Thanks, Marissa, and thank you all for joining us today. Last quarter, I walked you through a deliberate decision to concentrate our resources on proteoforms. This quarter, I want to talk to you about what proteoforms are and why we believe they're one of the most important opportunities in life sciences and how we're building the foundation for meaningful long-term growth. Let me start with the idea that guides everything we do.

We are making functional biology measurable. For decades, proteomics has primarily been about telling us how much protein is present. While the quantity of a protein is meaningful information, it's not the whole story. Most of today's tools don't have the resolution and scale required to measure the myriad of function-driving modifications that vary across every protein molecule. Shotgun mass spectrometry breaks proteins into peptides and infers the proteins from those pieces.

Most affinity assays estimate average abundances by measuring a singular epitope on a protein. Either way, functionally distinct protein molecules are undifferentiated as the information about splice variants, truncations, and which modifications co-occur on the same molecule is lost. That matters because the complexity of human biology does not come from the number of genes we carry. Consider the banana. A banana has almost 40,000 protein coding genes.

As humans, we are clearly more complex than a banana. In the early days of the Human Genome Project, scientists expected humans to have well over 100,000 genes. In fact, we only have about 20,000 genes, half as many as a banana. The reality is that our complexity comes from the functional biology layer above the genome, and particularly from the many forms each protein can take. Those genes are merely the instruction manual for building the machinery of life.

A single gene can give rise to many distinct proteoforms, shaped by splicing, sequence variation, and by many modifications that occur after a protein is made. Each molecule is a discrete functional unit, and its form determines what it does, how it signals, who it interacts with, and where it sits spatially in the cell. The specific form a protein takes often determines what it actually does, where it goes, what it binds to, and what pathway it turns on, and which phenotypes it ultimately drives.

AKT1 is a good example. It is a central switch in cancer signaling, and whether that switch is on depends on which sites are phosphorylated together on the same molecule. Two cells can carry the same amount of AKT1 and be in completely different signaling states. Tau is another example. In Alzheimer's disease, what matters is not just how much tau is present, but which modified forms accumulate. Since proteoforms were never previously measurable at scale, it was never possible to use this critical information to understand health and disease.

Proteoform resolution provides valuable, novel information for drug development and precision medicine, and it has not been accessible at scale until today. We built Iterative Mapping, the method that powers our Voyager platform, to change that. It reads millions to billions of single intact protein molecules across a massively parallel array, so it can resolve each molecule's functional state rather than breaking it apart or averaging them away.

When you can see that layer of molecular resolution, you're looking at an entirely new kind of biological insight. We believe no one else can deliver the resolution and scale our platform can. That is what we mean by making functional biology measurable, and I believe the value of this approach will become increasingly clear as our data reaches more scientists. We believe that proteoform resolution at scale will be a critical foundation for AI in biomedicine.

The industry is starting to build large data sets to train the next generation of AI models, and those models are only as good as the data they learn from. We believe highly reproducible proteoform data is exactly the differentiated data they will need to learn functional biology. To accelerate our proteoform roadmap, we effectively tripled the number of people and resources focused on proteoform development, and we set a goal of developing 20 proteoform assays by the middle of 2028.

That plan is now in motion, and two things give me confidence in where we're heading. The first is the pull we're seeing from the scientific community. Second is the evidence that we can execute against our roadmap. Let me take each in turn. On the pull from the community, at this year's HUPO World Congress, the leading global proteomics meeting hosted by the Human Proteome Organization, proteoforms were such a pervasive theme that one article covering the conference in Chemical & Engineering News ran under the headline, "Proteins Don't Exist: Scenes from HUPO 2026." We also hosted a panel with three leading researchers whose labs develop and apply some of the field's most advanced protein analysis technologies.

Birgit Schilling of the Buck Institute for Research on Aging, Jochen Schwenk of KTH Royal Institute of Technology, and Bernd Wollscheid of ETH Zurich to ask, "Will proteoforms change our understanding of biology?" I want to share some of their perspectives. Dr. Schilling put it simply, "My thought is proteoforms are critical everywhere. These proteoforms influence function. They influence really everything that makes a cell work." Dr.

