Sophia Genetics at TD Cowen Conference: AI-Powered Growth Strategy

On Wednesday, 05 March 2025, Sophia Genetics (NASDAQ: SOPH) presented its strategic vision at the TD Cowen 45th Annual Healthcare Conference. The company highlighted its innovative AI-driven platform, SOPHiA DDM, and its potential to transform diagnostic markets. Despite challenges, Sophia Genetics remains optimistic about its growth prospects, particularly in the US market.

Key Takeaways

• Sophia Genetics aims for 10% to 17% revenue growth by 2025, focusing on US expansion and liquid biopsy solutions.
• The company plans to convert new customers into revenue-generating accounts, leveraging its AI platform for improved diagnostics.
• Financially, Sophia Genetics expects to channel 60% of incremental revenue growth into EBITDA.
• The SOPHiA DDM platform’s accuracy and speed offer a competitive edge in genomic data analysis.

Financial Results

• Revenue Growth: Targeting a 10% to 17% increase for 2025, with a focus on converting new customers into revenue-generating accounts.
• EBITDA: Projected to capture 60% of each additional growth dollar.
• Gross Margins: Adjusted gross margins reached 72.8% in 2023, with expectations for further improvement.
• Operating Expenses: Aims to maintain current levels, with potential upside from the biopharma sector.

Operational Updates

• Customer Acquisition: Added 92 new genomics customers in 2024, expanding its base to 472.
• US Market Expansion: Significant growth in the US, with recent partnerships with Mount Sinai and the Mayo Clinic.
• Liquid Biopsy: Launched MSK Access, signing 34 institutions globally, focusing on routine usage and application expansion.

Future Outlook

• Growth Drivers: Opportunities in biopharma, liquid biopsy advancements, and US market penetration.
• MSK Access: Aiming for global standardization in liquid biopsy testing, with a pipeline for further deployment.
• Technological Advancements: Launching ANNEXOMES for detailed genomic analysis, enhancing multimodal data integration.

Q&A Highlights

• Accuracy and Speed: SOPHiA DDM’s precision in complex applications like HRD and liquid biopsy.
• Competitive Positioning: Advantages over in-house and custom solutions in accuracy and scalability.
• Pharma Business Model: Dual approach in diagnostics and multimodal data insights.

For a detailed exploration of Sophia Genetics’ strategic initiatives, refer to the full transcript below.

Full transcript - TD Cowen 45th Annual Healthcare Conference:

Dan Brennan, Follow Tools and Diagnostics, Cowen: Welcome day three of the TV Cowen Global Healthcare Conference. Dan Brennan, follow Tools and Diagnostics. Really pleased to be joined here with me on stage, management team of Sofia Genetics.

I’ve got doctor Philippe Munyu, who is a chief product officer and chief medical officer. And we also have Kellen Tanger, who’s head of strategy and chief of staff. So gentlemen, welcome and thank

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: you for being here. Thank you for having us.

Dan Brennan, Follow Tools and Diagnostics, Cowen: I thought, Philippe, maybe you could start off a little bit with kind of your background on the role in the company, your tenure here. And also if you could introduce from your perspective, you know, SOPHIA and the SOPHIA DDM platform and kind of what makes you unique.

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Absolutely. So thank you for having us. So my name is Vipun Nueh. I’m Chief Product Officer and Chief Medical Officer with the company. I’ve been here five years now.

So I saw you on the medical side, set

Dan Brennan, Follow Tools and Diagnostics, Cowen: up the medical function, then took over product management

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: and business development partnerships overall. So I’m in charge of more the strategic offering type of the company. So what we are, we are a technology company applied to healthcare. The idea is to democratize data driven medicine. The way we do that is through a tech platform play.

So we have a cloud based and cloud native platform called Sofia EDM that basically does the compute, generalization and analysis of digital health data modalities. So we started ten years ago now in the Genomics space. And five years ago, we branched out to increase the depth we can see on different patient profiles by adding imaging and clinical data on top of the genomics insight. So the model we pioneer is a decentralized one. So we basically have landed now about 800 customers across 70 countries that basically adopt whatever technology they want to do the testing.

