Okay, hi everyone. My name is Marta Zaremba. I'm from the Life Science Tools and Diagnostics team here at JP Morgan. It is my pleasure to introduce our next company, Seer. As a reminder, this will be a roughly 20-minute presentation followed by a 20-minute Q&A. And if anyone in the audience or online has any questions, feel free to submit them via the portal or pin me directly. And with that, I will pass it over to Seer Management Team.
Good afternoon, everyone, and thanks so much, Marta, and the JPMorgan team for the opportunity to present today. Seer's mission is to unlock the power of unbiased proteomics at scale. And this year, I'm excited to share with you the tremendous progress that we've made toward this target over the past year. We're seeing a growing footprint of customer publication, validating the platform from discovery to translational research.
And I'm going to share some examples of results from the customers that show us really the advantage of the unbiased proteomics that we believe Seer uniquely enables. My apologies, the ticker isn't working. Oh, there it is. Good. Please note our safe harbor disclosure, which indicates that my presentation may include forward-looking statements. At Seer, we imagine and pioneer new ways to decode the biology of the proteome to improve human health.
Let's start with just a brief overview of where Seer is today. We believe that our products have unique capabilities and features that will allow our customers to be successful in reaching the deep proteomics that they can't otherwise reach. This will give us an opportunity to tap into a $27 billion market today that's growing at about 10% year over year. We launched the Proteograph Product Suite to enable deep unbiased proteomics at scale. To date, our customers and work that we've done has been able to identify over 36,000 proteins across the various different species that have been looked at. This is now backed by 32 customer publications, preprints, and reviews. We have now served more than 120 customers across 20 different countries.
With a strong balance sheet of $312 million of available capital, we see a path to profitability supported by a recurrent high-margin revenue. With our ownership in PrognomiQ, which is a liquid biopsy company that we spun out before Seer went public in 2020, we're actually catalyzing a market expansion in this liquid biopsy space. I'll share with you a brief update on PrognomiQ that is now developing an early lung cancer detection test with a strong performance to be a best-in-class test. Taken together, we believe Seer is strongly positioned to take advantage of the massive opportunity in the proteomic space. Now, let's take a closer look at the proteome and its role in understanding health and disease. Biology is complex.
As you go from the left side of the slide to the right side of the slide, you go from 20,000 genes and you get to millions of proteins on the right side. These are proteins with distinct structure, shape, and frankly, functions. Across the population, these variants of proteins accumulate. No better proof than looking at the UKBB Nature paper that was published, looking at 455,000 exomes, where nearly 9 million protein variants were identified, of which about 6 million of them were potentially deleterious. Now, Seer has enabled access to this deep unbiased proteomics. I expect it's going to be a key enabler to decode the complexity of the proteome and to lead to much, much deeper and greater biological insight.
As the scientific community begins to leverage our platform and do larger and larger studies, additional protein variants are going to be identified and discovered, and the roles that they play in health and disease will be elucidated. There are fundamentally two distinct approaches that one can get deep into the proteome. The first is a targeted approach using antibodies or other analyte-specific reagents, and the second is an unbiased or untargeted approach using mass spec, which is considered the gold standard for proteomics.
Now, if we think of the complexity of the proteome as represented in this iceberg, then targeted approaches are represented by just the tip of the iceberg, as they interrogate only the specific form of the protein and their analyte-specific reagents can measure. Unbiased approaches or untargeted approaches using a mass spec are not constrained to measure a specific form of a protein.
And when coupled to a Seer Proteograph platform, this approach provides depth and scale and visibility to the enormous complexity and content that's represented in the portion of the iceberg that is underwater and yet to be discovered. Of course, you see the proteins on the tip, but you also see everything else that you do not otherwise know to be there.
We believe that the Proteograph provides a unique combination of the depth and scale that enables scientists to discover the vast body of the proteomic content. And it's likely going to result in the translation and development of new diagnostic and new therapeutic that are based on those biomarkers. Now, as I mentioned, mass spec is the gold standard for unbiased proteomics, and it has been for decades. However, prior to Seer, running a deep unbiased proteomics study at scale was just not possible.
