Nautilus Biotechnology, Inc.

Good day and thank you for standing by. Welcome to the Nautilus fourth quarter and full year 2024 earnings conference call. At this time, all participants are in a listen only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during a session, you will need to press star one one on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, Jian Yi, head of investor relations.

Thank you. Earlier today, Nautilus released financial results for the quarter ended December 31st, 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 email to investorrelations at nautilus.bio. Joining me today from Nautilus are Sujal Patel, co-founder and CEO, Parag Malik, 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 27, 2025. With that, I'll turn the call over to Sujal.

Thanks, Jian, and welcome to everyone joining our Q4 and full year 2024 earnings call. Today, we'll provide a quick look back at our 2024 progress, update you on our work since the last call, and present our fourth quarter 2024 financial results. We'll then, as always, open the call for questions. As you know, our goal at Nautilus is to enable proteomics researchers to study the entirety of the proteome at a depth and breadth never before possible, and to make the creation, accessibility, and use of that higher resolution, higher quality data easy enough that it will be practical for every lab everywhere to accelerate scientific research, enable the discovery of new biomarkers, and ultimately power the development of new therapies and diagnostic tests that will positively impact human health. As you saw in this morning's press release, based on the desire to reduce technical risk and bring to market a product with the greatest possible performance, we now expect that the launch of our proteome analysis platform will occur in late 2026. Parag will provide detail on the rationale for that timeframe in a few moments. Since the achievements of last year serve as a foundation for the work ahead, I want to take a few moments to walk you through some notable recent accomplishments. But before I do, it's important to remember that we'll be discussing the status of our overall platform development initiatives and share detail on progress against each of the platforms' modalities, broad-scale discovery, which aims to comprehensively quantify the proteome, and targeted quantification, which is currently focused on proteoform detection. While both modalities share the same core platform, each has its own development pack. With that said, in 2024, we had a number of key demonstrations and progress with regard to the core platform. Among them, we developed improvements to the scale and quality of our reagent production, an instrument and an assay capable of multi-cycling reagents over many cycles and observing protein-binding events at the single molecule level, and software capable of processing the data coming off the instrument and through proprietary bioinformatics algorithms, turning that multi-cycle data into biological insight. With regards to our pursuit of broad-scale decoding, we developed a large number of probes that successfully bind epitopes spanning the human proteome. We also performed an ultra-deep characterization of a large number of probes to define detailed binding profiles and kinetics. Lastly, we demonstrated via WesternBlock that these probes can bind to and differentiate proteins successfully and that the results strongly correlate to our binding models. We also made progress on our integrated proteoform capabilities. At WorldHUPO last October, and as Parag reported on our previous call, we shared data on the world's first quantitative measurement of biological variation in tau proteoforms potentially associated with Alzheimer's disease. These preliminary findings have spurred substantive conversations with a number of potential partners interested in exploring tau proteoform landscapes at a resolution never before possible. Armed with the learnings and advances of last year and years prior, we now have greater clarity about what remains to be done to deliver what we believe will be a game-changing product to the market. We're focused on the good that we anticipate our platform can do and confident in our ability to get there. For more detailed updates on our R&D efforts, let me turn the call over to Parag. Parag?

