momentum and operational readiness ahead of our commercial launch. On the technology front, we made steady progress in Q3 transitioning to our new broadscale assay configuration to better align with our growing probe library and improve platform performance. Early results have been promising and we expect this configuration to enable our broad-scale commercial launch in late 2026. Briefly, assay configuration change efforts were focused on better aligning assay design with the characteristics of our expanding probe library, improving probe yield and overall platform performance.

One of the most significant areas of change was in the flow cell and associated assay reagents. Together, these changes were designed to reduce technical risk and enable higher performance as we scale toward a more comprehensive view of the proteome. A key milestone of our broadscale assay configuration change was achieved in Q3 demonstrating that affinity reagent probes previously incompatible with our old assay configuration are compatible with the new configuration.

In Q4 of this year and Q1 of 2026, we plan to test the whole probe library with this new configuration to better understand performance and finalize the steps needed for broadscale's launch. We're confident that broadscale will drive long-term scalability and value for Nautilus. Lastly, we continue to be highly intentional in how we invest our resources. In Q3, we reduced expenses quarter-over-quarter, reflecting a more focused operating model aligned with our top priorities. This operational discipline is an important part of how we're extending our runway even as we move closer to commercialization.

Taken together, the progress we've made in Q3 moves us closer to realizing the promise of single molecule proteomics, a future where researchers can decode biology with a level of precision and resolution that is simply not possible today. We're proud of the scientific and technical advances made this quarter and grateful to our team and collaborators who continue to push the boundaries of what's possible. As always, I want to thank our scientific and engineering teams for their continued dedication. The work they're doing is not only technically challenging, it's foundational to the future of proteomics.

With that, I'll hand the call over to Ken, our Chief Marketing Officer, to share key insights from our recent voice of the customer and market research work. Ken?

Thanks, Sujal, and good morning, everyone. Over the past several months, our teams have been focused on sharpening our marketing strategy by developing a deep understanding of our customers, their challenges with existing technologies, goals for next generation solutions and how the Nautilus platform can uniquely address their needs. In the third quarter, we completed an extensive market study involving more than 250 decision-makers across North America and Europe spanning academic institutions, pharma, biopharma and leading proteomics organizations.

These participants represent our core target segments and are highly familiar with both mass spectrometry and affinity-based technologies. Through a combination of detailed qualitative [ in-reviews ] and deep quantitative analysis, we built a rigorous and data-rich view of our market opportunity. Three clear themes emerged. First, customers viewed the Nautilus platform as uniquely differentiated from current mass spectrometry and affinity-based technologies. They highlighted our iterative mapping approach as delivering an unmatched combination of protein coverage, reproducibility and sensitivity.

In particular, customers were most drawn to our ability to achieve both broad proteome coverage and deep single molecule proteoform level resolution, a capability that only iterative mapping can deliver. Our competitive differentiation is stronger than ever. As a former General Manager of mass spectrometry at Agilent, I found it especially validating when 1 customer commented that the Nautilus platform "has the potential to replace a major portion of mass spectrometry and proteomics". Second, our research confirmed that customers both expect and are willing to pay a premium for our solution.

The ability of iterative mapping to provide broad scale and proteoform level insights drove particularly strong enthusiasm and willingness to invest in our solution. Combined with the platform's reproducibility, sensitivity and simple AI-ready output; customers valued our instrument on par with high-end mass spectrometry systems, a strong endorsement in an already premium segment. Finally, we heard a clear and consistent message of eagerness to engage with Nautilus. Many customers described current technologies as limiting, constrained in performance, lacking cross-platform agreement and often complex to use.

They are actively seeking a new class of measurement technology to complement or replace their existing tool sets. After decades of experience introducing new products, I'm encouraged by the strength of this product market fit and by our customers' enthusiasm to begin evaluating the Nautilus platform. We are channeling this confidence as we plan for our early access program beginning with the Tau proteoform assay in the first half of 2026. I look forward to continue sharing our progress as we transition towards our commercial phase.

Next, I'll hand over the call to Anna to walk through our financials. Anna?