There were three main bottlenecks that needed to be broken in order to enable deep unbiased proteomics at scale to become a reality. The first bottleneck that we addressed was the workflow. Researchers always, prior to Seer, had to choose between depth of coverage or the scale of their studies. And studies of scales could only be done using shallow proteomic approaches, or studies that went deep because of the complex workflows and the depletion fractionation were only usually done in tens of samples at best. And this was the challenge that we initially addressed. And by the way, these approaches were also not standardized between and among labs. And so it was very difficult to translate one person's data from another.
Seer removed this workflow bottleneck with the introduction of the Proteograph Product Suite, which introduced a platform for deep proteomics and automation that drove reproducibility and standardization of the workflow. When this happened, we essentially shattered the bottleneck. And now large-scale studies were being done. And so the second bottleneck that we, in fact, created was a massive amount of data that became available and then the analysis of this data. So prior to Seer, you didn't have to worry about that because the studies were small.
And we addressed the second bottleneck with the introduction of the Proteograph Analysis Suite, or PAS. PAS is a first-of-its-kind cloud-based mass spec proteomic analysis solution today that's capable of scaling to over tens of thousands of samples. And prior to Seer, by the way, and prior to PAS, customers would do at best tens, maybe even hundreds of samples at best.
And the final bottleneck is the detector itself. And the mass spec vendors are constantly improving the performance of their products. And today, the Thermo Fisher Orbitrap Astral represents the pinnacle of mass spec-based instruments for proteomics. And when you pair an Astral together with a Proteograph, it makes it possible for the first time to do population-scale deep unbiased proteomics robustly, reproducibly, really fantastic.
Now, at Seer, we're constantly collaborating with our partners on the mass spec side to address all the bottlenecks across the mass spec-based proteomic workflow. And I expect to have more updates for you guys as the year goes on. As you can see, Seer has fundamentally changed the trajectory of proteomics with the introduction of the SP100 release in 2021. That was our first assay. And then our subsequent assay, Proteograph XT in 2023.
In its current configuration, the Proteograph instrument can run over 10,000 samples per year. And our Proteograph Product Suite is now backed by a strong IP portfolio of over 220 issued and pending patents covering over 35 countries. The impact of the Proteograph is increasingly evidenced in terms of proteins detected, customers served, and publications.
Prior to Seer's introduction, the deepest published study that we're aware of was a study from Steve Carr's group at the Broad Institute that was in 16 samples they could get to a depth of about 5,400 proteins. Now, each year after the introduction of the Proteograph Product Suite, you can see in the green the depth of customer studies has deepened and deepened. Today, the deepest is 13,000 proteins that were reached by a customer in 2024. Similarly, as you can see in purple, the customer base has also doubled each year.
As you can see there in teal, the cumulative publication is growing from three in 2022 to over 30 in 2024, which is a tremendous validation of our technology. We believe the combination of the Seer Proteograph with the Orbitrap Astral has enabled deep plasma proteomic studies that were never possible to achieve before. As I discussed last year, Proteograph boosted the depth of Astral coverage by about 8x.
What's remarkable in 2024 is we saw a customer run a study of 2,840 subjects reaching a depth of 13,000 protein coverage in that study. These numbers are just staggering and just completely different from what was possible just three years ago. Now, as generations of the mass spec instruments have been introduced, the Proteograph has consistently improved the performance in terms of depth of protein coverage.
You can see from 2022, by the way, we've had all of these instruments in our labs. The dark blue represents the performance of the mass spec on its own, and the teal bar represents the performance of the mass spec if you put a Proteograph upstream to it, running the same biological sample and the same workflow, and we expect our customers to see even more value as the mass specs get better. We'll continue to deliver value, and I think the future is quite bright. Now, we brought the first generation of the Proteograph assay to the market in 2021 and introduced the Proteograph XT in 2023. Last year was an interesting year because we saw a push by others trying to emulate our approach.