Thanks, and good morning, all. As Sujal shared, in Q4 and throughout 2024, we continued to make progress against our core development goals. We remained focused on increasing scale, stability, and reproducibility across our consumables, assay, and platform, and continue to see meaningful gains along each of those dimensions. This progress goes -in-hand with advancing the reliability, quality, and customer readiness of our instrument and software along with advancements in our ability to investigate the proteoform landscape of tau. As Sujal mentioned, both our broad-scale discovery and targeted proteoform analyses are built upon the same core platform. As such, the movement from platform development towards platform application, demonstrated recently for our proteoform analysis, also serves as a general validation of our progress, developing a fully integrated -to-end platform that starts with sample-in, immobilizes that sample at the single molecule level, robustly interrogates that sample cycle after cycle, and then coalesces that data through a data analytic and machine learning pipeline, producing quantitative output that can be a foundation for unlocking biological insight. At USHUPO earlier this week, we presented several posters and a luncheon seminar, in which we demonstrated progress towards both our broad-scale discovery and targeted proteoform capabilities. On the proteoform side, we demonstrated successful development of a high-resolution single molecule tau proteoform assay to quantify the molecular heterogeneity of tau proteoforms, high accuracy and reproducibility with over three orders of magnitude of dynamic range, precise measurements of specific tau isoforms and phosphorylation levels in organoid model systems, and the first-ever measurement of tau proteoform profiles between neuronal model systems and the human brain that could be used to reveal markers of Alzheimer's disease pathology. These results demonstrate our readiness to engage in significant partnerships to explore the role that tau proteoforms may play in both drug and biomarker development. On the broad-scale side, we discussed the development and characterization of robust multi-affinity probes capable of binding to a variety of proteins, extreme sensitivity into the Yoctamole range, the potential for the platform to be applied not just to human, but to a diversity of organisms, and a new adaptive decoding algorithm that is able to account for -to-run variation in probe binding. In meetings with KOL throughout USHUPO and in interviews with a range of potential future customers over recent weeks, we continue to hear researchers discuss the value of data attributes that go far beyond just the number of measurable proteins. They consistently discuss the quality of data they seek and point to factors such as reproducibility, specificity, and accuracy. We discussed how there is a range of coincidences in proteomics data, which vary from proteins identified by essentially a single demultiplexed peak through highly abundant proteins that may be identified by a multiplicity of peptides. We additionally discussed how our approach is substantially different in confidence and quality relative to traditional affinity-based approaches. In which proteins are identified and quantified by one or two affinity reagents versus dozens. One particularly exciting moment for me came in discussions of our proteiform assay, when the researcher declared that our approach was something he had always wanted and in his opinion would revolutionize progress in combating neurodegenerative diseases. Moving on to our current R&D priorities. You'll recall that last quarter we reported that we are behind on our internal milestones with respect to our next major broad-scale goal. To be capable of quantifying a significant number, 500, 1000, 2000 proteins from a complex sample like cell lysate on the road to measuring the comprehensive proteome. This represents the last piece of validating the broad-scale capabilities of our platform. Our unique method of identifying proteins, protein identification by short epitope mapping or PRISM for short, involves the development and integration of hundreds of proprietary multi-affinity probes which interrogate single protein molecules. Over the last three years we have spent substantial time and energy building and optimizing our affinity reagent pipeline and building and characterizing thousands of probe candidates. These studies, over Q4 in particular, have given us increased confidence in the probes we have built with regards to their ability to bind to a diversity of epitopes within proteins, their ability to differentiate amongst proteins, a key requirement for decoding, and the predictability of their binding to proteins. One key ingredient in this was the large-scale screening of probes against millions of peptides drawn from the human proteome to define very detailed models of sequence specificity for each probe. We additionally did a significant amount of work on the binding kinetics of these probes and on testing how probes bind to dozens of different proteins through a range of techniques, including Western blot and bio-layer interferometry. Through that detailed analysis, we can confidently say that our affinity reagent pipeline does indeed produce probes with the characteristics necessary to implement PRISM. Alongside our extensive probe characterization efforts, we have been doing the hard development work to optimize and increase the robustness of the fluorescent labels used within our platform, the chemistry used to attach probes to these labels, the chip surfaces themselves to maximize specific binding, and the buffers used during binding and measurement. We additionally examined how diverse label types and labeling approaches impacted these metrics on a -by-probe basis. Internally, we defined criteria for transitioning probe candidates to platform-ready labeled probes. As we entered 2025, many of these probe candidates were not meeting the performance targets desired of platform-ready labeled probes. In an effort to decrease the fallout rate, in Q1 we focused on a number of new development workstreams related to our label, labeling approaches, assay buffers, and surface chemistry. The data from those experiments have made clear the need for us to optimize some elements of our surface chemistry and assay conditions in order to achieve better alignment between our probes and our assay in a way that will increase our confidence that a significant number of our existing and -be-developed labeled probe candidates can become platform-ready. It is clear what work is needed and how that work will translate into a simple and robust assay. However, appropriately testing these optimizations and integrating any subsequent platform modifications will require time not anticipated when the current launch timeframe was established. Thus, this evolutionary work will push back the anticipated timeline on our ability to quantify a significant number of proteins from a complex sample like cell lysate. While we are disappointed with this delay, we are encouraged by the large data corpus we've collected that suggests our probe library is capable of successfully implementing PRISM and thereby unlocking the proteome. With that, I'll turn the call back to

