Welcome, Dan Brennan here. Day three of the TD Cowen Global Healthcare Conference, 46th annual. I think it's my fifth one right now. really pleased to join you on stage with the management team of SOPHiA GENETICS. To my immediate left, we've got Ross Muken, who will be assuming the CEO role come this summer. To his left, we have Jurgi Camblong, who's CEO and co-founder. Kellen Sanger is in the audience as well. Listen, gentlemen, thank you for being here. Thank you. Maybe we could start. You know, we'll kick it back and forth between both of you, but maybe we'll start with Jurgi. You know, it was announced back in January you're gonna transition to executive chairman, will also be promoted from president to CEO effective July 1st. Maybe take a moment to reflect upon, you know, the business you built co-founding it 15 years ago, and kinda why is now the right time to transition away from the CEO role. Yeah, 15 years, it's a lot. Yeah, 15 years ago, basically, what we had was a kind of a vision, right? We thought that, with the explosion of technologies such as genomics producing data, there would be a need for a tech platform that would basically compute data around the world and serve hospitals to enable them to better diagnose and treat patients. At the time, nobody was talking about AI. We're AI native ourself, and I think we came a long way from that idea. I'm very proud to say now what has been our impact. We've a network of almost 1,000 customers using our platform across 70 countries, analyzing about 35,000 genomics profiles a month. Thanks to that, basically being able to best diagnose and treat patients. I think, you know, over the years for us, one of the most important things have been to further demonstrate the scalability of this offering and to continuously improve as well the product market fit. Right now we're being working behind the scenes on some transformative things, both technologically but as well commercially on Ross' side. For me, it was very clear that, you know, getting close now to a $100 million AR, we would benefit from having another CEO, who wouldn't necessarily be a scientist, but who would have demonstrated to be a very strong commercial leader, very strategic, with a lot of instinct and maybe even better than I on knowing where to invest to maximize our return on investment. I'm very excited about the transition and, you know, basically, of course, as a founder, being always very engaged in the company. Ross wanted me to stay to support him as well, for a number of years. We don't know how many. We'll see. I'm very happy as well to stay with Ross and be his partner. Terrific. Yeah. Ross, Am I on? Okay, we're on. Can you hear me? All right, great. Just didn't sound like I was on. No. Great. Ross, listen, congratulations. Thank you. on promotion to CEO. Listen, you joined SOPHiA five years ago, CFO. Back in 2021, promoted to, I think, COO. You had this, you know, president, and now you're gonna have the CEO role. Just kinda how do you think about your priorities, once you'll be in the seat? Thanks. Obviously, you know, one, it's incredibly privileged to be able to, you know, lead this business. You know, for me and Dan, we come from the same world, right? I've been looking at companies across the space for 25 years. I really wanted to be somewhere where, similar to many of the companies you have here, I saw that journey from small to very big, right? I think SOPHiA has that potential, right? To be transformative in the space. You know, one of the themes you see across those most successful companies is you need the best talent, right? I wanna be a place where all of the, you know, best folks within precision medicine, AI, et cetera, come to work. We need to make sure that we attract that talent and we grow in that way. You know, the business itself today is doing incredibly well. You know, we just had our results yesterday. They were quite good. We'd like to see that growth continue to accelerate. I think you're starting to see as well some of the seeds that we planted over the last few years in a number of places also sort of come to fruition. As we move into larger, you know, types of compute, whether that's liquid biopsy, whole transcriptome, MRD, continuing to push at that sort of bleeding edge of innovation, but still being a bit of a fast follower and scaler and someone who enables access and effective cost depending on the geography. I think we have a real opportunity to leverage upon the network, right? You know, we'll soon be probably the largest company in the world in terms of producing precision medicine data. In that puts you in a really powerful position, having the data and having the network. The ability to leverage upon that with different types of capabilities, whether that's in the data side or in other types of diagnostics, et cetera, and working with more individuals within the hospital. Not just the pathologist, but oncologist, geneticists, and others. You know, that sort of expansion over time, which is kind of classic in the tech space from a network perspective, I think we have the ability to replicate, and that's how we're going to get to the materially bigger size that I think we can grow into. To me, you know, we've got a lot of the momentum and a lot of the pieces, and now how do we scale that? How do we, I would say, attract the best individuals so that as we're doing the scaling, right, we keep our culture, but we're also able to continue to grow materially and drive value for our shareholders. Terrific. Maybe, just on the guidance and then we'll dig into some of the businesses. You know, you basically for, you know 2025, to the revenue of, excuse me, 2026. Apologize. Right. You're guiding to 20%-22% growth, which is an acceleration right over the high-teens growth. Yep. from this year. As well, a major improvement over the prior year. You're seeing this accelerating growth which you mentioned, which is a priority. Speak a little bit to like some of the puts and takes on what's driving that accelerating growth, and then we'll dig into some of the details. You know, consistent with some of the drivers you saw from last year, liquid biopsy remains a really exciting, I would say, new category for us and an application