And the data in this slide is actually from a head-to-head comparative study on the same samples that were run by Professor Joshua J. Coon from the University of Wisconsin–Madison. And this study just became available on bioRxiv. And I encourage you to look at it. On the left-hand plot, the depth of coverage is shown for neat plasma in dark blue and for Seer in teal. The remaining three gray bars represent other methods that try to emulate our proprietary engineered nanoparticle approach in achieving depth of protein coverage. The right-hand shows reproducibility as measured by coefficient of variation, or CVs, in these assays, where a lower percentage indicates a lower variability and a higher reproducibility. As you can see, Seer is superior in terms of both depth of coverage and reproducibility of the assay.
Seer detects more low abundance protein than any other method while maintaining the lowest noise level similar to neat plasma. There are so many other metrics where we believe Seer is far superior to other approaches that are not captured in Professor Coon's paper. These include, for example, batch-to-batch and lot-to-lot manufacturing robustness that makes it possible to run multi-year population-scale studies and our quality systems that are ISO 13485 certified today.
If you ran a Proteograph in San Francisco on the same samples and run it in Boston or Copenhagen or China, you'll get very, very similar results. Now, these types of comparative studies have also been validated by several other academic and industry scientists, and it is incredibly rewarding to see the significant efforts that we're making and continue to make in the market for unbiased proteomic at scale.
Now, as we continue to mesh this highly compelling body of evidence supporting the superior performance of our technology, we're experiencing an evolution at Seer, transitioning from a pioneer that created this space to being increasingly seen as a trusted partner. And this hard-earned validation among customers is critical as we enter the next phase of our business and compete for large-scale, population-scale, deep unbiased proteomic studies. We now have over 32 publications, preprints, and reviews demonstrating the capabilities of our technology, many in high-impact journals.
And we expect that number to continue to grow in 2025. On the following four slides, I will quickly highlight a few customer examples that demonstrate the value proposition of the Proteograph Product Suite as an unbiased approach highlighting its breadth, scale, reproducibility, specificity, and, of course, utility across species. The first example is from PrognomiQ, which is our own spinout.
They're actually here at JP Morgan if you want to meet with them. They're developing a test for early detection of lung cancer. In their validation cohort, they demonstrated an overall sensitivity of 89% and specificity of 89%. Importantly, for stage 1 cancer, lung, they can see an 80% sensitivity at the same specificity. The identification and validation of these biomarkers was only possible through the combination of unbiased deep at scale and the robustness of our platform across many thousands of samples that was obviously enabled by the Proteograph platform.
The second example comes from Evotec, which has been one of our centers of excellence in Europe since 2021. Evotec has integrated the Proteograph into its service offering for its customers wanting to do deep proteomic analysis. Our automated Proteograph platform fits seamlessly into their workflow, enhancing their product offering.
They have over 50 mass specs, by the way, in their facilities. And so Evotec understands, appreciates very readily what it takes to perform large-scale proteomic studies. And the Proteograph has been fantastic in helping their pharma customers. And it's been a strong validation for our platform. To date, 35% of the global top 20 pharma customers that they have worked with have completed a study with the Proteograph, with Evotec. And they're seeing a tremendous traction among these customers for growth across their pharma customer base. We're excited to support their effort. We appreciate the partnership working together in driving deep unbiased proteomics at scale. The third example is from Professor Satchin Panda's group at Salk Institute. His team explored the application of the Proteograph Product Suite to study a mouse model of relative energy deficiency.
In their multi-omic studies, they identified 442 plasma proteins in mice that were perturbed. They were able to tie these subset of these biomarkers back to changes at the transcriptomic level. Now, the Proteograph is the only deep unbiased proteomic approach that can cross species because we're not tied to a specific epitope. Without the Proteograph, they would not have been able to study the perturbation in the mouse models and achieve the molecular and cellular understanding of the disease that they have been able to achieve. In the final example, my apologies, it's a very complicated slide. This is from Karsten Suhre's group from Cornell. It demonstrates the power of the Proteograph in enabling deep unbiased, accurate proteogenomics in large cohorts and identification of protein quantitative trait loci or pQTLs.