Sujal. Thanks for the update, Parag. Parag just outlined how the learnings of recent quarters have positioned us to pursue a development path with reduced technical risk and that we believe will yield the greatest possible platform performance, but at the cost of time. Based on the efforts required to implement these modifications to our assay configuration, surface chemistry, and related platform elements that Parag articulated, we now expect that the launch of our proteome analysis platform, Instruments and Reagents, will occur in late 2026. All along this development path, we envision significant scientific milestones and value creation inflection points for both modalities of our platform, targeted proteoform detection and broad-scale discovery proteomics. Here are a few examples. One, a major goal in the first half of 2025 is to provide leading researchers with access to our platform for tau proteoform-related studies. We firmly believe that 2025 will be the year that researchers begin to apply the platform's capabilities to ask and answer important questions about the role of tau proteoforms in Alzheimer's disease. Two, creation and publication of data showcasing the tau proteoform assay's performance characteristics, such as sensitivity, dynamic range, and reproducibility. Three, signing at least one tau-related partnership in the first half of 2025. Four, decoding of an increased number of proteins beginning with predefined mixtures and progressing towards complex samples such as cell lysates. And five, the sharing of data showcasing the broad-scale proteome assay's performance characteristics, such as stability, sensitivity, dynamic range, and reproducibility. We remain focused on driving our scientific and development efforts forward in the most efficient, most effective ways possible. By making the decision to pursue modifications to our assay configuration, surface chemistry, and related platform elements at this time, we believe that we are positioning Nautilus to ultimately make the maximum possible impact on the marketplace and on biological science. This elongated development timeframe necessitated that we reevaluate our operating plan and organizational structure to ensure that we are in the best position to execute against both our broad-scale and targeted proteoform goals. To that end, yesterday we reduced our headcount by approximately 16% in order to align the resources we need to pursue our development goals with the desire to extend our cash runway. Based on these difficult but necessary changes, and with ongoing very tight financial management of the business, we now anticipate that our cash runway will extend through 2027. For more on that and a full report on our finances, let me now hand the call over to Anna. Anna?

Thanks, Sujal. Total operating expenses for the fourth quarter of 2024 were $20.0 million, roughly equal to the fourth quarter of 2023, and $0.9 million above last quarter. This flat -over-year operating expense for Q4 2024 is a result of the focused and ongoing efforts of our team to identify better and more cost-effective ways to achieve our goals. Research and development expenses in the fourth quarter of 2024 were $12.8 million compared to $12.5 million in the prior year period. General and administrative expenses were $7.2 million in the fourth quarter of 2024 compared to $7.5 million in the prior year period. Overall, net loss for the fourth quarter of 2024 was $17.6 million compared to $17.0 million in the prior year period. For fiscal year 2024, operating expenses were $81.5 million, an increase of $5.3 million, or 7%, from $76.2 million in the fiscal year 2023. Both research and development expenses and general and administrative expenses also increased by 7% in fiscal year 2024. Net loss for the fiscal year 2024 was $70.8 million compared to $63.7 million in fiscal year 2023, an increase of 11% -over-year. As Sugil stated previously, we now anticipate the launch of our platform in late 2026. To ensure our cash runway well exceeds this timeline, yesterday we made the decision to reduce our headcount by approximately 16%, impacting all areas of the business. We expect this will result in limited one-time costs that will be recorded in the first half of 2025. While these steps will lead to cost savings in the short term, it will also allow us to invest in future business needs within a lower spending envelope. For fiscal year 2025, we anticipate our total operating expenses to be at or below 2024 levels. Turning to our balance sheet, we ended the year with approximately $206 million in cash, cash equivalents, and investments, compared to $264 million at the end of last year. The efforts we took in 2024 to limit growth and spending, combined with yesterday's workforce reduction, means that we now expect our cash runway to extend through 2027. With that, I'll turn it back to Sugil.

Thanks, Anna. Anna's report clearly demonstrates our total and continued commitment to very tight financial management of this business. We understand what it will take to get Nautilus to commercialization and have developed a culture of rigorous financial discipline that will benefit us both in the short term and the long term. We're excited about what lies ahead for Nautilus and the difference our platform can make in biological science. Our mission to positively impact the health and lives of people around the world remains unchanged and serves as the standard to which we hold ourselves. 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 before thought possible. We made good progress in 2024 and look forward to building on those successes as we move through development in 2025 on our way to commercial availability next year. With that, I'm happy to open the call up for questions. Operator.