Wollscheid also noted, "We operate under the assumption, like everybody else, there are no proteins, only proteoforms. And I think we have an opportunity to not only decode individual proteoforms, but also individual proteoform-specific complexes which have functional relevance." When we ask what customers need, they consistently want more proteoforms, more sample types, and more applications. A great example came when we announced our partnership in the SEEDS Consortium.

SEEDS is funded up to $51.7 million by the Advanced Research Projects Agency for Health, or ARPA-H. We expect to receive up to $6 million over the four-year program to apply our Voyager platform to tau in Alzheimer's disease and EWS-FLI1 in Ewing sarcoma, our first work in pediatric cancer. The data is expected to help train AI models on disordered proteins, which today's models handle poorly. Our work with both SEEDS and the Michael J.

Fox Foundation are early examples of a broader opportunity, large-scale studies coupled with custom development. As we work more deeply with pharma, we expect partners to want to build assays for their own targets beyond what's on our price list. We're ready to build those assays and to help apply them across large cohorts. Turning to the second reason for my confidence in our plan, our track record of early execution.

At HUPO, we shared first data from three of our oncology proteoform assays targeting AKT1, EGFR, and P53. To put the results in context, first, let's go back to tau. We believe it delivers some of the most reproducible, detailed proteomics data in the world, both internally and with our partners at the Buck Institute, the Voyager platform delivered a median coefficient of variation, or CV, of 5.5%. That reproducibility is what makes our data trustworthy and scalable and makes it possible to build AI on top of it.

After about a year of development, AKT1, EGFR, and P53 are already performing in line with tau, our most mature assay, which took roughly five years to build. Median CVs were 8.8% for AKT1, 3.6% for EGFR, and 6.6% for P53, all well below our 10% target and far better than industry norms closer to 25%. That is a remarkable result. It tells us our core capability carries over from one target to the next, and it gives us confidence in the development of all three assays and the ones behind them.

Stepping back, we have accomplished a great deal this year. We launched our Early Access Program and brought in our first Early Access customers, including Baylor College of Medicine. The Michael J. Fox Foundation is funding the development of an alpha-synuclein proteoform assay for Parkinson's disease, and that work is well underway. We recognized our first revenue from both the Early Access Program and the MJFF grant.

In Q3, our tau proteoform work was published in Nature Methods, a peer-reviewed validation of the Iterative Mapping method, and accompanied by a News & Views article in the same issue. In the News & Views commentary, Albert Heck of Utrecht University wrote that Iterative Mapping might be a valuable platform that could even be used clinically to assay tau proteoform landscapes, supporting diagnosis and stratification of disease subtypes, and potentially even assessing the effect of therapy. It can be adapted to measure the proteoform landscapes of other proteins.

In a small cohort analyzed in the paper, tau proteoform analysis distinguished people with Alzheimer's disease from cognitively normal individuals, and the clearest signal came from proteoforms with as many as four phosphorylations on the same molecule, information a single site measurement cannot capture. Rounding out our accomplishments year to date, we moved three oncology assays into development and shared their first data. We were selected to participate in SEEDS, and we remain on track to place our first beta unit this year.

Looking ahead, here's what you should expect from us in the next several quarters. We expect to bring our AKT1 proteoform assay into Early Access in late 2026. We're working with our Early Access partners to generate additional tau data, and we look forward to sharing those results as they're published. In early 2027, we expect to announce the commercial launch of the Voyager platform and open for pre-orders. In mid-2027, we expect to begin instrument shipments and introduce general availability of our tau and AKT1 assay kits, as well as general availability for a second oncology assay.

We expect additional assays to be available through Early Access at the same time, so customers can begin generating data on them right away, and we plan to follow by introducing more kits in late 2027. Between now and general availability of our consumable kits in mid-2027, we also expect to reduce our sample input requirements by roughly 100-fold. We anticipate this improvement will enable us to measure extremely low abundance proteins in biofluids, such as blood.