Now, pQTLs represent changes in protein abundance associated with the genetic variance across the population. Professor Suhre published a method paper on pQTL using the Proteograph, and he published that in Nature Communications in early 2024. In this study, which is now under revision at another sister journal of Nature, his follow-up study shows that this was the first demonstration of the biological insight that can come from doing deep unbiased pQTL analysis using the Proteograph. In a cohort of over 1,500 diabetic patients, he showed that the Proteograph data can distinguish between true and potentially erroneous pQTL predictions from leading affinity-based methods.
In particular, Professor Suhre exemplified the pQTL findings in two large-scale studies that were published in 2023. Both, by the way, were published in Nature. One study was conducted in 55,000 subjects from UKBB, and then the other was the Olink study.
And then the other was a UKBB pQTL and those with the SomaScan and the deCODE Icelandic cohort. Now, the plot that you see here shows the pQTLs that were identified in the Olink study. Plotted on the x-axis from the left to right are pQTLs according to their statistical significance in the UKBB. And on the y-axis, according to the level of evidence on the Proteograph data. One-third of the Olink pQTLs scored high in the mass spec data. One-third were in the gray zone. And one-third showed almost no evidence by mass spec. Now, looking at those pQTLs found by both Olink and SomaScan, now those specific ones are shown in green. And the pQTLs that were found by both Olink and SomaScan are more reliable.
They're not subject to the specific epitope effect that any one platform may have because they're found by two independent technologies in two independent cohorts. The Proteograph data confirms that these are true pQTLs, and in fact, nearly all the ones that are green that are shared by both fall in the high conviction, and then these are validated by the Proteograph. Hence, the Proteograph score differentiates high and low reliability pQTLs, and this should, by the way, surprise us, frankly, as mass spec data represents the ground truth in proteomics. Now, a very similar data when you look at the SomaScan pQTLs. Again, about a third of them are high conviction. Those are also corroborated by the Olink data, and about a third, gray zone, and about a third, no evidence in terms of pQTL by mass spec. OK.
Last year, I spoke about how we can enable discovery of content at scale and that we're at the customer inflection point, widespread adoption of our customer. And we just need to demonstrate the biological insight. Now, with 32 customer publications, I think we're getting there. And we're reaching this inflection. And I expect the pace of customer validation will only grow in 2025. A significant driver of our current momentum has been the excitement around the Seer Technology Access Center.
We announced the Center in 2023. It was fantastic. We opened the second Center in 2024 in Bonn, Germany. We've now served over 90 organizations, approximately doubling our customer base over the past year. 12 large pharmas have been served. Year-over-year revenue growth of about 69%. We're continuing to invest in our commercial talent and infrastructure to seize the opportunity in front of us.
In North America, we doubled the size of our commercial team in 2024. We'll continue to make selective investments in our direct sales throughout 2025. We also added six new channel partners that are going to help us continue to develop the market. And we'll continue to invest commercially as we see fit to expand. Now, in November, we announced our co-marketing and sales agreement with Thermo Fisher. It's terrific. So the Thermo sales team can now quote and sell the Proteograph product suite.
Obviously, the Proteograph product suite, together with the Orbitrap Astral, performs the best there is in unbiased proteomics. And now the Thermo customers can get an end-to-end solution right there as they're looking at the Astral. And we're very appreciative about our partnership with Thermo. And we'll continue to work together closely in developing workflow optimization or other methods.
I spoke earlier about how PAS is the most scalable proteomic analysis solution. You can see in this graph, PAS 3.0 has literally reduced the time it takes to do data analysis by over 95%, by the way, also driving down cost. We'll continue to invest in our software and our data analysis. In addition, next month, we're going to be launching a new product application for Proteograph XT, which is for cell lysate proteomics.
This brings the power of Proteograph Product Suite also to doing intracellular proteomic work in just about any cellular compartments. If you do this with the Proteograph, you'll see substantially more proteins. Then we're encouraged that our base products and service business, and this excludes our related party transaction with PrognomiQ and grant revenue, continue to grow nicely.