Thanks, Ken. For the third quarter of 2025, total operating expenses were $15.5 million, down from $19.1 million in the same quarter of 2024. This 19% year-over-year decrease reflects our continued focus on expense management, operating efficiency and lower development costs overall. Our stock-based compensation expense also declined meaningfully year-over-year. Research and development expenses for the third quarter of 2025 were $9.6 million, down from $12.3 million a year ago. This year-over-year reduction was driven by lower development cost as well as improved operating efficiency in personnel, laboratory and services spend.

General and administrative expenses were $5.9 million, down from $6.8 million in Q3 2024 driven largely by reduced stock compensation expense. Net loss for the quarter was $13.6 million compared to $16.4 million in the prior year period. We ended the quarter with $168.5 million in cash, cash equivalents and investments. Cash burn in Q3 was $11.0 million reflecting the benefit of lower operating expenses. We continue to project a cash runway extending through 2027 providing ample time to advance platform development and early-stage commercial activities.

Looking ahead, we anticipate that total operating expenses for the full year 2025 will come in below what we saw over the past 2 years. With that being said, we expect Q3 will be a low point in our spending and future quarters will increase as product and market development activities ramp up. As for our Tau early access program, the first customer engagements are likely to be with academic KOLs that need access to the platform and initial data sets in order to support their grant applications.

We believe these first internally funded services engagements will lead to revenue engagements over time, but more importantly, publications, additional grant applications and potentially instrument orders. We are excited by the shift towards commercially oriented activities, but we don't expect meaningful services revenue from these engagements in 2026.

Back to you, Sujal.

Thanks, Anna. As you've heard throughout today's call, Q3 was a quarter of continued execution and meaningful progress for Nautilus. We advanced our Tau proteoform assay, built momentum with prospective collaborators and are on track to launch our early access program in the first half of 2026 beginning with Tau. We're preparing to showcase externally generated Tau data at World HUPO in November, a milestone that reflects years of investment in scientific and technical innovation.

As demonstrated by our excitement and ability to expand our collaborative work, Nautilus' doors are open today for partners who are interested in funding the development of new proteoform assays and shaping the future of proteomics. We also made steady progress towards the new broadscale assay configuration that will support our commercial launch. In addition, our disciplined operations and spending have us ending the quarter with a strong balance sheet and clear line of sight to our strategic goals.

As we close, I want to step back and emphasize something fundamental. Our platform is as disruptive today as it was when we first set out to build it and now we have even more external validation to back that up. Iterative mapping represents a completely new class of measurement, different from anything else in the market, delivering proteome and proteoform insights that existing technologies simply cannot match. Our extensive market research and voice of the customer work encompassing more than 250 interviews with representative customer groups makes it clear that the market recognizes our differentiation.

Customers consistently affirm that what we're building will reshape the landscape. This strong validation gives us tremendous confidence in both our technology and the commercial opportunity ahead. I'm incredibly proud of what the team has accomplished; the science we're advancing, the platform we're building and the opportunities ahead. Our foundation is strong and our mission has never been more focused.

Thank you again for joining us today. With that, we'll open the call for questions. Operator?

[Operator Instructions] Our first question comes from Dan Brennan with TD Cowen.

This is William Ruby on for Dan Brennan. Just a couple of questions. First, just wondering how we should think about the level of OpEx investment you'll need to make heading into the launch next year. And I know you touched on it a good amount on the call, but if you could just go into a little bit more detail on the funnel that you're building out of early access coming into next year.

William, this is Anna. I can speak to the first one. From an OpEx standpoint, we're, as I said in the prepared remarks, expecting that from our low point here in Q3 we are anticipating that spend will increase as we get closer to commercialization. As you might expect, I don't have an outlook yet for 2026, but you can extrapolate from our guidance that we have cash through 2027 and I would anticipate some steady step-up between now and the end of 2027.

And William, this is Sujal. Let me take the second half of your question, which is the funnel. So let me first sort of describe just in a little more detail how we would expect next year to unfold. And so what we talked about on the script was that we intend to launch our early access program in the first half initially with Tau and our proteoform panel with Tau and then in the second half, we'll expand that early access to include our broadscale proteomic capabilities. And that sort of setup will lead to a launch of each of those things after that early access period, that official launch. And we continue to state that by the end of 2026, we expect a launch of our broadscale capabilities.