For example, in genomic side, it can be any combination of wet lab chemistry, sequencers. And we go into the lab, we help them in toolkit and we tailor the analytics to their solution, right. So the power of the platform is with AI at the center from inception, we have been learning now from 2,000,000 profiles that we’ve computed in the platform. We do about 1,000 a day across a large gamut of NGS applications And we’ve become smarter and smarter as we’ve seen more diverse profiles from these 70 countries, right? With that, we basically serve both the clinical and the biofauna market.

Again, it’s a tech play, so the idea was always to lend a global platform, leverage network effects to make the platform more valuable for the clinical users and then leverage network effects indirectly with biopharma because we have a real life real time real world view of the testing practices in NGS, for example. So we can work with pharma then to clinical trial recruitment, CDX deployment, things like that, both in The U. S. And ex U. S.

Dan Brennan, Follow Tools and Diagnostics, Cowen: Terrific. And I don’t know if this question would be more for Kellen or for Philippe, but just a question since Sofia just reported yesterday. Just wondering kind of how you guys would characterize the 25 guidance, you know, you guided for I think it’s about 10% to 17% top line growth or healthy growth still below though kind of your long term goals, I think of, you know, somewhere closer to 30% plus. So the industry, the broader tools industry has been facing a difficult couple of years here. So maybe just speak through the puts and takes around that guidance?

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: Yes, sure. And 10% to 17% revenue growth at the midpoint is more around the 15% there. But I’m happy to just take down the P and L. So from a growth perspective, there are really three key things that we’re looking for in 2025. So first, we signed an incredible number of new customers in 2024, so 92 new core genomics customers on our base of four seventy two customers a day, so that’s a pretty large step up.

I’ll remind you that our growth strategy is the land and expand strategy in which we land customers. They implement the solution typically between six to nine months, ramp up revenue usage and then we expand across those accounts over time as we encourage them to adopt additional applications. So our our main focus on that pillar is just getting those accounts into a routine faster, and having them complete that implementation so that they start generating revenue. And then, we’ve had a great ability to expand historically. Our average customer uses 2.6 applications, 3030% of our customers use three or more applications, 20% use four or more applications.

So for us, it’s really getting those 92 customers that we signed in in ’24 into into revenue and then expanding across those. So that’s the first bucket. The second one on the on the growth side is, The US market. So we’ve done a great job, expanding and growing in The US. We were born in Switzerland.

We grew up in Europe. We’ve done a great job penetrating the European market, typically something that’s a little bit more difficult, and The US still remains largely under penetrated for us. We’re growing at really solid revenue growth rates from the clinical perspective in The US. We announced recently that we found Mount Mount Sinai, in New York, which is a big name. We’ve expanded across, the Mayo Clinic, and so this represents, obviously, a big opportunity for us from a geographic perspective to continue the growth.

It’s increasingly becoming one of our largest markets as well, so the the basis is growing. And then the third piece, which I know we’ll we’ll talk a lot about today, especially with Philippe on stage, is our new liquid biopsy offering MSK access. So this is a partnership that we started with MSK to decentralize their liquid biopsy solution. Since launch ten months ago in April, we’ve already signed 34 healthcare institutions across the globe to that solution, which is a pretty resounding number in terms of adoption. And And so now it’s really getting those customers again into routine usage so that they start generating revenue.

They’re not really felt right now in the figures and then continuing to expand that application both across our existing customers but then landing new customers. If we look beyond, the growth side revenue, we mentioned that we expect to drop 60% of every incremental growth dollar of revenue, down to EBITDA. So this is something that will at least paint a picture in terms of our loss and how we expect that to perform. A big piece of that is is margins continuing to increase. In 2023, we had adjusted gross margins of 72.8 percent, up 60 basis points from last year.

We expect that to continue to grow and then largely holding the the line on operating expense.

Dan Brennan, Follow Tools and Diagnostics, Cowen: And and and that’s terrific. In terms of, you know, the growth outlook for next year, say, 15% at the midpoint, maybe just high level question. What what would take you from 15% kinda up towards those long term targets, fifteen, twenty, 20 five? Obviously, land and expand, that makes perfect sense. Are there certain pressures on the broader kind of market today with spending that is kind of limiting the amount of spending certain customers are doing?

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: Yeah. And specifically to our biopharma customers. So the current guidance does not contemplate any material growth from the biopharma business. So that can be seen as a pretty material upside in terms of if we are able to bring in new customers or accelerate some of the contracts there. In addition, just the progress from liquid biopsy is exciting.