Thank you. At this time, we will conduct the question answer session. As a reminder to ask a question, you will need to press star 1-1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1-1 again. Please stand by while we compile the Q&A roster. Our first question comes from Yuko Akul at Morgan Stanley. Your line is open.

Good morning and thank you for taking my questions. Could you further elaborate on your plans to modify the assay configuration and surface chemistry? What are the specific issues you're currently facing that these changes would address? And with these plan changes, has anything changed in terms of how you're thinking about initial specs of the platform at launch or your plans to continue to improve those specs with subsequent kits?

Good morning, Yuko. This is Suzhou. Why don't I start with this question and then I will take the second half.

Great. Thank you for the question. The key aspect of the assay involves a couple different components. One is that all are targeted at driving the specific binding of our affinity reagents to proteins that contain an epitope of interest and to differentiate the non-specific binding away from proteins that don't contain an epitope. Some of the key factors that influence that are, for instance, how those particular probes are labeled with a fluorophore. For example, if those probes are labeled in a way that is slightly suboptimal, you might end up conjugating a fluorophore into the binding region of the antibody and interfering with its ability to bind to its target. In addition, depending upon the surface chemistry, it's possible that as you add fluorescent moieties, you might drive towards non-specific binding. And so those are the kind of separations that we're working to enhance. And many different small factors can influence those assay configurations, such as how the surface is passivated, such as what the actual chemical structure of the fluorescent label is and how it is attached to the probe of interest.

Next slide. This is Sujal. Let me just take this. I can have your question, Yuko, which was related to specifications. And I think the key thing here that I want to point out is, well, there's two key pieces, right? One is the assay configuration change that Parag is discussing is really meant to allow us to get the large number of probe candidates that we have built and that we are building to have a higher yield where they function well on our platform and enable us to get the type of information that we need to decode the complete proteome. And so, you know, when we say in the prepared remarks that this is an approach that has less technical risk and allows us to optimize our performance, that's what we really mean, which is we're trying to get a much higher yield out of the probes that are developed already and the probes we're developing so that we can deliver a high specification in terms of coverage of the proteome. Now, in other parts of our specification, things like dynamic range sensitivity, the reliability of the instrument, I think that the additional time that it's taken us to develop our first instrument reagents, full commercial launch of our proteome product, that additional time gives us more time for those other areas to bake. And so we anticipate that those will be closer to launch spec or at launch spec or exceed launch spec by the time that we get out by the end of 2020 or late in 2026.

Great. That was helpful, Kolar. Thank you for that. And just a related question. Does the plan changes to the assay configuration or the surface chemistry change how you're thinking about cost structure of the platform or consumables? And is that one million bundled pricing still the right way to think about the price

of the platform? Yeah, that's a great question. In terms of what the changes that we are developing now due to our cost structure, they have no negative impact and may even have some positive impact, particularly on the consumable side in terms of cost. And with that, we do anticipate that our pricing is roughly correct based on the previous guidance that we've given you, which is that we expect that a instrument deal, which includes the instrument, the software, the services support, kind of the initial deal to get you going is roughly a million dollars. And sample costs will vary based on the configuration of the product and what you're looking for, but could start at a few thousand dollars per sample and then decline over time. And we think that those price points based on continued conversations with customers are the right price points given the differential data that our platform produces and the quality of

the data. Thank you.

Our next question comes from Subu Nambi at Gugaheim Securities.

Hey guys, thank you for taking my question. This is for you. I'm confused a little bit. Shouldn't surface chemistry be uniform for all proteins? And if TAU worked so well, why does that require optimization for different proteins? My understanding was you use the same surface chemistry. That's one. And then why should labeling of fluorophore to the FC region of antibody require optimization? Isn't that pretty standard as well? Hey guys, can you hear me okay?

We can, are you on mute?

I apologize. I was only able to hear the second part of your question. Could you please repeat the first part of your question?

Absolutely. So I'm confused a little bit. Shouldn't surface chemistry be uniform for all proteins? And if you were able to attach TAU to a surface, shouldn't we assume that it should be the same chemistry for all different proteins to attach on the chip? The second is labeling of fluorophore to FC region of antibody is pretty standardized. And how does that require optimization?