And that early access and then launch model is a model that we'll use for subsequent proteoforms and subsequent versions of broadscale and so forth as we move beyond into future years. So in terms of the pipeline build, pipeline build is occurring for both of those different products and use cases, proteoform starting with Tau and with broadscale. With Tau, obviously the pipeline build in earnest really just began as we released that preprint last quarter meaning Q2 of 2025 and started to talk to partners about the capabilities of our product.

And as we mentioned in the prepared remarks, we intend to at the beginning or the first half of 2026 launch early access in a [ funnel ] manner for those Tau capabilities. And so with that coming, we're in the process of sort of finalizing our product verification and validation. We're in the process of talking to and building the top of the funnel for those Tau capabilities. And we're starting to think through the first commercial hires, which we would expect the first -- we have business development and scientific affairs types of headcount today, but we would expect that in the first quarter we would make our first official hire on the direct sales side as well to build capacity for the Tau services initially and then broadscale as we move on to the second half of the year.

Thank you. This concludes today's question-and-answer session and today's conference call. Thank you for participating. You may now disconnect.

Hello. Hi. My name is Yuko Oku, and I work on the Life Science Tools and Diagnostics team at Morgan Stanley.

Before we begin, I'd like to remind our listeners important disclosure information that can be found at morganstanley.com/researchdisclosures. It's my pleasure to host Nautilus, and speaking on behalf of the company, Founder and CEO, Sujal Patel. Thank you for joining us today.

Maybe to start for those that are not as familiar with the story. Where do you see Nautilus fitting within the evolving proteomics landscape? How is Nautilus approach to proteomics different from other proteomics platform that exists today, including proteomic sequencing companies like QSI and Encodia, targeted proteomics platform like Olink or SomaLogic, nanopore protein sequencing and protein fingerprinting?

All right. Well, that's a lot to dive into right there. First, thank you, Yuko, for the invite to the conference. It's great to be here again.

So Nautilus is pioneering a new method to analyze proteins. And proteins are the key part of your cells that do all of the work in your body. And unlike DNA, which the analysis of DNA is a commodity, costs a few hundred dollars, you can get 100% of your genome. It's accurate, it's reproducible, it's reliable, easy.

Proteins are very different. Protein analysis is incredibly hard. It's complicated. There's many different dimensions. And in the end, the very best we can do is get a small fraction of the answer that we're looking for out of a sample. That's a big problem. It's a big problem because 95% of our FDA-approved drugs target proteins, most molecular diagnostics target proteins, proteins are incredibly important for therapeutic development, for diagnostics, for precision medicine, and the world does not have a good way to measure them.

The way that we measure them today, the gold standard, if you will, is a complex workflow that's built around mass spectrometry. Billions of dollars of mass spectrometers are sold into protein discovery environments, every single year. But for example, if I take a drop of blood and I'm looking for the proteins that are in a drop of blood, the high confidence proteins that are identified and quantified out of that can be as little as 10% of what's actually in the sample. And when you have such a small percentage of the sample being accurately identified and quantified, you don't have the ability to do complete analysis. You don't have the ability to figure out, if a drug candidate can be cross-reactive with some other part of the body. You don't have enough data for this next generation of AI technologies to really analyze it and figure out where the next therapeutics are coming from.

Nautilus is building a new instrumentation platform that is a complete platform end-to-end, that's focused on delivering comprehensively the entire proteome out of any sample from any organism. That is a -- you mentioned a bunch of other companies in this -- in your opening. That is a very different proposition than what many of these other companies, not many, all of these other companies are after. All of the companies you mentioned and things that are separate from the mass spectrometer are focused on some small niche of a solution. I have some percentage of the proteome, but not sensitively. I have some applications in sequencing, but only very, very short fragments of a protein. I have some ability to measure 10 or 15 proteins, but not the whole thing.

We're building a platform that can identify the entire proteome and dig deep into single molecules of interest, which is becoming increasingly important in the customers that we're talking to. So that's kind of us in a nutshell. We are a development stage company. We are planning a full launch of our full proteome solution at the end of next year. And this year, we've begun early analyses with customers for some of these deeper proteoform applications. I'm sure we're going to get into.

Yes. I want to dig right into the science here now. You recently made manuscript available on BioArchive, which introduces iterated mapping of proteoform, IMAP, a method that enables interrogation of proteoforms in a massively parallel manner.