Now, on our Q3 earnings, we guided for a full year 2024 revenue range of $13 million-$15 million. And we'll report our 2024 revenue on our year-end earnings call. Past year was tough. We were impacted by a broader difficult macro environment. And while this uncertainty continues today, I'm also optimistic and believe that a strengthening tailwind of publications and customer validation is going to translate to a much stronger 2025 for us. Looking at our balance sheet, we'll continue to carefully manage our significant cash balance and deployment of capital to maximum shareholder value.
We had approximately $312 million of cash, cash equivalents and investments as of September 30. In 2024, we materially reduced our burn while continuing to invest in our commercial infrastructure and product innovation. This is going to be an exciting year in product innovation. I look forward to updating you.
We expect to further reduce our cash burn by a similar amount in 2025. I'll share more about that detail also in our year-end 2024 earnings call. Given that we believe there was a massive dislocation of share price throughout 2024, our board also authorized a $25 million share buyback program. Through the program, we had repurchased 5.7 million shares, weighted average of $1.80 through September 30, reducing our total shares outstanding by about 9%. As we begin 2025, I'm extremely excited about the opportunity we have in front of us.
We're going to continuously see momentum evidence build increasingly as we begin to take the position of a trusted partner for our customers in this unbiased proteomic space. We're going to be innovating new products. We'll be launching new products which I'll share with you guys over the year.
I think all of these are going to reduce the barrier to access the Proteograph over time. Importantly, we're going to continue to innovate in this space. We opened up a space in this unbiased proteomics at scale. I think there's more room to be innovative in this space. I'm very, very optimistic. I think with that, I will turn it back to Marta for Q&A. Thank you so much.
Wonderful. Thank you. Thank you for the presentation. Are you going to come on? With that, maybe let's kick it off with some more near-term questions and then more long-term questions as well. I appreciate that you're going to provide more color in 4Q at your earnings call. Perhaps you can give maybe some high-level color on how it progressed and elaborate on how macro impacted your portfolio in 4Q.
David, do you want to open up with that?
Sure. Thanks, Marta. So in terms of, as Omid mentioned, 2024 was a tough year just from a macro environment standpoint. I think the first half of the year was especially difficult. But then we did see some loosening up of budgets from folks in the second half of the year. And I think that is encouraging as we move into 2025. I think we are excited about the prospects for 2025. Macro conditions aside, I think there continues to remain uncertainty.
But with the increasing number of publications, with the Thermo Fisher partnership, and with the continued growth in our funnel that we see from a sales perspective, and the increasing conversations we're having with customers about deep unbiased proteomics, that it's putting together a good setup. But we're cautiously optimistic, I will say, just given the continued overhang that we see out there.
Wonderful. You actually kind of touched on my next question, which is set up for 2025 on top line, but also gross margins, especially given the alternative programs like STAC that you're offering. So any more color you could share would be wonderful.
Yeah. Look, I mean, our gross margins are really driven by the consumables, which is a high-margin business. And I would say our instruments, we make relatively small margin in our instrument sale, which is an OEM from Hamilton. The STAC falls in the middle of those two in terms of gross margins. And so on a blended basis, I don't think the STAC will materially change our overall gross margin for 2025.
And if I look at the year and I look at our funnel of customers today at the beginning of 2025, we've never had a stronger funnel of customers than we have today. And by the way, this is on the back of a challenging macro environment. And I think what's helping us is that the evidence for the value proposition for the Proteograph is getting stronger and stronger and stronger in the hands of the customers.
We are being asked for the first time to actually come and have a seat around the table and talk about being able to do population-scale proteomics that's deep and unbiased. Such a thing was just a complete pipe dream just two or three years ago. And I think the reason we're being asked to participate in those discussions is because the validation of that technology is becoming more and more obvious. And we're being shifted and viewed from a pioneer in the space to being a trusted partner in the space. So I'm really bullish about 2025.
