Good day and thank you for standing by and welcome to Nautilus Q2 2024 Earnings Conference Call. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today to Ji-Yon Yi, Investor Relations. Please go ahead.

Thank you. Earlier today, Nautilus released financial results for the quarter ended June 30, 2024. 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 Investor Relations at nautilus.bio. 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, July 30, 2024. With that, I'll turn the call over to Sujal.

Thanks, Ji-Yon, and welcome to everyone joining our Q2 2024 earnings call. The update that Parag, Anna, and I will be sharing with you today is due to the great work of our teams in the Bay Area, Seattle, and San Diego. My thanks go out to them for their continued progress against our key scientific and business objectives. I look forward to the day that their work is in the hands of researchers who will leverage our platform to explore important biological questions once thought unanswerable. The team remains focused on both our development milestones and commercialization goals. Through these and other efforts, we remain motivated by our purpose to revolutionize proteomics in the name of improving the lives and health of millions of people around the world. Our entire team is motivated by this goal, fully aligned and committed to doing what it takes to make this a reality. As you've heard me say on previous calls, to deliver a range of long-discussed and long-desired improvements in human health, we believe biomedical research needs a dramatic acceleration in targeted identification and therapeutic development. We believe we are pioneering a fundamentally new approach that holds the potential to overcome the limitations of traditional and peptide-based analysis methods and unlock the value of the proteome, both in targeted proteoform analysis and broad-scale discovery, something we continue to view as one of the most significant untapped opportunities in biology today. As you'll hear from Parag in a few moments, KOLs are enthusiastic about the data that we shared at this year's U.S. HUPO conference. In fact, several have begun to discuss with us the specific initiatives against which they plan to apply our platform. In Q2, we saw continued progress against core development goals for each of the components of our platform, and I look forward to additional progress towards commercial launch in 2025. For a more detailed R&D update, let me now turn the call over to Parag. Parag?