Now one of the things that jumped out at me, was the methods dependent on availability of highly specific and sensitive antibodies for the particular targeting question. In light of that, in what format would you make this application available to customers? Do you anticipate having kitted solutions that have already been validated at Nautilus? Or would you also enable custom solution by allowing the customers to bring their own antibodies?

Yes. So the preprint that you're talking about in this capability is what we call proteoform analysis. And just to kind of differentiate that from what we expect to launch at the end of next year, when -- one of the most basic questions that biologists ask is, here's a sample, tell me all of the gene encoded proteins in it. And that is an unsolved problem and one that we expect to address at the end of next year, and we think that product is an absolute killer product in pharma, in DX, academic nonprofit research.

The other half of our platform, same platform, different application is focused on digging into 1 or 2 or 3, a small number of proteins and mapping all of the different chemical modifications and forms of that protein. Why is that important?

It's important because there may be 20,000 canonical gene encoded proteins inside of a human, but that is a very small fraction of the complexity of a human. All of these proteins are degraded in different ways, are functional in different ways, and that diversity is reflected in the chemical modifications that are done by kinases and enzymes on these protein molecules, and it's encoded in that form of the protein. There really is no good at-scale way to understand what are the forms of proteins that are out there. So why is that important?

Well, take, for example, this preprint that we put out. The preprint is all about tau and looking at hundreds of different forms of tau. And in fact, our assay is capable of up to 2,000 forms of tau. In Alzheimer's disease, the key pathology is that there are many phosphorylation events that occur on tau. Phosphorylation is one type of modification, there's too many of them, and it causes an accumulation in the brain, which ultimately causes neural damage and leads to the awful symptoms and awful lifelong effects of AD.

This preprint was the first time, that it has ever been -- the entire form of the tau protein as you progress to AD has been analyzed. We, for example, were able to find a quadruple phosphorylated, meaning 1 molecule that has 4 modifications version of tau, that showed a distinct pattern that got to that point, meaning a pathway that led backward in time. If we can follow those types of pathways, you can intercept AD earlier and our customers and future customers in therapeutic development space are going to use that information to build better therapeutics that are earlier, that are more precise. That's really the crux of that preprint.

Tau is the first protein that we're going to work on. We'll likely do 1 or 2 more in neuro-degeneration, but this is a generalized problem across cardiology, across inflammatory disorders, autoimmune, cancer. And so there's a great deal of white space for us to expand into. But this is a market where each of those applications, we have to build a new assay. We have to go and evangelize it. We've got to go put it out into the world. It's a slower build than the product we intend to launch at the end of next year.

Okay. That makes sense. And then one of the other interesting aspects of the paper, is that you demonstrated the ability to measure over 130 different proteoforms of tau, some of which had many of 6 co-occurring phosphorylation events. Tell me, how common is it to see that many different protein alterations on the same gene? And how big of a problem is the lack of ability to interrogate these forms in determining biological function?

Well, I'm going to zero in on an interesting part of your question, which was how common are 6 phosphorylations on a single molecule. The answer to your question is, we have no clue. This was the first time that anyone has ever gathered this level of information on any molecule. And this is on the tau molecule with our assay.

We don't know how common it is. We know through some methods like top-down mass spectrometry that modifications are extremely prevalent. We also just intuitively know that as well, right? We have 20,000 genes in a human. It's less than a banana has. The complexity of the human is not encoded in our genes, it's encoded in all of these different chemical modifications and iso-forms of these and splice forms of these proteins. And you asked a question, well, do they have biological relevance? That's a question that is answered.

Every one of those modifications, creates a different pattern within the protein. It creates some -- sort of messaging change. It creates a degradation. It causes protein to migrate from the nucleus to the cell-surface. So they all have functional changes. And so understanding this is going to be critical if you're trying to build better therapeutics, you're trying to build better diagnostics for the future.

Another highlight from the paper to me was extreme reproducibility of the platform, which other proteomics vendors have also highlighted as a key differentiator. Could you explain to me why this is important?

Yes. Let me try describe -- I'm going to answer the question two ways. One, I'm going to answer the first part, why is it important? And then I'm going to talk about how we're able to deliver this reproducibility and how it compares to others' claims?