Sure. So maybe I'll, with regards to the surface chemistry and passivation thereof, really what we're not talking about the mobilization of the proteins via the nanoparticles to the surface. That you're absolutely correct that that is identical between any assay and speaks to how we immobilize proteins from the sample onto the chip. On the other hand, depending upon the labeling strategy, the number of cycles and the buffers, there are interplays between the fluorescent moieties that may be used to label the probes and their interaction with the surface. Different buffers may lead to increases in nonspecific binding to the surface or to other targets. Likewise, even factors like temperature and time of measurement can play into that differentiation between specific and nonspecific binding. And with regards to fluorescence labeling, you're absolutely correct that fluorescence labeling in general is a very well established method that there's a number of different conjugation chemistries for labeling of antibodies. Within our system, one of our key considerations is that we want to be able to perform the measurement repeatedly and we've shown hundreds of cycles of repeated measurement. And so maintaining that balance of specific binding cycle after cycle is something that we really have have optimized tremendously and that we believe further advancements in our configuration will allow for greater differentiation for a wide number of our probes. And really, this is about aligning the probe characteristics to the assay configuration.

Thank you for that, Bharad. Each protein is quirky, right? So how are you confident that whatever optimization you do is going to be applicable on a broad scale in terms of specificity?

Absolutely. So I think while each protein is quirky and internally in the building, we think of them as essentially their own beautiful snowflake. The optimizations are really about the interaction between a labeled probe and a protein. And at that point, that's really driven by, you know, very fundamental physics of binding, where if you increase the concentration, you increase the extent of on. If you increase the time prior to measurement, then you decrease the amount of bound. And so those fundamental kinetics of the system are at play. And so those apply across proteins. Those are just general principles of binding. And we think we see that

actively in the platform. Okay.

Our next question comes from Dan Brennan at TD Cowan.

Great. Thank you. Could you just review, I know you did in the prepared remarks, just kind of what are the key milestones and timing over, say, 25, maybe in the 26? Are there two or three checkpoints that the market will see, whether the customers or investors, that we could kind of get a further update if you're meeting your expectations? Or will it just come at some point in early 26? It's either going to be, you'll kind of reveal and then we'll get a sense if you're on track or not.

Yeah, Dan, thanks for the question. Let me try to answer the question in two different directions for you. Remember, the core platform has two different modalities. One is a mode where you take a deep dive in a single protein or small number of proteins. And that today is really focused on proteoform detection. And then there's another modality where we're looking for what we call broad scale discovery proteomics, which is get the all of the GD-coded proteins that you have within the sample. And each of those modalities has different catalysts that we think are coming up here over the course of the next call it four to six quarters. I won't assign individual timelines necessarily to all the pieces of it. So, you know, on the Tau, let's start with the proteoform side first. The first proteoform that we really have a great deal of interest in is Tau, which is key biological marker implicated in diseases like Alzheimer's disease. And as we move through the first half of 2025, we expect to provide the platform's capabilities to researchers to do Tau proteoform related studies. And, you know, Parag talked a little bit about some of the data that we've produced over the course of the last few months in his prepared remarks. And we will update our investor deck here over the course of the next day. And there's continues to be some more information in there on what we're doing on the Tau proteoform front. As we as we continue on the Tau proteoform side, we expect to also through the year continue to show more data and publish more data related to our performance characteristics, sensitivities of amic range, reproducibility, and so forth. And we expect that in the first half of 2025, we'll also sign our first Tau related partnership and stay tuned for more on that front. You know, so on the Tau front, I think that's that's kind of what you should look for in the in the near and medium term. So let me change my shift my attention to broad scale on the broad scale side. I think that, you know, one of the things that you've heard us say is that, you know, the big milestone on the broad scale side is when we can decode a significant number of proteins out of cell life. It doesn't have to be a lot 500, 1000, 2000 proteins. And by the time we get to that point, all of the platform pieces have come together. All of the assay performance is required for decoding is there. And we will at that point have a very firm grasp on the timeline remaining and final specifications and so forth. And I think that will be a big update for our investors and our analysts on the road to being able to do that. Once we're able to move through this asset configuration change and surface chemistry change, you'll see us have some intermediate milestones such as decoding predefined mixtures of proteins as we come as we progress towards cell life. Say as a comp, you know, as an example, the complex sample and then ultimately to that 500,000, 2000 protein milestone. And so as we start moving through those predefined mixtures, we'll bring the scientific community and our investor community along so that there are some interim checkpoints before we get to that that big data readout. And as well as we move through the year, I expect we'll continue to once we make our asset configuration change, continue to share data, particularly scientific conferences related to our broad scale capabilities, stability, sensitivity, reproducibility, dynamic range coverage in our

assay. Great. Maybe just one on Paladin since you're going to be engaging with customers now in the first half and planning a partnership. From what you've produced so far, could you just speak to the sense? I think you said you're going to provide some details, obviously, and sensitivity, specificity, key measurement tools. Could you just speak to the number of players emerging in the market? There's a lot of specs out there. Just kind of how you think your performance would compare to some of the other kind of leading kind of tall protein platforms.