Thanks, Sujal. You may remember that during our last call, I reported on the promising data we released at U.S. HUPO late in Q1. Among other things, we shared how by exploiting the core capability of our platform to iteratively probe individual protein molecules, we were able to measure 32 distinct tau proteoforms from control samples. We also demonstrated the ability to perform measurements of enriched cell lysates. These results are the foundation of future assays which will be accessible to the broader biological community enabling more detailed investigation into molecular mechanisms of diseases like Alzheimer's and other pathologies. In addition, they suggest new frontiers in diagnostics. As proteoforms are not yet widely discussed outside of the proteomic research community, let me take just a moment to define what they are and why they're important. The term proteoform was introduced by Lloyd Smith and Neil Kelleher in 2013 to be used to designate all of the different molecular forms in which the protein product of a single gene can be found, including changes due to genetic variations, alternatively spliced RNA transcripts, and post-translational modifications. We know from examples like signaling molecules, cyclin-dependent kinases, oncogenes, and histones that what makes proteoforms an important driver of biological outcome is not just that a protein has a mutation, a splice variant, or a post-translational modification. What matters from the perspective of biological relevance is the combination and pattern of those modifications. The result is an exponentiation and complexity of proteins' actions that have tremendous potential to alter the behavior of a biological system. Researchers seeking insight into the role that proteoforms may play in, for example, the progression of Alzheimer's or other neurologic diseases have been limited by a lack of robust and accessible technologies to measure proteoforms at scale. Approaches such as Western Blots and Digital ELISA assays can only measure one post-translational modification at a time, typically as a bulk measurement averaging across collections of molecules. When there are potentially millions of patterns of modifications across billions of protein molecules in a sample, being able to measure one modification yields very limited biological insight. Other technologies such as bottom-up shotgun mass spectrometry or frankly any peptide-centric technology are simply unable to measure proteoforms as they cannot recognize that multiple alterations were present on a given protein molecule. These methods also cannot measure modifications at low concentrations. In general, measuring protein presence at low concentration is hard, measuring particular variants of proteins that are at even lower concentrations is exponentially harder. But it may be that these low abundance proteins and proteoforms hold the keys to unlocking new, more effective drugs across a range of indications. To date, the majority of proteoform studies have been performed using top-down mass spectrometry. This technology is the basis of ongoing efforts to build a proteoform Atlas. However, though powerful, this technology is extremely complex and unlikely to be broadly accessible to the wider biological community. The limitations in existing technologies have prevented meaningful analysis of what is believed to be an extraordinarily complex interplay of diverse proteoforms. This gap has inhibited meaningful understanding of disease mechanisms and drug actions. In addition, examples like troponin and prostate-specific antigen, PSA, have shown how proteoforms can serve as powerful biomarkers. Creating a technology to see these proteoform patterns and measure their relationship to one another has the potential to hugely advance biomarker identification, drug discovery and development, and precision medicine. We believe that the Nautilus platform holds precisely that potential. The single-molecule capabilities of the Nautilus platform, combined with the system's dynamic range, sensitivity, and ease of use, enable researchers to reveal and leverage extraordinarily valuable proteoform data that has never been available. In concert with our team's continued focus on the platform's broad scale discovery capabilities, we're concurrently creating proteoform assays that quantify at scale, the functional proteoforms present in the sample. Tissue and cell lysates initially, with blood and CSF to follow, in a way that has not been possible with the bulk analysis methodologies of the past. Since we announced our preliminary proteoforms data at U.S. HUPO, we heightened our focus on proteoform development activities, primarily in response to, as you'll hear from Sujal in just a moment, an enthusiastic reaction to the data from the research community. Specifically, based on the experimental work done in Q2, we have been able to reproducibly quantify mixtures of proteoforms, improve our assay performance, and successfully extract, enrich, and detect proteoforms from humanized mouse brain. We have also demonstrated that those patterns of proteoform abundances can be shifted with biochemical perturbations, such as by kinases and phosphatases. This latest data demonstrates the platform can be applied to important biological questions in relevant biological samples. We are very excited about our progress on this front and look forward to updating the community further at the HUPO World Congress in late October. As I wrap up, I want to emphasize the fact that any advances made to our core platform accrue value to both our targeted proteoform detection capabilities and our broad-scale discovery capabilities. Both modes of the platform rely upon a single-molecule library preparation, nano-pattern chips supporting super deposition of that library, iterative probing of individual molecules with fluorescently labeled affinity reagents, and machine learning software to infer molecule identities and quantities. In Q2, in addition to meaningful advances in our proteoform assay capabilities, we continued to make progress against our core and broad-scale development goals. We remain focused on increasing scale, stability, and reproducibility across our consumables, assay, and platform. And continue to see meaningful gains along those and related areas. In particular, this quarter saw the successful execution of the large-scale experiments we've performed to date. This progress is in lockstep with advancing the reliability, quality, and customer readiness of our instrument and software. With that, I'll turn the call back to Sujal.

Thanks for the update, Parag. I could not agree more with Parag's enthusiasm for our progress in detecting proteoforms and the substantial impact we could have initially with tau on the efficiency and cost-effectiveness of biomarker discovery and drug development in Alzheimer's and other neurodegenerative diseases. This progress represents a perfect example of our platform's unique ability and our continued focus on enabling both targeted proteoform analysis and broad-scale discovery proteomics, that understanding of the platform's dual value is shared by others. Extensive voice of the customer work done since U.S. HUPO, during which we previewed our latest data shows enthusiasm for targeted proteoform analysis from both academic researchers and pharma for use in drug targeting and drug discovery efforts. In fact, one high-profile KOL said as part of our VOC interviews that he believes building a reference database containing millions of proteoforms will transform biological research and health care. We share his and others' enthusiasm about the potential here and are energized to generate and share additional high-value data. As Parag mentioned, our next significant opportunity to educate the community about the platform and our progression towards commercial availability will occur when Nautilus participates as a top-level sponsor of this year's HUPO World Congress, October 20 through 24 in Dresden, Germany. As we've previously discussed, my management team and I, in fact, the entire Nautilus team continue to proactively manage our resources to maximize our cash runway while balancing that with investments to drive our scientific progress forward. As of the end of last quarter, we still hold on our books over half of the cash that we've raised in our 7.5 years as a business, and at our anticipated 2024 run rate, we expect to be resourced through commercial launch. For more on that and other financials, let me hand the call over to Anna. Anna?