So reproducibility is absolutely critical, because reproducibility means that you have data that you can rely on. If you're trying to do an analysis and understand what is the marker that is a therapeutic target that I'm going after. If you're trying to look at a diagnostic for AD and you want to understand, is this a biomarker that always precedes -- change always precedes disease or not? Those are things you have to be able to rely on. If there's differences and you look at the same sample and there's variability that's significant, you're never going to make sense out of what you're looking at.

And particularly when we move to this world of the future, where AI and other data science technologies are analyzing these data sets, having data that is reliable and always correct is going to be 100% critical. So that's the reason why it's important. The way that we get reproducibility is fundamentally different than what anyone else has attempted before. The way that others get reproducibility is that they tighten every aspect of their analysis and their assay. They make sure that every single reagent that goes in their system is in these tiny, tiny narrow bands of specification. They go and make sure that assays always run in the exact same way, the same time, the same temperature, at the same instruments. This is really the level of specificity.

Our approach is the only approach which takes a single intact protein molecule and probes it over and over again with all sorts of different reagents, gathering information that increases our confidence about this molecule. Because of that, we're not just taking one data point. We're taking hundreds of data points and putting them together to come up with a comprehensive exact identification of what the molecule is.

By doing that, we are able to be so confident about the molecule's identity and proteoforms that our CVs co-efficient to variation, a measure of [ reproducibility, incredibly ] tight. We showed CVs between 1% and 5% in the first experiments that came off of our platform that made it into that preprint. 1% to 5% for a platform that just, is publishing first data is crazy. Most of the platforms that have been around for 2 decades have 20% CVs. And even then, you can look at the asterisks on their disclosures. It's really, really -- it's really, really hard to figure out, is that really a true CV? How did they look at it?

Because we're able to gather all these data points, it's a fundamentally new method of gathering reliable data. And we think that's going to be critical for us over the course of the next few years of productizing both those proteoform capabilities and our broad scale capabilities.

Great. While this study used cell lysate, do you imagine that over time, the technology could be used in fixed tissue slices? Are there any technological limitations that will restrict you from doing that?

Yes. So when you -- your question more broadly is about sample type. So when you think about each application, the sample type is going to be different. When we're talking about tau, tissue is fine, but that means that your patient is diseased. So there is a need for -- from our customers to move to CSF as a potential sample input and then ultimately to blood serum, which, of course, is the easiest and most prevalent out there. And so those are two capabilities that we intend to pursue over the course of time as well.

And the issue, of course, is that CSF has at least a few orders of magnitude less tau in it than brain tissue, another few orders of magnitude to get the blood and some of the forms might begin to degrade. And so we'll work through that over time. Things like frozen tissue and so forth, the only limitation for us is that, in order to do these proteoform analyses, we're going to want whatever has occurred with the tissue to make sure the proteins are still intact. They can be denatured. They could be -- they could lose their structure, but they have to stay as a whole.

You also announced that you entered into an agreement with Allen Institute to evaluate connection between tau protein and neurodegenerative disease. Tell us a little bit more about the goals of the partnership and when we might begin to see data from the collaboration?

Yes. So the Allen Institute for Brain Sciences agreement is really a pilot to start taking some of the samples that they have of brain tissue and looking at how our data relates to the data sets that they already have on it.

Their goal is to demonstrate with their own samples that the depth that we showed in that preprint is what they should expect out of their samples. And then the goal there for us, of course, is to go and turn that into a Phase II or Phase III after that and really start to do some analyses that help understand the basic pathology that occurs with tau as it relates to AD and frontal temporal dementia and some of the other tau-opathies that are out there. This deal is probably a lot like what we will see both with other research institutes, but as well pharma, right? It's always going to start with a very, very small pilot. Some of those may be paid, some of them may not be. But when they are paid, they're small dollars.

Really for us, revenue is not important in any of these engagements. Our goal is to show the world that if you don't measure tau proteoforms at this depth, you are not going to be able to build better therapeutics, you're not going to be able to build better diagnostics. And so our goal is to make it known, that this is a necessity, not just for tau, that's a proof point of 1,000 other biomarkers beyond it. But the goal is really to show the world what the power of this technology is.

And just based on customer -- potential customer conversation you had so far based on these protocol analysis capabilities, could you provide color around the mix of customers that have expressed interest in potential collaboration partnerships?