Putting all that together, we believe our commercial path is not dependent on any single future application, and that proteoforms, on their own, represent an incredibly compelling business opportunity. The scientific need is real, the data shows we can deliver, and the instrument assays that bring it to customers are maturing into commercial-grade products. With that, I'll turn the call over to Anna.

Thanks, Sujal. Our results this quarter reflect where we are as a company. In an early commercial phase, with revenue coming from early access services and grant funding, and the commercial launch of the Voyager platform still ahead of us. We are encouraged by the engagement we are seeing across academic and pharma customers and collaborators. Total revenue for the third quarter was $200,000, consisting of grant revenue for our Michael J.

Fox Foundation funded alpha-synuclein proteoforms assay development and service revenue from our early access program. As a reminder, early access is our initial phase of commercial engagement, focused on serving our first customers and delivering the highest quality data possible. Working through the operational details of each engagement is exactly what this phase is for, and what we're learning reinforces our confidence that our pricing and margin expectations for the commercial platform are achievable over the long term.

In Q4, we expect revenue to again come primarily from grant funding and early access services. With our participation in the SEEDS program, we expect to recognize grant revenue as the work is performed over the four-year program. Excluding any potential contribution from our ARPA-H funded SEEDS work, we expect fourth quarter revenue to grow sequentially from the third quarter, driven by year-end early access activity.

As a result, we now expect total 2026 revenue to exceed our prior outlook of approximately $500,000. Total operating expenses were $16.9 million for the third quarter of 2026, an increase of approximately 10% from $15.5 million in the prior year period. Research and development expenses were $10.2 million, up approximately 6% from $9.6 million in the prior year period, driven primarily by higher personnel costs and higher laboratory and professional services costs as we advance our proteoform assay development.

Selling, general and administrative expenses were $6.8 million, up approximately 15% from $5.9 million in the prior year period, driven primarily by higher legal, marketing, and personnel costs. Net loss for the third quarter of 2026 was $15.6 million or $0.12 per share, compared to a net loss of $13.6 million or $0.11 per share in the prior year period. We remain disciplined in how we manage expenses and cash, and we expect full year operating expense growth in the single digits.

We ended the third quarter with $114.3 million in cash equivalents, and investments, compared to $129.2 million at the end of the second quarter, reflecting cash use of approximately $14.9 million in the quarter. Based on our current trajectory, we believe our financial plans support the cash runway that extends into the first quarter of 2028. Finally, on capital. As Sujal described, we believe proteoforms represent a significant market opportunity, and we see tremendous potential to begin capturing it by continuing to invest in our technology, capabilities, and team.

Our current runway gives us a strong foundation, and we are exploring the option to raise funds between now and mid-2027 to invest in three areas. Expanding our proteoform assay portfolio, extending the platform's capabilities, and building the commercial team to serve and scale our customer base. We are actively evaluating the right path to do so, one that positions Nautilus to capture this market and serves our shareholders well. Back to you, Sujal.

Thanks, Anna. Let me leave you with four points. First, we're making functional biology measurable. Proteoforms give scientists an entirely new layer of biological insight, and we believe our platform is uniquely positioned to deliver it. Second, Iterative Mapping is core to Voyager platform, and we'll continue to build on it with more assays, more sample types, and new applications like the one ARPA-H is supporting.

Third, we have confidence in our roadmap. The performance we've established on tau is carrying over to the next round of targets, and the funnel behind our goal of 20 assays by mid-2028 is in place. Fourth, proteoforms are the foundation of our growth strategy. With the Voyager platform approaching launch and a growing library of assays behind it, we believe we are well-positioned for the next phase of our commercial journey.

This year, we put proteoforms at the center of our strategy, proved our assays can scale from one target to the next, and earned validation from Nature Methods, the Michael J. Fox Foundation, and ARPA-H. The year ahead is about putting that capability in customers' hands, starting with pre-orders in early 2027 and instrument shipments in mid-2027. I've never been more confident in our team's ability to deliver. Thank you again for joining us today. With that, we're happy to take your questions. Operator?