on the platform that's of great interest both with our clinical and pharma customers. I would expect that to be a major driver. The U.S. for us right now is just on fire, right? You know, we had 50% growth of volume in the period. I think there's the potential to actually materially exceed that over the balance of this year, particularly as some of the larger wins we talked about come online. I think we'll be the fastest-growing company in the U.S. in this space this year. I would say as well, you know, biopharma, where, you know, we certainly had challenges going back to 2024, I think we've, you know, rebooted the strategy. We're seeing the fruits of some of the, again, efforts that we started to implement over late 2024 into 2025. You know, we talked about this quarter broadening out our customer base there. We've got some really significant wins that I think will prove out our value proposition, not just to the pharma who we work with, but to others. The ability to then scale that, I think is quite significant. As you know, you think about the momentum we came into the year with and those sort of factors, from a new business perspective, you know, I think we're well-positioned to continue to, you know, ideally show growth acceleration through 2026 and ideally as well into 2027. For your business model and the growth that you're hoping to achieve over the next couple of years, five years, in terms of the centralization, decentralization split, today therapy selections I think it's very centralized, right? Sure. Not that MRD is, I think, almost all centralized. Yeah. You just had a couple of big wins. Like, could you be successful if that split remains, just given the growth here? There's always going to be some decentralization. For your business to really be successful, do you need to see that decentralization occur? Yeah, I would say we don't really see... You know, I know in this community this is a phenomenon we talk about. We don't really see it the same way, right? We serve all players, right? I would say, and many of our biggest and most successful companies that we serve are central labs or reference labs, right? For us, you know, we are providing technology, and we're enabling compute at scale and menu expansion and efficiency, for anyone that is providing you know, precision medicine diagnostics, around the world. I would say, look, you know, we do see specific to the U.S. a phenomenon where at least for tests that have been in existence for some time, where the clinical validity is high and the reimbursement is attractive, we are increasingly seeing larger, you know, centers in the U.S. bring some of that capability in-house and closer to the patient. This is in line with what pharma is pushing for as well. We think that will be a phenomenon for the foreseeable future, and this is the trend that has happened in almost any other space that exists like this. There's always going to as well be innovative capabilities or tests, right, that academic medical centers or community oncologists are never going to develop on their own. Those will remain certainly, within, you know, larger, more centralized institutions because they're willing to take the reimbursement and clinical risk, right? To me, that's really the question. For us, at the moment, you know, we're having success, frankly, in all of the different type of entities that exist in the space, and we have no view of competition there. For us, it's our customers that are competing with each other, right? We're sort of indifferent, somewhat into what that customer looks like as long as they're aligned with us on helping the patient and driving the best outcome in terms of, you know, driving them to the best therapy and ultimately to being cured or at least treated properly. Great. Maybe if we zero in on the U.S. market, I think you announced yesterday a couple of these two large customers. I think it was on the MRD side you highlighted on the call. Exomes. Exomes, excuse me. Maybe just speak a little bit to the growth you're seeing in the U.S. You talked about this 50% volume growth which could accelerate. Just give a little flavor for the size of the customer base and kind of what's driving this acceleration. Yeah. We have now north of 100 accounts in the U.S. you know, I would say there's still a concentration of those that are a majority of the volume of revenue. You know, if you think about the 100+ logos this year, a disproportionate amount of that is coming from the U.S. business. The momentum here is significant, but it's also not just the momentum, it's some of the largest and most prestigious organizations, right? When you win those type of accounts, everyone else takes notice. I would say on that vein, we're really happy with the new business that we're bringing online, and we think it's going to be a game changer for us in this market and we're really breaking through. That being said, many of these, we're still only signing one application, right? The expansion potential we have in these accounts over multiple periods is really significant. It's hard sometimes to say that there's a structural shift in a market, but I think if you take a step back and you were telling me before you were at AGBT last week, you know, there's a fundamental shift happening, right? You have now the sequencer, which is no longer a bottleneck in the process, whether it's Ultima or Illumina or MGI or AVITI or VITARI from Element or the Achelous, right? There's a plethora of instruments available and chemistry available that you can now produce precision medicine data at massive scale quite cost effectively, right? So that's no longer a bottleneck in the system. You mix that with some of the automation advancements, whether again, it's Hamilton or Opentrons or Thermo or Beckman or whomever, right? You can now automate them with robotics, run a relatively small laboratory at actually quite high volumes with these instruments. You mix in, you know, sort of what we've done to, from a compute and algorithmic perspective, solve probably the biggest challenge, which is the data and the interpretation and the output, right? You can be a relatively small laboratory with one or two techs and actually run a whole lot of volume