Thanks, Sujal. Total operating expenses for the second quarter of 2024 were $20.8 million, up $1.8 million compared to the second quarter of 2023 and $0.8 million below last quarter. This 9% increase in operating expenses year-over-year was driven primarily by continued investment in personnel and their activities towards the development of our platform, as well as investment in personnel and services engaged in maturing our business operations. Research and development expenses in the second quarter of 2024 were $12.4 million compared to $11.9 million in the prior year period. General and administrative expenses were $8.4 million in the second quarter of 2024 compared to $7.1 million in the prior year period. Overall, net loss for the second quarter of 2024 was $18.0 million compared to $15.8 million in the prior year period. Turning to our balance sheet; we ended the quarter with approximately $233 million in cash, cash equivalents, and investments, compared to $248 million at the end of last quarter. As our Q2 results show, we continue to tightly manage our spend. Given our operating expenses in the first half of 2024, combined with our spend expectations in the second half, we anticipate our total operating expense growth for the full year to be between 15% and 20%, well below our previous guidance of 25%. Importantly, we remain committed to disciplined cash management and running an efficient organization as we execute our strategy to launch our revolutionary proteoanalysis platform. With that, I'll turn it back to Sujal.

Thanks, Anna. We're excited about what lies ahead for Nautilus and the difference we believe our platform can make. I'm grateful to our team, our investors, our strategic partners, and our research collaborators for joining us on this journey to revolutionize proteomics and empower the scientific community in ways never thought possible. We made good progress in Q2 and look forward to building on those successes as we move through the remainder of 2024 on our way to our expected commercial launch in 2025 and beyond. With that, I'm happy to open the call up for questions. Operator?

And our first question comes from Subbu Nambi from Guggenheim Securities.

This is Ricky Labidus on for Subbu Nambi at Guggenheim. Are you able to provide any further specificity on the launch timeline other than calendar year 2025? And if not, when would you be able to provide that insight? Is there a specific milestone that you might be looking to achieve? And then I have a follow-up.

Thanks, Ricky. This is Sujal. I’ll address this first. When considering the essential elements for our planned launch in 2025, it involves ongoing development efforts to integrate all our platform components and create approximately 300 reagents, consisting of multi-affinity probes and labels. These are necessary for identifying each molecule on our chip, determining the specific protein they are linked to, which gene they come from, and their type. We maintain our belief that 2025 remains an appropriate time for this launch. We have several development tasks ahead of us, including significant work on reagent development, qualification, and integration into our platform, and we’re still assembling all these elements. Regarding your question about the milestone for providing more details, I've mentioned previously that we have an upcoming milestone where we will present data at one of the HUPO conferences or another venue, demonstrating our capability to measure about 1,000 proteins or more from cell lysates, which means from complex samples. By the time we achieve this, most of our technology development will be complete, and we’ll have over half of the necessary reagents in place. Our system operates on an exponential scale, so this point will allow us to share more precise details on launch timing and product specifications. We expect this milestone to occur before our early access period, which will last around six months, leading into the product launch. Considering all these factors, while the launch in 2025 is likely not in the first half, things are looking favorable for our progress.

Great. And then a follow-up on the early access launch. Are there any updates or additional color you could provide on what strategy you're looking at for that beta testing? And what customers you'd be targeting?

Yes. So this is Sujal. And when you look at our early access programs, our early access programs' goals are, first and foremost, to give customers who have no variety in the proteomics world and customers who are proteomic savvy early access to our platform, so that they can generate unique and meaningful biological insight. And that biological insight has 2 goals. One is the value that we get out of it, publishing, bringing into conferences, papers, abstracts, posters, that value really is important to us because it provides the customer evidence that we need for the next stage of the business and for landing the first instrument deals and so forth. The second major activity that we want out of that early access program is really related to signing preorders for the instrument. And so when you think about those 2 goals, the types of customers that we will have in our early access program are very similar to the types of companies we're working with today on our collaboration. So it will be pharmaceutical organizations like Genentech, who we've been working with as collaborators for quite some time, and it will be academic and non-profit research organizations, particularly those that are proteomic savvy and the key opinion leaders in the proteomics world and then as well in there some diagnostic types of applications.