Yeah. So good morning, Subbu. This is Sujal. The SEEDS program is separated into different program goals with different institutions, the Buck Institute and Georgetown leading the efforts for our part of SEEDS. Revenue will be recognized over the course of the four-year period as we complete work. I do not know if there is anything else you want to add on that, but I think those are the basics of it right now. We just signed that agreement to get going on it this week here, and so we will look forward to getting started shortly.

Yeah, let me try to address your AI question a little bit more broadly. I think that if you look at the industry, there is definitely a huge AI wave, and a lot of it is very real. A little bit of it is hype today. If you look at the areas where AI has been really successful in 2026, there are some areas in biology it has been successful. For example, this lab-in-the-loop concept, which enables you to design experiments, learn from them with AI, design the next experiment with AI, and iterate faster.

There has been good success in antibody design and small molecule design. At the end of this year, if you look at the state of things, we are just now seeing companies that are formed and are trying to take large cohorts and analyze them for genomic information or for proteomic information to try to discover trends and learnings that we have not been able to discover with humans. Our view is that that last piece represents a huge opportunity, but the training set required for frontier models does not yet exist.

Because if you look at the training set that you could get with mass spectrometry-based proteomics or with traditional assays that are affinity-based proteomic products, the data between the various techniques does not agree. The CVs are 20%, 30%, even 40% in many cases. If you cannot even agree on what proteins are in a sample, how are you going to understand what is upregulated, what is downregulated? What are the minute changes that are occurring?

That is where we see Nautilus's opportunity. The proteoform assays that we are building are doing two things. They are providing an extremely high reliability, low CV, very precise measurement of what is going on with critical biomarkers in disease-relevant molecular pathways. The second thing we are doing is we are providing this layer of intelligence because we do not just see the biomarker in its gene-encoded form.

We see the modifications, the splice forms, the sequence variants, and we see those co-occurring on a single molecule. That is incredibly critical because each molecule has a different function, different degradation, signaling, different molecular pathways that it participates in based on the combination of those modifications. We are already seeing that with the early evidence that we are seeing with the Buck Institute and tau, with other early access customers, and now we are beginning that work in AKT1, and in the future with other oncology markers.

I think applying this proteoform technology to AI and frontier models on large cohorts is going to be a massive long-term opportunity that will be a driver for us. We are just at the beginning of that wave today.

Yeah, that's a good question, Subbu. Let me give you a little bit of perspective just to kind of tell you where the pipeline and commercial build is today. In March, we hired Amber Faust, who is our Head of Worldwide Sales. In April, we hired the two sales reps that we have in the company today. It's a sales team of three. If you look at April to the end of Q3, which we just reported, it's about six months. That team came on board.

They closed some of the early activities that we had before we had a sales team, related to tau and early access, and then they really began pipeline building for tau. Everything that we see in the pipeline today, for the most part, is really tau-related. As Anna talked about in her prepared remarks, the pipeline is strong enough that we can predict today that we do expect revenue to grow sequentially in Q4, even without any contribution from SEEDS, the ARPA-H grant.

We're seeing good trends in terms of pipeline growth on tau, and keep in mind, it's still early, right? It hasn't even been 60 days since our seminal Nature Methods publication. The team is just building pipeline. As we start to look at our Q4 activities, a lot of those activities are still related to tau, but we're beginning the activities related to AKT1. As I said on our previous earnings call, we have a small sales team today, but they're a mighty team.

They all know the proteomic space really well, and we're confident that they're able to handle both the neurodegeneration and oncology activities over the course of the next couple of quarters. But you should expect that we are going to continue to grow that commercial team in 2027.