OK. And then last one, probably on the near-term dynamics. Recently, there's been investor concern regarding budget allocations under the new administration. So as you look at 2025, what are your thoughts on academic customer budgets, particularly in relation to potential changes to NIH funding? And then in general, what are your thoughts on the risk related to the new U.S. administration?
I think if I look at the NIH budget, and if you look at it over a long span of time, almost independent of the party at the time, NIH budget had grown. And there's only two occasions where the NIH budget would actually shrink. So my expectation is that we're not going to see a very significant swing. I think there is an uncertainty that may follow the next two or three quarters as people get a better visibility in terms of what's coming. But I don't think that there's going to be dramatic shifts in terms of budget allocation. And if anything, if I was going to then say, let me take a lens that is much, much more focused in the types of studies that we do, there is a tremendous amount of interest today that is brewing in the proteomics space.
I actually think in a disproportionate way, independent of the budget direction, that omics and specifically proteomics is going to be a beneficiary of it. By the way, not just in 2025, but 2025 and years to come. We're at the very, very beginning of a shift in terms of the understanding of the proteome. And the dollars that are being invested are only going to grow in this space, by the way, no different than the investment that the NIH began to make in genomics. And that investment continued to grow. I think we're going to see a very similar shift in terms of interest and investment in the omics and specifically in the proteomics space.
OK. And then you've spoken a lot in the past about how publications are really driving adoption of your products. So in terms of publications, can you talk about the pipeline and what it really looks like? And any color you can share on what you expect for 2025.
Yeah, well, obviously, 2024 was a great year for publication. We saw a lot of papers come. In the scientific world, which I lived for 20 years before Seer, you spend a couple of years doing work, and then you spend a year fighting the journals to get something published. Usually, it takes two to three years to go from the start of a study to a published work. Seer has had exactly three full years to the T of broad commercialization of its products. The fact that the flow of publications is just starting is exactly par for the course. In 2023, we had exactly one customer publications. Now we have 32 of them that have come. My expectation is that that velocity will continue to go, Marta. I don't have an exact number for you.
But I don't think the slope is going to flatten. I think the number of publications are going to grow. And the validation is going to increase. And by the way, if I was going to say, where do I see a real inflection, I don't think there's any one specific paper that will do that. But I do think the moment the first population-scale study using deep unbiased proteomics happens, that is actually a true inflection point in terms of proteomics and unbiased proteomics for the field.
OK. And then in terms of new products, innovation is definitely an important aspect for Seer. So what can we expect from you in the medium to near term in terms of new products and services? And can you touch on your R&D priorities and which areas you're investing more heavily from the R&D perspective?
Look, I shared the slide that showed the bottlenecks. I mean, obviously, our approach is to lower barrier to access to deep unbiased proteomics. I'm not a proteomics scientist. I'm a nanoparticle expert. And the control experiment for when we are done what we needed to do is if a scientist like me becomes a user of the proteomic data. And to do that, you need to simplify the workflow so that any customer, any scientist can be a consumer of proteomic content and data.
I think we've now done that for the genomics. We've done that for PCR. We have not done that for proteomics in an untargeted way. And so we will continue to invest across the challenges and the bottlenecks of the proteomics space to realize that goal. And I have every expectation that every month, every quarter, every year, we're making advancement to that.
2025 is an exciting year in terms of our R&D roadmap. I will be making some product announcement later this year, and I will also make some new announcement in terms of the ways we are tackling this space to really democratize access to deep unbiased proteomics, so I think it's really an exciting year in terms of R&D roadmap, and obviously, scale, speed, and ease are the three dimensions that we're focused on.
Okay. And then you've actually touched on this during your presentation. You recently expanded your partnership with Thermo for the insider co-marketing and sales agreement. So how did this partnership really come about? And what do you think are the long-term benefits of this partnership this year?
Let me make one comment, and I'll hand it to David. The partnership didn't happen overnight. When we took Seer public, and this is right at the end of 2020, beginning of 2021, we said we are Switzerland, and we want to be working with everyone and we want to partner with everyone. To solve this challenge, we need everybody's help, and we want to be a constructive contributor to do that, and Thermo was among the partners that we picked in 2021. They've just been very consistent. Their team has worked very closely with our team.