Maybe I'll take this one, and I think one of the key and most important differentiator of our platform relative to everything else out in the world is that we are the only commercial platform that can measure protea forms in high throughput and high sensitivity from complex samples. So that aspect of being able to comment on the combination of isoforms plus potentially triple phosphorylation of tau or quadruple phosphorylation of tau at sites A, B, C, and D or A, B, C, and E is a unique capability of our platform and something that our customers are extremely excited about. Because that allows you to reveal the order and timing of events that are on the way to Alzheimer's. It allows you to unveil substructure and subtypes that are potentially indicative of response to therapy of one therapeutic versus another and also potentially allow you to define differences between patients who have aggressive rapidly progressing disease versus not. So it's really in the resolution of the measurement that is incredibly unique. With regards to other specifications, some of the things that we've been looking at are the dynamic range within the measurement of an individual protea form. And so keep in mind there are two different measures of dynamic range. One is the across analyte dynamic range and the other is the within analyte dynamic range. And typically, for instance, in TMT assays and mass spectrometry, you have what's called range compression. And so you're within analyte dynamic range is typically below one order of magnitude. We've demonstrated dynamic range of upwards of three orders of magnitude within our within analyte dynamic range. With regards to reproducibility, showing reproducibility with CVs, you know, well below 20%. And then one other common factor that you'll see people look at is just what are the range of analytes that you're able to look at. And that's that's where, as I highlighted, we're able to access analytes that are simply inaccessible to other platforms.

Great, thank you.

Our next question comes from Matt Sykes at Goldman Sachs.

Good morning. This is Will Ortt-Meier from Matt Sykes. Thanks for taking our questions. I appreciate the commentary around the probe optimization, taking some time and pushing out the launch date, but just want to clarify, is that late 2026 launch for both the broad scale discovery and the more targeted platform or are those timelines different? Morning,

Will, let me try

to take

that one. Both of our modalities are heading to the market with different strategies. So on the let's take the broad scale side first. On the broad scale side, we are moving towards a model where late in 2026, we have our commercial launch. And from that point forward, we're largely selling instruments for selling consumables, for selling software services, of course, that's the business model going forward. And we'll provide some services capability after that point as an on ramp to buying instruments and burst capacity of that sort of thing. On the proteiform side, because the proteiform data coming off our platform is a type of data and a level of detail that you can't get with other assets, we've chosen not to just productize it as a service or to sell an instrument that does proteiform assets and instead have focused on partnering with organizations who are looking for this level of detail and jointly exploring the space with those assets. So we're looking at the TAU initially of that proteiform and understanding what are the implications biologically, how does it inform therapeutic development, are there potential diagnostic applications. And so on the proteiform front, we are today talking to a number of organizations around partnerships on the TAU proteiform. Those analyses will be done in our facility, and we will work with our customers and return results to them and then work with them on the next phases of their project. And then ultimately, certainly over the course of 2025 and 2026, we will also add additional biomarkers, some that are driven by customer conversations and some driven by our own research and desires for that product. And for the foreseeable future, those proteiform capabilities are capabilities that we're going to introduce to customers via partnerships and collaboration.

Got it. That's super helpful. Thank you. And then just following up on that, you mentioned giving researchers access to proteiform in the first half of 25. But then I just wanted to see if the launch date impacts your expectations for the early access program, maybe on the broad scale side and in relation to instrument placements as well. Thank you so much.

Yeah, so the early access period is a just to kind of define it for those that may not remember the early access period is approximately six to nine months prior to the commercial launch of our instrument on the broad scale side. And that is an opportunity for customers to see the data that our platform produces with their own samples. And so that's a model where the customer potential customers will send the samples will analyze them using the pre production broad scale capabilities. And the goal of those engagements is one to generate data and excitement and have a set of data that we can leverage as we move towards launch. But even more importantly, to get customers excited enough to want to place orders for the instrument once we get to that commercial launch. And so you should think about commercial launch late 2026 and early access period starting from six to nine months.

Great. Thank you so much.

I'm 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.