Yeah, Dan, I can speak to that. We aren't giving guidance on, or disclosing the number of customers, but I think what we can say is reiterating what Sujal just said, is that the sales team, when they first came on, they had to prosecute the pipeline that we had and largely build their own pipeline. From what we are seeing in the pipeline today, we have the confidence to be able to say that we expect early access services revenue to grow in Q4. Then keep in mind, next year, we'll have the oncology assays in addition to tau that will drive customer acquisition from an early access standpoint.

Yeah. Dan, let me answer the question in two ways, right? Because you asked about launch, and there are two milestones that are key for next year. One is the launch of our instrument, and that is really about getting pricing finalized, final specifications out in the world, and getting ready to take pre-orders. Then the second is the big milestone, which is the actual ship in the middle of the year. Obviously, the launch just depends on the ship being on track.

In order for the ship to be on track, we are planning to ship a beta unit here this year. We are planning to get it operationalized and prove that the final instrument is fully capable, it is reliable, it does what it needs to do. The intention is, in the middle of next year, we are shipping instrument consumables, we are shipping our software platform, our cloud portal, and we are shipping a set of applications. Expected to line up with that launch, generally available, is our tau assay, our AKT1 assay, and the second oncology assay.

In addition to that, we expect a third oncology assay and somewhere around another four to five proteoforms that are in early access or just about to get into early access at that time. For us, there is a significant amount of content that is available for customers to consume to drive those instrument purchases. All those things being on time is our launch criteria, and I think that our execution in Q3 shows that we really are capable of advancing these assays through our pipeline quickly and still meeting the performance criteria, which is industry-leading, that we first demonstrated with our tau assay.

If you look at our assays today, we keep saying second and third oncology proteoform because we are not committing to what those are yet. If you look at our current state, AKT1 is in verification and validation, EGFR is in late development, and P53 is in development right behind that.

Dan, it's a good question, and the launch will look, in our minds, it will look a lot like other disruptive technologies that are life science platforms that get introduced. You could look as inspiration to products like 10x when they first came to market with their single-cell genomics platform. You could look at products like Berkeley Lights and others as they got going. Berkeley Lights I mentioned because their price point was around $2 million per instrument, so it's got a price point much higher than where we were.

Generally what happens is, from what we observe, is that there's a new data modality, something that's bringing novel insight to the customer. Customers who are early customers in the academic and nonprofit research side often will apply for grants. They'll go get those instruments, and they'll bring them in. The difference between successful companies and those companies which don't achieve a high degree of success is how useful is the information that you get out of the platform?

How actionable is it? Does it help you to build better diagnostics? Does it help you to accelerate drug development programs or to improve the efficacy of drug development programs? For us, we expect that because this data is first of kind data that no one on the planet has seen, there's going to be great interest for the platform. We expect, given that these proteoforms are critical to understanding disease pathway, critical to understanding how proteins are functioning within a cell and signaling within a cell.

They're critical to understanding where in the cell the protein is. Is it on the cell surface? Is it in the nucleus? Is it in one area or the other? We expect the data is going to be really important to drug discovery and to diagnostics. It's not because we just think that. We're hearing that from the scientific community. We heard that at World HUPO from the KOLs who are on our panel and from others who visit us at the booth or had meetings with us.

That's sort of at high level how I think things will roll out. For 2027, I think that we have a sort of measured approach. We're going to get launched. We're going to have a few assays that are in early access, or sorry, a few assays that are in general availability, some others in early access. We're going to have to build funnel for the instrument purchases. Today, if you looked at our funnel, it's for both early access services and the very beginning of a few conversations around instrument.

The funnel does represent all three sectors, academic, nonprofit research, and pharma. That's a good thing, right? For the most part, the grant funding cycle for instruments, the S10 grants, is largely behind us for 2027 grant funding. That means that we're going to have to go after pharma and philanthropically funded types of projects. There are plenty out there, but those are the things that we're dealing with for 2027.