Yes. I mean mix of customers is probably too early to generalize off of that. These capabilities are about 3, 4 months old. And so it's very, very new. The first people that read these preprints are the KOLs in the neuro space, and they all call up, they're like, holly macro, how did you do this? And then we have a conversation.

We also just went to the AAIC, which is the big Alzheimer's conference just occurred. So we met with most of the academic and nonprofit research KOLs in this space. And so I'd say that most of our conversations have been with them, but the pharma conversations are starting to pick up as well as we start to show more of the data that we're -- that we've been generating with some of our early, early collaborators.

Great. And then just moving on to now broad-scale discovery capabilities on the platform. In conjunction with targeted proteoform analysis capabilities on the platform, are you also advancing broad-scale discovery proteomics? You're also advancing broad-scale discovery proteomics capabilities. Are there key takeaways or learnings from the IMAP publication that can be read through to the efforts of broad-scale discovery efforts?

Yes, that's a great question. Just to level set, right? So we have one platform that has 2 use cases. One use case is these proteoform analysis and one use case is what we call broad scale analysis, which is a discovery application. I have a sample tell me everything that's in it.

The platform elements are the same. The only thing that broadscale requires is, it requires a few hundred proprietary reagents, which are the probes that we've been talking about on earnings calls that we've been building for many, many years. The rest of the platform is actually pretty much identical. The go-to-market for each of these opportunities is also quite different.

While both, I firmly believe now both are really big opportunities, multibillion-dollar opportunities each. There's a ton of market development that has to go into the proteoform work because no one has even conceived that this type of data was producible until that preprint came out.

The second thing is for every biomarker, I have to make a new assay. And that's -- it's a significant amount of work for us to build an assay to go through verification validation, to ship it and so forth. So panels are going to come out more slowly and the revenue wheel is going to spin more slowly on that side. Not to say that it's less important, but that's just a fact.

On the broad scale side, customers are buying million-dollar instruments every single year to try to do discovery proteomics. The sales cycle is going to be shorter. There's an existing CapEx budget that we can fit into, and customers readily understand our differences relative to the incumbents that are out there. And so we expect that when that product is done, it's one product that will sell at a much more rapid pace.

With that, we're a company with very limited resources. We have -- while we have $180 million-ish of cash, we are preserving the vast, vast majority of that for our completion of development on the broadscale side, the commercialization, building the commercial team, commercialization, early revenue.

So if you ask me what the split is, it's probably 5% of our resources are being spent on proteoforms right now. It's way lower than I'd like, but it's kind of a fact of where we are, like 95% of our energy is still focused on broad scale because we believe that the differentiation relative to the competition is enormous, and we think the revenue opportunities are more immediate.

Would you ever consider just launching a product with proteoform analysis capabilities alone? Just to get researchers more comfortable with the data that comes off it and build a brand awareness?

For sure. Yes, absolutely. And it's not a question of if, it's just a question of when, right?

We will launch those capabilities. And today, it's just collaborations. It's a one-off process each time, but certainly, we're going to launch those capabilities. You asked earlier, how are we going to let people access those capabilities? Initially, we're going to let customers access those capabilities through a service, send us the samples, we'll analyze them, prep them, get you the results. And that is a good model for proteoforms, because there's not a lot of appetite out there to buy $1 million instrument just to do proteoform analysis on one marker.

But over time, once the instrument is being placed because of our broad scale capabilities and that we don't have panel, we have 10 or 20 panels, we expect that we'll be using kits to drive those proteoform capabilities on the customer's own instrument as well.

One of the reasons for delaying launch was to reconfigure the broadscale assay, which is expected to reduce technical risk and yield, greater number of affinity reagents. First of all, how do you know that changing broadscale assay configuration will yield more affinity reagents to meet your specifications?

And then second, I understand that it's a significant undertaking that's likely to take multiple quarters, but could you provide any updates on those efforts?

Yes, that's a great question. So our broad-scale assay depends on us building hundreds of antibodies. We call probes, affinity reagents, whatever you want to call them, hundreds of probes that go and will bind to pieces of a molecule. And those pieces are very short, usually about 3 or 4 amino acids.

And that level of information by itself is nothing. We can't tell you what a molecule is. But when you stack up 100 or 200 or 300 pieces of information from these probes, you can come up with a shockingly precise idea of what the molecule is, and then we can do that for billions of molecules across our system at once.