And as we continue to grow new applications, that scenario where that could bring in even more growth. The last is The US market. We’re continuing to talk to larger and larger customers, health systems, beyond the current customers that we’re addressing. So there’s a lot of exciting things across the growth drivers. Terrific.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So maybe, Philippe, maybe just, you know, we’ve met with Yurgey and Ross several times, and I think when you look at what Sophia does, you know, AI on top of diagnostics and genomics, it’s it’s really perfect for this market. But sometimes it’s hard for investors to contextualize of what makes you different. Walk through a little bit of, you know, as, Kellen just said, you know, it takes time to get these big, you know, hospitals or big health systems to sign up. Kind of when you walk into the hospital and you say, here’s what we do, here’s why we’re different, here’s what you can get from us, you can’t get deploying this locally. Is it possible to give us some more quantifiable measures about like the rate of improvement, what you can see that these customers can’t do on their own?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Sure. So we have a few unique selling points. So the first one is the accuracy, right, the ability to pick the signal from the noise. This is increasingly critical, especially as we move towards more complex applications and more complex biomarkers. About HRD, I think we have a best in class application, liquid biopsy with MSK access.

We just launched MRD last year as well. So that is really like the bread and butter of what we do, right? Being very highly differentiated in our ability to pick the signal from the noise and confidently call variance and identify basically causative variance of disease. I think that’s number one. Number two, the turnaround time is very important because we’re a decentralized player.

So we basically push the analytics into the hospital. So basically, the only thing that stands between you and the results is you actually pushing the button on the sequencer, getting the results. You don’t have to send out the sample. Sample doesn’t get lost, right? It’s basically staying in your lab.

You generate the data as quickly as you can possibly do it, and then you keep all ownership of your data. And the third one I would highlight is a scalability aspect that can add on to. So we do a land and expand strategy. So we will land on any application in a given lab and then basically people use the platform. It’s very convenient, it’s very fast.

And so now they will basically go into an expansion, adding new applications on top. So you do the scale up of the adoption of precision medicine applications very easily in a very cost effective manner, right? Because the alternative as a lab is, well, I can hire a bunch of Bio IT people which are expensive. I can’t really find any way in the market because it’s competitive. I have to do cybersecurity.

I have to do all of these things or I can have an Internet connection to Sofia DBM and then we take care of all of that for them, right? So then whatever pre shorts resources they have on the Bio IT side, they can use to reallocate more to R and D projects to do more innovation in house and we can take care of all of the operational things that we have industrialized to a very high point now.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So I know management has talked about customer deploying TSO500 locally versus having Sofia DBM on top of it and the benefits they’ll get. You mentioned your first answer to that question was finding the signal out of the noise and the accuracy. Could you just give some perspective on that level of improvement or just what a customer is not deploying Sofia that does deploy SOPHIA, kind of the benefits on that accuracy. I’m sure you’ve written white papers on this, maybe a little more kind of quantitative.

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: So maybe let’s take the MSK example because it’s a good example, right? So if you zoom out MSK has two best in class assays. They probably have the best molecular oncology program in the world. MSK Impact, which is tissue, CGP assay, MSK Access with their flagship, liquid biopsy assay, one hundred and forty six genes about tumor normal, right? There’s been a lot of demand historically for MSK to increase their volume testing from outside institutions.

They would like to benefit from these insights. So in the past, they’ve tried to decentralized MSK access specifically to central labs in The U. S. And the concordance was actually really poor, right? Even in a centralized setting trying to basically do a tech transplant if you want into another lab, they ever got to something like 60% roughly concordance with the central test in Manhattan.

So we were selected by MSK in early twenty twenty three to do a tech transfer to decentralize now these assays to get MSK access. This is essentially the way to think about this is a completely independently developed and validated assay that simply happens to have the same probe footprint. And we were basically tasked with having the highest concordance as we can compared to Manhattan, right? And so essentially now what you see is in the real world, we hit about 98% concordance, give or take something like this, which means that in practice, you have a super sophisticated assay, right. It’s really like sequence twenty thousand eggs.