As we get to 2028, I think things will be much more open for us as a company. One, we will be working hard with customers for the S10 grant cycle in 2027 so that the grants come out in 2028. In addition to that, we'll have much, much more content available as we start to move through 2028. We'll have something closer to 10 assays starting in 2028 and exiting with 20 or more proteoform assays. That's sort of how I think it'll roll out. I think that 2027 is a year where we set the foundation, and 2028 is a year where we really go and scale the business.

Yeah.

Yes. Good morning, Michael. Why don't I let Parag walk through some of that?

Hi, Michael. That's a really great question, and I think we've been excited by the diversity of use cases that we're seeing. In general, I would categorize them into sort of three buckets. One is fundamental mechanistic biology. Two is disease biology, particularly associated with therapeutic development, mechanism of action type studies. Then three are really the foundational building blocks of biomarker discovery.

We saw that, for example, in the work that Taylor from NSCI presented on our webinar recently, where she was looking at the diverse model systems that are used in the field, particularly for drug screening studies. Today, if you look at those diverse model systems, you have iNeurons, you have stem cell models, et cetera. By just about any preexisting measure, they are indistinguishable despite the fact that they have very different responses to different therapeutics.

When she was looking and studying them using our platform, it was clear immediately that they actually have very different forms of tau. The proteoforms of tau are different. They change over time as the systems mature and age. That's a level of detail that is critical to understand how drugs will function in those models. But today, pharma companies can't really tell them apart, so they're sort of picking all of them or picking at random.

That was a really exciting study to be able to say, "Oh, okay, well, here's why they're responding differently. They actually have fundamentally different flavors of tau." Another sort of very interesting question that we've seen from our early adopters has been trying to understand how there's a challenge in Alzheimer's disease known as selective vulnerability. This is that Alzheimer's disease starts in one part of the brain and moves to other parts of the brain in a very specific manner.

Again, big open question, and understanding how the forms of tau differ across the different brain regions, and we're seeing very strong evidence that there are different flavors of tau in different parts of the brain. The last point I'll just call out is really one that gets to biomarkers and maybe even prevention, the therapeutics. A study done by our collaborators at the Buck was looking at this APOE genotype, which is in a lipid biosynthesis pathway.

It has basically nothing to do with tau, but it's one of the strongest markers for Alzheimer's disease. So people who have one mutation, are likely to have Alzheimer's disease by the time they're 45. A different mutation is incredibly preventative, people are at extremely low risk. But the connection to the mechanism of Alzheimer's disease was previously unknown. In some of their very first studies, it became clear that there were double and triple phosphorylated forms of tau that were associated with these mutations in a protein, in a completely different pathway, in a completely different part of the cell.

So really the first link between this key genetic driver of Alzheimer's disease and the actual pathology of the disease. Maybe one last anecdote for you is really thinking about stratification. One of the major challenges that we have in neurodegenerative diseases is that people may have one neurodegenerative disease, Alzheimer's disease, or they might have mixed pathologies. Most patients have mixed pathologies, where they have a mix of supranuclear palsy, or they will have Parkinson's disease and Alzheimer's disease.

So that makes drug development extremely challenging because you are developing a drug ostensibly for Alzheimer's disease, but your cohort in your trial contains mixed pathologies, then maybe the drug fails, not because it doesn't work on Alzheimer's disease, but because the patient cohort that it's being explored on has either one of multiple different neurodegenerative diseases that typically can't be disentangled until postmortem. So there are active studies going on to try to understand these mixed pathologies and differentiate them.

I think you hedged the question for us appropriately, which is that it's early for us. The primary changes in our pipeline are due to the fact that our team is just getting outreaches done, getting out there. We've had less than 60 days with the Nature Methods seminal publication to go out to customers and show the power of it. So I think those are the types of activities that are largely driving the funnel increase as we head into Q4.

With respect to customer sentiment, what I'd say is I think customers are still nervous about NIH funding in general and other sources of government funding. But I would say that funding still seems to happen, it's still moving forward. I think that S10 grants in particular for large instrument purchases is something that is a little bit more unknown than funding of other sources. So it's something that we're paying particular attention to helping customers next year get those grant proposals in so that we've got continued momentum in placements of instrumentation in 2028. So that's what I would say about it. I think for us, we're less sensitive to it because we're so early.