One of the key problems that we talked about on our earnings call at the very beginning of the year was that, too few of the probes that we're building are functioning well on our platform. And by functioning well on our platform, what I mean is that every antibody on the planet has a natural state. How long does it take to bind? How long does it stays put before it unbinds? The unbinding was too fast for us. And we had to deal with that either by building thousands and thousands of more probe candidates with a very small yield, which is not an approach that you want to take for a number of reasons or biting the bullet and changing our assay configuration, so that it's much more tolerant of these shorter rates that antibodies come off of a protein.

And that is -- that was what led to 1 year delay in our schedule from this most recent round. And how do we know that it's going to make a difference. We've done extensive proof-of-concepts before we started to do the work to change the assay configuration. Changing the assay configuration for us requires a chip and flow cell change. So we've gone through the process of doing that. We have external partners that help with that. And I'd say that we're through the development work on that and are at a phase now where we're proving. And so what I'd say is over the course of the next 1 to 2 quarters, you'll hear a lot more specificity from us on where those efforts are. And those efforts are expected to allow our probe library that we have today to be much more usable, which means that we will be able to get to our goals by the end of next year.

Great. Looking forward to it. And then beyond affinity reagents, what to do are remaining prior to commercial launch? What types of internal performance metrics, milestones are you watching to gauge, whether you're on track for a launch in late 2026?

Yes. So what I would say is that from a development perspective, many parts of our platform have had a lot more time to mature because it's taken us a lot longer to get these affinity reagents done, to get the probes that we need to get a full platform out. And with our work that we're doing on proteoforms, we're showing that the platform is capable of very tight CVs. It is capable of cycling affinity reagents in one at a time. The chips and flow cells are fully functioning. And so a lot of those capabilities are being hardened by the work that we're doing in proteoforms.

The go-to-market work that's required as we head to broad scale, is really related to getting a preprint out that looks like the preprint we just did on tau, but for broad scale. It's launching an early access program to let early customers have access to these capabilities via a service, which gets them comfortable with the results and it gives us the data that we need to continue marketing to other new customers out there. And we've really just -- those are the big steps that are coming up that get us to that final release at the end of next year.

And how should we think about time lines to when you might kick off the early access phase?

You should think about the early access phase is about 6 months before the launch. And so that's the goal for us. And so we can work backward from whenever you think, end of next year.

Okay. Sounds good. All right. And then moving on to manufacturing. What have you done to ensure that you're ready for launch in late 2026 from a manufacturing perspective, both on reagents as well as on the instrument side?

Yes. So on the instrument side, like I said, the instruments had good time to bake. We have multiple facilities ourselves. So we know what it's like to ship an instrument. We know what it's like to get an instrument up and running on another site. We've worked through some of those early things that you would expect. We have enough scale on the instrument side to go and get done a reasonable number of builds for a revenue ramp, and as well, we've worked with our supply chain to reduce any of the single parts that are difficult to have long lead times. We don't have any of those sort of things on the instrument side.

On the reagent side, we have a robust reagent manufacturing capability within our walls. And then we have a number of partners on the antibody side, in particular, where we have [ burst ] capacity, and we have capacity to bring in product that is the same specifications that we make internally. And so we've got a robust pipeline there of partners and CROs that are backing us up, and we feel confident that we're good to go from that perspective as well.

Should we anticipate the launch in late 2026 will be fully scaled? Meaning you'll be able to ship as many instruments that are in demand? Or do you anticipate that to be steady as you gauge demand?

If we were fortunate enough to have so much demand that we had to worry about that, we would [ stage the mouth ] a little bit. I mean, this is a brand-new launch of what I think is the most ambitious proteomics platform that's ever been built. And we will take it a little by little, to make sure that our customer satisfaction is very, very high, right? Those things are super important when you're introducing a new capability like this.

Makes sense. Okay. And then while focus has been predominantly on progress of developing affinity reagents, could you share where you are with respect to software side of things? Is it possible to work on software to back-end analytics in parallel? Or do you essentially need to wait until you have a complete set of affinity reagents for the launch?