I mean, it’s like tumor normal. So it’s a bit of a Ferrari type of assay. We can deploy it across the world, 24 institutions we announced, right, I think over 20 countries now. And the point is, you can walk into a lab in Brazil, in Paris or in Australia and get the exact same insight you would get if you were tested in the middle of Manhattan, right, which I think for me is a pretty mind blowing idea of us being able with the decade of experience in the single detection technologies we have to deploy that at scale in a year. And I mean, pharma has noticed as well, we’ve been public with AstraZeneca.

They’ve been helping us to deploy the test, right? So there’s a huge wave rising where this decentralized aspect of testing is getting a lot of attention.

Dan Brennan, Follow Tools and Diagnostics, Cowen: Maybe you mentioned you’re going deeper with Mayo, you signed Mount Sinai. Maybe just as an example, could you discuss whatever

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: you

Dan Brennan, Follow Tools and Diagnostics, Cowen: could share on Mayo Clinic? They’re obviously a leading institution. How are they using SofiaDDM today?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Yes. So at Mayo, we basically have very specific target applications we built with them in a way. So that was very much a co creation, if you want, of the assay. So they had very specific and it goes back to your earlier question. They had very specific assays where there were challenges in detection of signal.

They knew this was a tricky one. So we worked very closely with them, with their lab, with their clinicians to make sure that we had a fit for purpose application that really met exactly their standards. And I think that’s a very good halo effect for us, right. We work with MSK, we work with Mayo. It tells the market the quality is very high.

Dan Brennan, Follow Tools and Diagnostics, Cowen: You mentioned turnaround time as a key driver. I just wonder if you can discuss in terms of what the benefit is at a typical hospital or lab, Mike, and I’m sure it depends on their level of expertise. I’m sure the ones that are more kind of these big academic medical centers are Mayo. They’re probably pretty good on their own, but maybe smaller places might not be. So what’s the level of performance enhancement that you give and how important is that turnaround time advantage?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Yes. So this is very material. We increasingly put the premium now on having an end to end solution to for customers, right? So I mentioned we’re technology agnostic. It expands to sequencer.

It expands to liquid handler automation as well. So increasingly, we’re trying to come to our customers and say, look, let me work with you to have the right automates, the right sequencer, the right deployment on EDM DTM so that this is a completely seamless experience. And, you know, it varies, but, you know, if you have a central lab model, typically, you’re looking at send out, sending out the sample. You may have a turnaround time that may be anywhere between ten days to two weeks to three weeks to four weeks depending on where you’re in the world, right? I mean with SofiaDDM, again, you just have to load your sequencer, you push a button and depending on the size of the application, a few hours, the result will come back, right?

So that’s the you save completely on the logistical time if you want. And then again, don’t forget, you have the benefit of keeping all the sample in house, all the data in house. Don’t don’t just get a PDF report. You get everything. So you basically, you know, like, gain time and have more insights.

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: And that turnaround time is obviously critical in some cases to the the patient care. If it’s a late stage cancer patient, lung cancer or something like this, those waiting two weeks is sometimes unacceptable and getting a result or an insight faster is critical to their treatment.

Dan Brennan, Follow Tools and Diagnostics, Cowen: In terms of your competitive positioning with the market, when you’re going into some of these hospitals, whether in The US or around the world and you’re trying to convince them about your offering, do you run into any other players because it is somewhat of a unique model?

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: In short, not really. The typical people that we’re competing with is the in house bioinformatics tools and custom solutions that have been developed. And when we’re comparing to that, it’s it’s often a pretty easy sell. You can compare it to to, like, when people were were building their own CRM platforms and then when Salesforce took hold, oftentimes the tech platform offers a large suite of benefits. Fleet touched on a few, so it’s the ability to deliver accuracy.

Of course, we are leveraging, obviously, collective intelligence of people on a network where algorithms have been exposed to different types of diverse patient populations. So if a new sample comes on, onto the to the sequencer, we were able to read and harmonize that and then produce an accurate result. It’s the ability to retain control of data, it’s a usability, and then most of all maybe or or last of all, it’s an ability to expand and scale over time. So when you’re looking at a custom in house solution, it’s often hard if you wanna add an additional application or area. So maybe they’ve developed a solution around solid tumor testing.