Thanks, Michael. Happy to speak to that. For the most part, our projections on cash runway into Q1 2028 are primarily around our investments in expanding our proteoform portfolio, getting ready for instrument launch, and investing in our commercial team and market development. Of course, we anticipate that capital spending grows along with our spending, but we are not seeing any material CapEx investments either in production facilities or facilities in general or equipment. Those are things that we would do in a very targeted way, and ultimately, it is not material from a cash burn standpoint.

Hi, Max. Yes, that's right. The SEEDS Consortium work includes a couple different elements. It includes running our existing assays for tau in both tissue samples as well as model systems. Then, to your point, as well as in biofluids. It also includes building a new assay for running in tissues and biofluids for developing a biomarker assay for EWS-FLI1 cancer-specific biomarkers. It includes a third piece as well, which is further platform optimization and development.

I think number one that I see is that we are making a measurement that literally no one else in the world can make. There simply does not exist another technology in the world that is capable of single molecule resolution proteoform analysis at scale. We're hearing that message resonate very loudly. We're hearing people saying, "Well, obviously, this is how biology works, and we've always wanted to be able to measure it," and they're excited about the opportunity to be able to look at this critical aspect of biology.

I think in terms of how this is affecting our launch strategy, I think it really is validating our thesis that when we talk to people, what they care about are two things. They care about increasing the content, what proteins we're measuring, what additional proteoforms we're measuring. Then they care about capabilities, things like increasing sensitivity, decreasing sample input requirements, moving to different types of matrices, sample types.

You mentioned biofluids earlier, so that's really driving our next stages of development is those two dimensions, increasing the content and increasing the capabilities. I'd just like to emphasize that in both of those dimensions, those really are just changes in the consumables on the platform. The instrument was designed to have a tremendous amount of functionality and capability, so we're able to address those desires from the market through changes in reagent kits.

Max, this is Sujal. Just to add a little bit to Parag's response. One piece to your question was how does it inform our launch strategy? I wanted to highlight that long-term success for Nautilus is about taking each application tau, AKT1, EGFR, and so forth, and showing and demonstrating for customers that there is real biological insight here that is critical information that's necessary for improving the efficacy and speed of drug development for the next generation of diagnostics for disease diagnosis, therapeutic response monitoring, therapy selection, MRD.

That's the goal for us. If you look at all of our activities today, early access, the collaborators, Michael J. Fox, ARPA-H, all of that has the end goal of giving us the biological information package that we can use to demonstrate to customers that there's a significant amount of utility in these applications that we're selling. That will sell more consumables, it'll sell instruments. When I talk to investors, one of the things that I highlight is that look at the activities we're doing today.

Look at the types of partners that we have, how important are these partners in the community, and what are they doing with our platform? Because that's going to inform the future growth rate of our platform. One of the things I was most encouraged about at HUPO this year was not just the number of conversations, but the quality of conversations around proteoforms and their importance to biology and what that means for each of the scientists that we talk to in their labs and in their development programs.

Yeah. Max, I think that the way I would answer your question is, I don't think about Tau in a vacuum. We absolutely expect that at the middle of next year, when we ship instruments, concurrent with that ship, we will have the Tau assay, AKT1 assay, and another oncology assay in general availability concurrent with the instrument. We will have a third oncology assay and another set of four or five in early access or just about to reach early access.

We think that's a significant enough amount of content to begin driving instrument demand. We think that consumables will likely. Not on this call, but on the previous call, we had said that we think that the instrument makes sense from a financial perspective for customers versus using services through a core laboratory, Nautilus, when they're going to scale to about $500,000 of consumable pull-through annually on the instrument.

We think that's going to take some time for a customer to get up to, but we certainly think that having a few assays in general availability and a big pipeline of deliveries of additional kits in six months is going to be enough content to keep these instruments busy.

Thank you, Max.