So there's a lot of different aspects to software. The instrument requires a tremendous amount of software to run. We send all of the data that comes off the instrument to the cloud because the type of analysis that's required to identify molecules is pretty compute-intensive. And so all the technology for that data pipeline, for the cloud software, for the customer portal, all of that technology is being built and is in good shape for launching at the end of next year.

There are a whole set of analytical capabilities after that as well. And we think those capabilities will be critical differentiated capabilities for us that perhaps we will even be able to charge more for. But no, we haven't substantively started building a lot of that technology yet because, yes, we could parallelize some of it, but it's better if we see the data first and understand what we're looking at and how our customers want to use that, right?

There's going to be -- there's never been complete information in proteomics before. There's never been this level of mapping of proteoforms before. And so the process of understanding what our customers want to do with that information is -- it's the learning process that we're in the middle of with customers on the proteoform side, and we think that, that same learning process will happen on the broad scale side.

Got it. And then as you touched on earlier, you're talking about a $1 million price tag for a complete bundled solution for your platform. So first of all, is that how you're still thinking about it? And second, if the environment continues to be challenging at a time in a commercial launch, could you provide your thoughts on the ways you could help to facilitate accessibility to the platform?

Yes. So we'll talk about it in more depth on the next earnings call, but we are just about done with a new pricing study. And I can tell you our price point is absolutely solid for the value that we're going to deliver. And so a roughly $1 million deal is what I expect that we'll be launching at. That deal is instruments, software support, some reagents like prep install to get you going.

And given the value that the platform is capable of putting out, what the data that we're seeing from customers is that, that price point is solid and that a few thousand dollars a sample, which is what we've been talking about is a solid price point on the consumable side as well.

Now your other question, what do you do if it's not accessible to users? There are a number of things that you can think about doing there. One, is customer can access these capabilities in a less scaled fashion using our service offering. We expect that customers on the academic and nonprofit research side will need to apply for grants. And when they do apply for grants, we'll provide capabilities for them via the service until their grants come through. There's the possibility of things like reagent rental models and so forth, but we'll be careful with that, and we'll have to feel our way out as we get closer, right?

There are some platforms that don't quite have the value that we do, in the tool space today that have started to use those models because customers don't want to pay for the instrument. Our instrument is fitting into a bucket where customers are buying mass spectrometers, and we think that the budget is there, and we don't want to compete against ourselves here. So we'll have some flexibility, but we're going to be careful.

You've been extremely prudent in your spending and extended your cash runway into '27. Could you remind me of your cash position and provide examples of how you're able to manage costs so well?

Okay. So I did -- our cash position is about $180 million. And when we took the company public 4-plus years ago at this point, we raised $345 million. So we have done an excellent, excellent job with cash management. How do you manage cash? Like that is a daily job. My CFO is in the audience here, Anna Mowry. She is like the best at it. Anna and I worked together at my last company, which was a publicly traded tech company. We had the company at a positive 20% operating margin before we sold it. That was on a scale of roughly of closing $100 million a quarter for the last quarter before we sold that business.

Making a business as efficient as we think we are, is like thinking like a start-up. Everything in our organization is like a startup. There's not one headcount where I'm like, that's a headcount that isn't necessary. Every single dollar that we spend, we're spending in a prudent way. And we think that's important for all of our shareholders. We also think it's important for us, right? Parag Mallick, my Co-founder and I own 1/3 of this company still. So every dollar we spend, with $0.33 out of our pocket. We take it seriously.

Great. And then in the last couple of minutes here, I just want to close up with a bigger picture question. So how would you anticipate proteomics to evolve in the future with new emerging technologies, improving scalability of proteomics as well as increasing number of targets that can be identified on the platform?

And in your view, what are the key differentiating factors for those that take a majority of the market versus those that are limited to niche applications?

I mean that's a great question. And I think that we can take some hints from the genomics era on this, right? There have been no less than 50 different platform attempts in the genomic space. And out of those, one, Illumina emerged as by far the leader. They had a solution that was reliable. It was packaged really well. It gave you a largely complete answer, and they did a great job of executing.

I think proteomics will have lots of winners, but we think we're the one that will emerge, assuming we get done what we say we're going to get done, which I'm hopeful of. I think we're the one that will have the opportunity to really democratize access to the proteome, and that's why I get up every morning.

Okay. Well, thank you so much, Sujal.

Thank you, Yuko.