And the next question comes from Matt Sykes from Goldman Sachs.

Maybe just first on something that I don't think has been discussed in the last couple of quarters, just the bioinformatics platform that's going to be attached to the Nautilus instrument. Just curious, given how unique and novel the data sets that you're providing, the proteoforms for scientists are, could you just maybe dig a little bit more into the bioinformatics platform and what that looks like? And have you worked with customers to make sure that they get reports and data that's easily understandable, just given, again, how novel the information is to them, given the capabilities of the instrument?

This is Parag. I'll start with your question. Our bioinformatics platform has multiple layers. The first layer focuses on primary data and ensuring the quality and reliability of the experiments. We’ve created specific metrics to evaluate our data compared to standard mass spectrometry datasets. The second layer involves protein identification and quantification, where we provide access to primary data through simple spreadsheets containing protein identities, quantities, and false discovery rates, along with the ability to visualize the data in relation to users' own datasets. The third layer is comparative analysis, allowing for examination of different cohorts and case control studies, which is where we delve into biological insights. The fourth, and very powerful, layer is the integration of our data with other datasets. Our bioinformatics portal spans these layers, and we’ve conducted extensive customer feedback to identify gaps based on the sophistication level of our users, whether they have established bioinformatics processes or are at earlier stages. Common analyses users need include principal component analysis and volcano pathway analysis, and we are actively incorporating this feedback. Regarding proteoforms, this represents a new modality, providing unprecedented detail. Hence, we are also developing custom visualizations to help users explore the intricate details of individual protein molecules they haven’t encountered before. We consistently engage with customers to gather feedback and understand their needs, and the responses have been overwhelmingly positive.

Got it. And then Sujal, just as we look into '25 in the launch, it's obviously unclear what kind of NIH, NSF budgets may or may not be, but there's clearly some concern that those budgets could be somewhat compromised next year. I think you've stated in the past that you feel like the novelty of the instrument will likely penetrate through different types of budget environments. But just curious how you're thinking about the potential level of spend and budget for the academic end market next year and the various scenarios under which the NIH budget or the NSF budget could kind of be and what your go-to market if that would change it at all?

It's a good question. I believe my earlier comments remain relevant, as we are developing a highly innovative technology that offers unique and extensive biological insights, which no other tool can provide. This valuable data is essential for our customers. We are confident that, despite potential reductions in government funding through 2025, we can still succeed. However, when government funding faces downward pressure, it may result in longer sales cycles or complicate funding acquisition for organizations that depend on government support, particularly in academic and nonprofit research sectors. To address this, we plan to offer multiple pathways for customers to engage with our technology. These include outright instrument purchases, longer-term service models that may transition to purchases, instrument rentals, leasing options, and prepayments for consumables. We are open to these models should they assist customers in accessing our platform. One advantage of these alternatives is that we aim to recover our capital investment quickly, and since our revenue streams, including instruments, boast high gross margins, we generally have greater flexibility. If necessary, we will be prepared to adapt quickly in 2025 or 2026, depending on government funding trends.

Got it. And if I could squeeze one more in for Anna. Just on the total OpEx growth of $15 million to $20 million you said versus the previous guide of $25 million. What areas are you kind of achieving some level of savings to modify that guide that you had previously?

Matt, I can definitely speak to that. In our original operating expense plan, we had anticipated investments in a targeted way across all areas of the business. On the R&D side, we've had a few years of growth there. And so we've realized that we have the resources we need and we can limit further growth and just work with what we have. We've been reallocating resources from areas of the business to the areas of highest need. We've also brought down our cost of reagents in a way that offsets the growth in consumption of those reagents. That's what really has driven our ability to hold R&D expense growth a little bit lower. On the G&A side, we've found savings there as well. And as you know, we hold off on hiring the commercial team until we hit those product milestones. So the combination of those has really been behind the reduced OpEx guidance.

And our next question comes from Tejas Savant from Morgan Stanley.