If they wanted to add on hereditary cancer or liquid biopsy or heemont, that’s often difficult. It would require a large amount of resources to build. So this is, this is really what Sofia Didym specializes. It’s not in the scalability of all of the compute, but it’s also the ability to adopt additional applications without having to add more resources or a large IT infrastructure and maintenance costs and servers and such.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So Felipe, you mentioned MRD earlier in the discussion on those specifically for MSK, but right now the MRD market looks like it’s heavily driven by the CLIA labs. I don’t know how much it’s really locally distributed. Is that something that is currently hospitals are trying to do something locally? Is that something in the future you think there’ll be a big opportunity since there’s such a land grab in that market right now and folks are really excited?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Yes. So I think MRD recapitulates the story about Lipid Biopsy and others, which is first, pharma has to establish a clinical validity and clinical utility of doing these things, right? I think in the hematology space, that’s now very well accepted. Now Now you see the next battleground shifting to solid tumors, right? And so what you see is typically a model where first you have a few big central labs that dominate like a warrant for example, we did biopsy.

We see the same in MRD. Makes sense, right? You want to decrease the risk. You have a single provider, you build the evidence. But then once you have this tipping point where you go towards clinical adoption in routine, which we are seeing now in liquid biopsy, I think MRD in AML, we’ve launched, for example, this is already ongoing, but soy tumors is still a bit of a way out.

Then there will be a demand for, okay, so I need to scale this very quickly. Yes, I have a few central labs in The U. S, but it’s still a constrained market, right? So with our presence in these 70 countries and in The U. S, we can be a perfect complement to like these early central lab models and you can be centralized through us to basically get the best of both worlds in one.

So for us, the analogy always take as a share pharma and this had to own in a way. We’re not first in class, we’re best in class, which means we’re not investing to develop new markets. We wait for the markets to emerge, have a robust clinical demand, and then we go in with our solution.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So when you think about a customer running a 10 gene panel versus running hundreds of genes, running into exomes versus transuritum full genome. I assume the richer, the deeper like the test, the more ideally you could be valued by finding the signal from that. It’s also probably a better business for you financially. I’m sure there’s a higher pay rate for that. Can you just speak to kind of what you’ve seen, Philippe, in terms of, you know, as prices of sequencing will come down, I assume hospitals are looking to deploy kind of larger, more complex tests on their own and that directly benefits your strategy.

Where are we in that evolution like when you look at your portfolio of tests that you guys are applying SOPHIA DDM to, has there been a big shift towards these more complex panels yet? Do you think that’s coming and kind of how would that impact SOPHIA?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: So definitely yes, you start seeing like much more complex data being computed, which means both size of the panel, but complexity of the biomarkers, if you got HRD, MRD, I mean these are very sophisticated detection techniques. And I would say this is something we see both in oncology and in rare inherited disorders, right. So in oncology, we see these higher ASP applications for us. Again, HRD, liquid biopsies, MRD that get a premium because they’re very sophisticated. You also see that in the rare inherited disorders.

I think there’s a gradual shift towards whole genome, but I would say that remains still a small minority of institutions. What we now see is more consolidation of targeted specialized panel like hereditary cancer, pharmacogenomics testing, things like that. We have a new offering that we’re very excited about for 2025 called ANNEXOMES, where you take the backbone of an exome can be a clinical or whole exome and then you spike in specific modules that allow you to zoom in and find these what I call gourmet variants, right, the other insertions, your volume inversions that if you’re at the exome level, you’re basically losing the ability to find them because you’d see you don’t have the coverage. So we basically marry our technological bricks to serve customers with a bigger picture with exomes and then having the ability to zoom in very deeply into specific variants of interest. That’s a solution that gets a lot of traction, especially in The U.

S. We’re working on a few big large deals on this one we’re very excited about. So it’s not just oncology, we also see a very growth potential on the Raynor to disorder side.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So on MSK impact, I think you said with their 34, antibodies. MSK access, six zero seven MSK impact. So kind of where can that go to and how important is that for Sofia? I don’t think you break out your revenue contribution from MSK right now, but can you just speak to what you see as the opportunity for that? And how like, if we’re if we’re if we’re sitting here two years from now and there’s 200 labs that are running one version either the liquid or the solid tumor or both, how meaningful could that be to Sofia?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Yes. No. I think for us, it’s a, the MSK deal is a fantastic deal that we’ve signed. I’ll be on the record saying the collaboration with MSK is nothing short of excellent. Like really, there’s been, you know, like a fantastic partners to us.