They've just been fantastic in every possible way, and year after year, we've done more and more together, and so this was just a natural extension in terms of a partnership, so it was not an overnight event. It was something that gradually built. It was, in fact, a long dating that we did together. And it was not love at first sight. But it's certainly a lot of love at this point. So let me hand it to David to tell you guys about the details of the partnership and why I'm very excited about it.
Yeah. Thanks, Omid. So we signed a co-marketing and sales agreement with Thermo Fisher with their mass spec group, the group that sells the Orbitrap Astral. And really, from our perspective, this is something that obviously will be exciting in that we provided our product list to Thermo so that they can put that in their system so that their reps can go out and quote our products for their customers as part of a think of it as a bundled package when they're selling the Astral to their customers who want to do deep unbiased proteomics.
And so now they can offer to their customers the full workflow that includes the Proteograph so that they can get from sample to data pretty quickly. So from our perspective, it's a great leverage of this Thermo infrastructure. Obviously, they're a global player. And they'll now be selling our product.
From their perspective, it allows them to now offer the complete solution to their customers in a seamless fashion. Why we also like it is that their main goal, obviously, is to sell more Astrals. And so once they make a sale, they'll hand the customer to us to follow up on the consumable pull-through. So we'll continue to have visibility to the customer base and what they're using the Proteograph for once Thermo makes the initial sale there. And so we're training their team over the Q1 . And so we expect to have the partnership operational in the Q2 . And we'll take it from there.
OK. And then can you discuss the competitive landscape of the proteomics market and how it really has evolved in the last few years, probably for your relevance since Seer became public?
Yeah.
And then are there any perhaps competitors that you're running into more often than not? And what do you consider your main competitive advantages if you were to list, let's say, a top three?
Yeah. Martha, I would bucket the landscape into three buckets. I would say there are those players that approach the proteomics in a targeted way. And by the way, those approaches go back commercially 20-plus years, 25 in the case of SomaLogic and maybe 15-plus in the case of Olink. But then newer players like Alamar and maybe some older players like Quanterix. But targeted approaches, interrogating a subset of proteins using an allele-specific reagent.
So that's one bucket. The second bucket is a group of companies that emerged under the premise that mass spec is a lousy detector. And so I'm going to make the new detector. And that would be like the Erisyon on the board or the Encodia privately or maybe Quantum-Si and Nautilus on the public side. And then the third bucket is those that say, I'm going to approach this in an untargeted way.
And that's Seer. So we don't compete with bucket two in any way, shape, or form, not even for the wallet. In fact, if anything, I wish for the scientific community's sake that every one of those examples are successful. Because if they are, the Seer Proteograph Product Suite will go sit upstream to their platform, just like today sits upstream to a mass spec platform. The scientist in me is extremely skeptical because those technologies need to emerge and launch and become commercially accepted at a time frame that they're better than the mass spec. But the thing is, the mass specs are getting better and better. If you just look at the slide that I showed just in the last four years, the performance of the mass spec is phenomenal.
My expectation is the velocity by which mass specs will continue to innovate is not going to slow down. So we don't compete with the second bucket. In the first bucket, in the target bucket, I don't think we compete there in terms of the kinds of data that's emerged. We do compete in terms of a wallet share with the customers. And when we're out there, I would say in a significantly disproportionately high ratio, Olink comes up for us over the other parties. But the acquisition of Thermo of Olink actually shows that these are complementary platforms. In other words, the mass spec business is the crown jewel of Thermo Fisher. They did not sabotage that business by buying Olink. They bought it because it was actually very complementary.
So, I think over time, the value proposition of Seer as a leader in unbiased with another leader in targeted, the complementarity of that will become clear. But today, in terms of a dollar wallet share of a customer, the name that pops up, and so we have to educate the market, is in the targeted side.
Wonderful. And with that, we're out of time. Thank you very much.
Thank you, Marta. I appreciate it.