This is Yuko. Would you talk about where you are in development progress for the instrument with respect to the launch target in '25? Would you say that development of city region is the gating factor at this point?

Parag, you want to take it?

Yes, this is Parag. I'll start. One of the aspects I'm really enthusiastic about, as I mentioned earlier, is our ongoing efforts to enhance the scale and quality of our large-scale experiments. These experiments involve a combination of many affinity reagents, numerous cycles, the latest chips, advanced instruments, and our main focuses are: firstly, the execution of these experiments, secondly, as Anna pointed out, managing the costs associated with them, thirdly, ensuring the reliability of each component in the system which includes consumables like nanoparticles for protein deposition, affinity reagents, and all the buffers along with bioinformatics. In the last quarter, we've observed a significant improvement in both the scale of these experiments and their stability, such as whether the chip stays clean after each cycle and whether the proteins remain mobilized. The latest data appears impressive, particularly regarding nonspecific binding background and removal efficiencies, all of which continue to improve. There has been very exciting progress in development.

Great. And then second question for me. Regarding development cadence to reach a milestone where you are able to measure, let's say, 1,000 proteins reproducibly to unlock greater visibility towards that specific development timeline, is this something that would happen fairly quickly once you hit a certain point like 100 proteins measured? Or is it something where development would move in a fairly linear fashion?

Yes, I can take this. Do you want to talk Parag and I'll take it from that?

Well, I'll just mention that one of the most exciting aspects of the platform really is this exponential nonlinearity in how the number of proteins decoded scales with a number of cycles. And so my expectation would be that there would be a very strongly nonlinear aspect to that. But Sujal, please get some color there.

Yes, that's right. I mean, I think that we've talked about this for a number of years. With any traditional platform that uses antibodies to measure proteins, you need 1 or 2 of those antibodies or affinity reagents to be able to detect each of the different proteins in the human proteome. Our technology is very different; with only 300 or so multi-affinity probes, as we call them, you're able to gather all of the information that you need from a particular molecule to almost with 100% certainty differentiate it from every other molecule in the human proteome and therefore, identifying it accurately. In order to make an accurate identification of just about anything from a complex sample, we have to have most of the probes and we have to gather quite a bit of information. And so once we cross over that point, you'll cross through 100, 500, 1,000, 2,000 proteins pretty rapidly because it really just has to do with getting more of those reagents on the platform. In terms of cycle count, Parag mentioned earlier that our large cycle experiments are performing quite well. And so we feel like the assay stability and reliability are there. And so now really, it's focused on getting the reagents that have the right characteristics on our platform to be able to put the entire set together to be able to get first, those early milestones that I talked about but then ultimately comprehensive proteome coverage.

And our next question comes from Tycho Peterson from Jefferies.

Maybe you could touch on the publication roadmap. How important is that out of early access that gets good publications? What should we be focused on there?

This is Parag. That's a great question. We see publications as essential for sharing information with the community and generating enthusiasm. Generally, we focus on two main types of publications. The first includes our PrISM manuscripts, which showcase how the platform operates. We consider these to be core demonstrations of the platform's capabilities and serve to help the scientific community understand its fundamental components and functionality. This represents the initial layer of publication. The second type involves applications, where we collaborate with our partners to illustrate how our platform can facilitate learning about specific biological aspects, demonstrating not only the individual components but also how they work together and perform in an integrated system. Beyond this integrated system, we have even more application studies where we explore specific biological questions using the Nautilus platform to uncover insights that were previously unattainable. We view this progression from components to an integrated system to biological applications as a multilayer framework that engages various communities from early to late adopters, fostering excitement about what the platform can deliver.

Great. And then you've had a number of questions on the tech development. I guess, Matt, obviously asked about informatics, maybe flipping it around upstream. Is there anything on the sample front we should be paying attention to in terms of kind of improvements there?