Just so you understand the trends, right? So MSK Access, we launched in April 24, which is why you see now 34 customers with very fast ramp up of adoption in over 20 countries. MSK Impact, we launched in October, which is why you see a fewer number like the seven we reported. And also inherently that we know that the CGP market is a more competitive market than the liquid biopsy is. For us, I will focus on the liquid biopsy because I think that’s where the big ramp is for us.

You have a view of oncology that says liquid biopsy will become a de facto standard at some point in the future, right? The issue is today, I have a few central labs mostly in The U. S. That can run my assets. But if I was a farmer tomorrow launching a new asset on a ctDNA endpoint, I will derisk my regulatory program by going to a central lab in The U.

S. And then I fall flat on my face because there is no established testing base of liquid biopsy outside of The U. S. And even within The U. S, you have a lot of underserved populations, right?

So the vision we have with MSK is we want to make MSK access for Sofia EDM the de facto standard in Lipid Biopsy testing globally. So we’re deploying in these 34 sites. We have a pipeline of about, I think, 50 or 60 additional names that we’ve disclosed. So this is kind of a big growth driver. At the same time, we’re actively also exploring regulatory routes to put that into IVD status.

So we have nothing to share right now, but just to share the vision is to have like an IVD platform across the world that can support Lipid Biopsy Testing needs for biopharma and clinical. And again, same progress with MSK. So with the quality you would get anywhere in the world, it would be the same as you would get in Manhattan. So maybe Kellen, can

Dan Brennan, Follow Tools and Diagnostics, Cowen: you speak to I don’t know, I forget that Sophia has disclosed this, but back to that question in terms of small panels, bigger panels and then really big panels. I would assume it’s fair to say the larger the panel, the more opportunity is for Sophia because the price is probably going to be higher and you probably collect the price somewhat analogous to the depth and the and the kind of expense of the panel. Right? What kind of where do you stand today when you look at all the tests that you’re running on the on a sequencing basis? Is there a sense could you share with us and the relative size of that panel and kind of where that could go over time?

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: Yeah. Sure. Absolutely. So so two trends that are that are kind of overarching, what’s happening with with ASPs and also sophistication. So first, data is exploding, and in turn, more sophisticated applications are using are being used.

So, we published some numbers on the amount of data that’s coming off of our platform. And while analysis volume has maybe grown, you know, quite steadily, the data that’s coming out of those tests is even more. So I think data has grown more than 50% on a, on CAGR over the last five years, which is an incredible amount. And this speaks to the sophistication of the tests that are emerging, such as liquid biopsy, some of the things that we’re doing with with HRD and solid tumor has been a large kind of data test. And so what we’re essentially doing is we price, as you mentioned, based on the sophistication of the the algorithm that we’re running and the complexity of the bioinformatics.

And so if a test ranges between 100 and $500 per per, per run, our business model is is pretty simply volume times price. We’re seeing a move hopefully in the long term to more sophisticated solutions. Felipe has talked a lot about how liquid biopsy is becoming a standard. And so, what you’ll see is more, ratio of our of our, testing volume move to those sophisticated solutions. And and just to note on the liquid biopsy piece, if you look at our 24 numbers, none of the the liquid biopsy here, only a very small amount of those 34 customers are generating volumes and producing revenue, to date.

So 15 of the 34 have implemented those solutions. They will ramp up over the course of the year. We want to move the other 34 into to, to routine as well. And so as you’ll see towards the back half of the year, these applications will come on online. And then as we look further on to the future, you should see the more sophisticated test driving price improvement.

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Just one thing to add because we haven’t targeted, but like the business model is a volume based model. So the access to the platform is free and then you pay basically per use, which basically aligns our incentives with our customers. Because if the test is not good, they will not use it, will not get paid. But the wider point for us is you would do that if you were to bet that presume medicine will explode and you would ride the volume wave, which we very believe we are very much believed to. So if the volumes are going up, the tech complexity are going up as well, then that’s the way we’re riding.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So can you discuss your form of business model? So you’ve got a company like Tempest that has like a data lake, right, that they basically have and they apply their own algorithms and clients can run access to that data lake by years, by therapeutic type or get everything. And then you’ve got the other CLIA labs. Mostly, it’s like pharma will send them samples even though they have their own data business, send them samples and run them and send them back and the assays are oftentimes much deeper and richer. Kind of what’s your pharma business model approach today?

Is it evolving? Just kind of speak to the pharma opportunity. Sure.