Absolutely. One key aspect of the sample preparation is the simplicity of the workflow, the amount of input material needed, and the degree to which the sample prep might influence the output. We've made significant progress on understanding whether the sample prep introduces any bias, particularly concerning the chemical processes involved and their impact on different classes of proteins. The data we've collected strongly suggests that the chemistry is quite general, which is very encouraging. We intend to share this data at HUPO. Additionally, we are examining the amount of input material required for proteoforms. There's an important question about the level of enrichment we achieve and whether there are biases in that enrichment concerning specific protein forms. We are also excited to share findings related to this topic at HUPO.

Okay. And then I want to follow up on the question earlier on funding. And Sujal, you mentioned may be entertaining leasing, reagent rental, other kind of types of business models. I'm just curious how seriously you're thinking about that and how we should think about your willingness to kind of carry the cost of the capital equipment on your balance sheet if you do move to a kind of reagent rental model?

I would say that our thinking on this is still in the early stages. For example, we haven't discussed this model with potential customers yet. I see these strategies as a way to facilitate instrument purchases, and we don't plan to keep the cost of the instruments on our balance sheet for an extended period. However, there may be unique situations where we want to use this model for specific researchers we wish to partner with. Given that the manufacturing and shipping costs for the instruments are relatively low compared to the sales price of around $1 million, I believe this approach is feasible, although we haven't conducted detailed analysis yet. As we approach launch and engage in discussions with customers about the capital acquisition cycle, we will be able to explore this in more depth.

Okay. And then one last one. On the diagnostics front, kind of a couple of angles here. Roche is obviously entering the clinical mass spec market. They're talking about blood-based tests for amyloid pathology in Alzheimer's. I'm just curious, how you think about them in the context of the space, how you think about kind of what needs to happen for the diagnostic market to open up more broadly? Will you guys go down the regulatory path to the box at some point down the road? Can you maybe just talk a little bit about how you think about the diagnostic opportunity evolving?

Yes. Why don't I start and then Parag can add any detail in here. I think that first and foremost, we think that the Nautilus platform is really important for the diagnostic world for really 2 categories. Number one, on the broad scale proteome side, our platform provides a dynamic range and a sensitivity which enables you to reach much rarer biomarkers in blood. And so if you think about biomarkers that are present in blood at low concentration, these are things that are shed from tissue, potentially from tumors. And so you really have to have a huge dynamic range of single molecule sensitivity to be able to reach all the way down to the lowest concentration proteins. And that, I think, is going to unlock new biomarkers that are going to be really interesting. On the proteoform side, as Parag talked about in his prepared remarks, the ability to detect an entire proteoform is a whole new level of biological insight. Today, the standard analysis that can be done with assays and with mass specs can detect protein modifications which is a single modification. For example, there is a modification on tau at site 217 with phosphorylation. But what you can't tell is there are 3 phosphorylations and they're at 3 different sites in this population and 2 different sites in that population. That proteoform information, we believe and many KOLs in the proteomics world believe will unlock a new type of biomarker and a new class of biomarkers that will be really important to diagnostics. And so we think that from a discovery perspective, finding those biomarkers enables Dx companies to do some really exciting things over the course of the next 2, 3, 4, 5, 10 years. The question around whether we will enter the clinical space with this product, not initially for sure. The first use cases of this product for a number of years will be all RUO use cases. And when a customer makes a discovery, we'll say, hey, great, customer, you found this great biomarker, now go build a high-throughput assay, go get it cleared through the FDA. And we're going to go onto the next research discovery. But there will quickly come a point where either the dynamic range of sensitivity of our platform or its unique nature to measure proteoforms will become a necessity and the customer won't have a way to really build an assay that replicates the finding that they made with the Nautilus platform. And I think that's probably the right point for us to start pushing the product through the FDA and moving towards clinical. I don't think that's in the first 4 to 5 years of shipping. I might be surprised, but I don't think it is. I think that those RUO use cases are going to be more than enough to fuel our growth for a number of years.

Our next question comes from Dan Brennan from TD Cowen.

Maybe just back to the timing of the launch. It appears to have slipped a little bit here from mid-'25 to, I guess, back half '25. Obviously, you guys are tackling a very ambitious goal with very novel single molecule protein detection and that's not surprising things can slip. But just given the series of slips that you've seen from end of '23 to end of '24 to mid-'25 and now back half '25, I'm just wondering, can you address kind of the key factors for the latest delay? And how should investors gain confidence that this won't continue to up, let's say, beyond '25 into '26 or even later?