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: So we have kind of two ways to think about pharma. We have one which is the DX side, so we diagnostics in terms of genomics and the other one which is the datamultimodal approach. So the DX side is basically the value prop is we have a global testing base. We have real world, real life and real time visibility on what’s going on in the testing base and we can deploy assay to meet pharma demands, right? So a good example of that is the partnership with AstraZeneca on HRD where they help us basically sponsor the deployment, the testing of our own solution, which was put under IVD to drive the testing of these patients.

They’ve done now this was so successful that we’re now doing the same with MSK access in lipid biopsy, for example. And so here you can think of the platform as being potentially like a CX platform of the future in decentralized fashion, right? That’s the division where we are going to I alluded to with MSK access, having a standard testing base under regulatory review at some point where you can basically deploy, run your clinical trials, you can run your assays once you’re post marketing from a pharma company. So really plugging that gap between the central labs and the rest of the world that doesn’t get access to any from testing, right? So that’s a big part of what we do.

And the second part is this multimodal approach where, as I mentioned five years ago, we started branching out to add to the genomics component, the imaging, the clinical and the laboratory data to do using AI in the platform to do like next generation certification of patients. We have a few public examples. If you want to go to the ESMO Congress with AstraZeneca, we did the analysis of their Phase three trial in immuno immunotherapy where we found a population that would have responded much better than the average. And the idea here for us, it’s more about inside generation with pharma, both on their data and our data to basically drive then hypothesis generation for clinical trial go to market and commercialization.

Dan Brennan, Follow Tools and Diagnostics, Cowen: So just on that second point, the multimodal set, just remind us on the data that you were running on the data you’re analyzing on behalf of all the clients that are deploying. Do you have access to all of that data in terms of your ability to manipulate that and de identified way and analyze of it? Like how are those contracts struck?

Philippe Munyu, Chief Product Officer and Chief Medical Officer, Sofia Genetics: Yes. So we basically have so it’s a project dependent view, right? So we have we can have access to pharma data or to real data. In the pharma data, the model, for example, could be like the one that in this project with AstraZeneca. They send us the clinical trial data.

We recognize it in Sofia and DiEM and we basically provide the predictors and the analytics that says based on this data, we think these patients would actually respond much better to the therapy. So it’s a trial data. And on the reward data, we have our own observational clinical studies where we collect those data. We have as part of the MSK partnership, we have access to all of the clinical genomic database from basically the last few years that we that they have. So we have a partnership there.

We can interrogate that data as well. And so we have now we’re now building a network of other institutions like money, like MSK that want to pitch in their data as well to do multi centric research. So this is something we’re focusing a lot for 2025 and beyond about scaling the assembly of this multimodal data stacks, which when you’re a central lab, it’s relatively easier because you basically are the recipient of everything, but then you’re limited to the test that you run, right? For us, it’s about getting out, harmonizing the data in a decentralized fashion, making these data talk to each other on the platform, harmonizing it, and then providing the analytics tool for people to actually integrate the data. So we’re they are breaking new rounds.

I don’t think that exists, which means it’s not easy either, but we see very high upside for the future there.

Dan Brennan, Follow Tools and Diagnostics, Cowen: Maybe final question. We’re based out of time, but do do you think as you look at where the stock is and you read analyst reports and you meet with investors when you can hear, which is terrific. Do you think there’s anything that the market is not really appreciating for Sophia?

Kellen Tanger, Head of Strategy and Chief of Staff, Sofia Genetics: Yeah. I think there would be probably many things. I think, well, first of all, AI has been a big thing, obviously, this year, especially in healthcare. We are a true AI platform. The solutions that Felipe has been talking about both in genomics and multimodal are embedded with deep proprietary AI technology.

I think there’s a story on just reaccelerating growth and reaching a certain amount of growth and then profitability hopefully in the medium term, will unlock certain things around the story. And then it’s tough because there aren’t so many companies that look like us who is a consumption based SaaS cloud platform that’s really a tech provider. And so, it’s difficult to compare us to others in the space in terms of what we’re doing and and some of the innovations we’re making. So it’s hard to join those parallels, but certainly we think some things are missing from the story.

Dan Brennan, Follow Tools and Diagnostics, Cowen: Terrific. Well, thank you both for being here. Thanks everyone in the audience. Thank you.

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