Yes, thank you for the question. This is Sujal. I’ll start by saying that I don't see my comments today as another delay. Our last earnings call indicated we plan to launch in 2025, and we haven't changed that timeline. However, it's true that the process has taken longer than we anticipated. When we went public, we expected to be commercial by now. Developing something truly groundbreaking typically involves a long development phase filled with significant effort. As we approach the end of the year, it will have been eight years since Parag and I began working on this company and developing the product. It's been a long journey, but we are creating something truly innovative, including the ability to immobilize billions of molecules on a chip, develop a new class of reagents, and create an instrument and assay to cycle these reagents and gather data on individual molecules. This requires a tremendous amount of work, and we are making solid progress. Currently, we have an instrument capable of performing all necessary cycles to meet our launch targets and reliably conducting assays. The data quality is sufficient for measuring proteoforms, and we believe we will soon measure around 1,000 different proteoforms of tau. We also plan to engage more on the proteoform side ahead of the proteome launch. All of this indicates that the platform is coming together. You asked how we can be sure it won't be delayed further into '26 or '27. The truth is, no one has a definitive answer. My team and I closely monitor our R&D progress and compare it with past experiences. Everything points to us moving in the right direction and doing what we need to get the product out. I want to emphasize that Anna, the management team, and everyone at the company are focused on running the business efficiently. Despite the extended timeline, we've managed to significantly prolong our cash runway from our original projections for 2023 and 2024. In summary, I believe we are managing the business effectively and am very confident in our progress towards delivering this product to biologists worldwide.

Terrific. I know you also mentioned during the Q&A in the prepared remarks, you're making meaningful advances in Q2 on scale and stability. So could you just quantify that a little bit? I know in the past, you've talked about probes recycling, talked about a number of reagents to get to full coverage kind of where you're at. Can you just provide updates maybe on those metrics or whatever metrics you think are relevant to distill what the scale and stability advances that you saw?

Sure. This is Parag. We haven't disclosed the exact number of probes run, but you can infer it from the cycles we've reported. A couple of quarters ago, we demonstrated data showing stability in chip performance and removal efficiency at around 25 cycles. After that, we showed about 70 cycles at HUPO, and most recently at the U.S. HUPO, we indicated about 100 cycles. Currently, we expect to reach between 125 to 150 cycles soon. This illustrates the platform's stability and removal efficiency, meaning we effectively eliminate the reagent after probing so that it doesn’t linger. We also showed that the baseline of nonspecific binding was stable up to about 100 cycles, and we're extending that by another 25 to 50 cycles, which are critical metrics for data quality. Additionally, we've observed the degradation of signal over cycles. Years ago, we could only achieve about 5 cycles before the signal decayed, but now, with defined positive control cassettes introduced at 15 cycle intervals, we are able to maintain performance throughout the entire run. All these metrics indicate significant improvements in the platform's stability as we increase the number of cycles.

Got it. And then maybe a final one for Anna. So Anna, with the reduced burn or the reduced OpEx, I know you mentioned in the prepared remarks something about where the cash gets you through. But can you just provide an update there in terms of timing of how far your cash runway is now with the reduced burn?

Dan, thanks for the question. I can speak to that. The previous guidance which you're referring to, we said we had cash runway into the second half of 2026. Our reduced OpEx certainly helps us in achieving that target. With that being said, the second half of '26 is still 2 years away and our commercial build-out is yet to come. So I think, while we have the ability to extend cash runway further if necessary, we're not ready at this point to commit to that.

Just for the final point. So, I'll just add just that cash just the cash forecast that I gave you includes the product, building out a commercial team, launching, and starting to get into the revenue ramp before cash out. And those activities of commercialization are expensive. And so the question before was about if there was any further slip hypothetically, the runway on cash would elongate in that case because the commercialization build would get pushed out. I just wanted to make sure that I connect all those dots.

Got it. No, that makes sense. Thank you.

And thank you. And I'm showing no further questions. This concludes today's conference call. Thank you for participating. You may now disconnect.