cost effectively and with where reimbursement sits. It's actually probably one of the most profitable endeavors that a hospital or community practice can push into. I think, you know, both at the lab side, but frankly more at the hospital administrator side, they're strategically seeing that's a big profit pool. Again, look at the size of some of the companies that you follow today and what their gross profits look like, right, serving this community. Hospitals don't have a lot of areas where they can make money, right? That's begging that conversation. I think with that, again, and it's not everywhere, but you're seeing an acceleration, particularly in applications where I think taking it in-house is not a huge lift, right? Do I expect, you know, sort of solid tumor MRD to get in-sourced in the next 12 months at scale? No chance. Yeah. Right? Too complex. Are there other applications where it's possible? Absolutely. Can you just elaborate a little bit on the applications? I think, you know, we saw a lot of interest in exomes, right? I think that's an area certainly most large institutions can run on their own, you know, and that encompasses hereditary cancer and carrier screening and pharmacogenomics, et cetera, as well as the traditional sort of rare disease testing, and inherited disorders. I think a lot of hematological malignancies and heme testing can be done in-house. I think frankly, solid tumor, right? I mean, there's no reason you can't run a CGP today like our MSK -IMPACT Flex product pretty effectively in any laboratory in the U.S. even liquid biopsy. Increasingly liquid biopsy. Still more complex, right? Just from a procedural perspective than solid tumor is because you have to change some of the collection and other elements. Increasingly you're seeing that. I mean, look, our, you know, 70+ customers have adopted MSK-ACCESS in the first 12 months. I mean, that we've never seen anything like that in terms of uptake. Some of that's also being driven by pharma, right? In that vein, you know, pharma again really wants that testing. One, they want the cost to go down, but they also want the testing to get closer to the patient. There's a lot of benefits to that, to them and to others. Can you talk a little bit about like the capture you talked, or maybe two questions ago, about a lot of these adoptions? Maybe it's one test. You have this land and expand strategy, right? When you look at like your revenue and you look at kind of the volumes and you solve for that like test capture rate, like you've got some of the, you know, MRD and CGP players, they're collecting thousands of dollars a test, right? Talk through a little bit about like the monetization that you're seeing today and like how much that average revenue per test? Sure. will change over the next five years. Does it go up incrementally? Does it go up significantly? Maybe, Jurgi, start with, you know, when we founded the business. Yeah. -what it looked like, and then I can give some color today on some of the newer applications. Okay. Yeah, well when we started, right, we were envisioning that definitively, you would have more and more labs and hospitals producing precision medicine data, that volumes would go up, complexity would go up, as well as, basically number of genes that would be analyzed would go up. At the time, we hadn't anticipated, to be honest, with you, Dan, that the ASP for data compute would increase, in the way it has increased. Back 2015 when we started selling, our platform, they were paying us $50 per patient, and right now the ASP is on $170 per patient. Yeah, to your point, I think there is a trend where people appreciate that the more complex the data become, the most heavy they become, the more value they are giving to the software maybe versus the equipment they have invested in. Today, if you think about some of our newer applications, they can be $300, $400, $500, right, per patient. That ASP mix still has quite a lot of room to be able to grow. You know, if you think about it as a percentage of reimbursement, it really depends on the region, right? If I'm in Latin America and more complex testing is done at $1,000 or $1,500, you know, you're much more limited than if in the U.S. you're looking at reimbursement at $3,500 or $5,000, and that now you're even seeing $8,000 or $9,000, right, for certain types of applications. Although I'm not sure that that's sustainable. In my mind, I think, you know, we want to continue to grow as a percentage of the mix because we think the value proposition we bring is greater. We also want to layer on top of it in, you know, we can talk about digital twins and other things. We want to layer on other applications and other intelligent solutions to keep building up the value of what we can get either per patient or per institution outside of even just pure diagnostics. Can you speak a little bit about AI and then the differentiation? The role of AI Yeah. What that enables your informatics, you know, the whole platform to do, and then B, when someone's gonna choose you, what's the alternative? I know, Ross, we've spoken in the past a little bit about your ability to call versus TruSight, but you know, there's other examples you can portray about like what you're actually delivering. Yeah. Well, actually we were AI, since the beginning ourself, right? Because bioinformatics is statistical data computing and so on. We're being always paid To compute data. We started with statistical inference and pattern recognition, then we moved to machine learning with deep learning. Today, we don't do generative AI because there is no point of doing that for our operations, but maybe in the future there might be use cases where we may have as well to use transformers. The most important thing to understand is that if you want to be very good on developing and deploying and applying AI technologies, you need to have been able to face a lot of diverse data, datasets so that you can train your models, right? I think people understand that now in this world, whether it's natural language or whether it's images, algorithms learn from being exposed to diverse and massive amount of datasets. That's why, in our case, owning a network where we are supporting almost 1,000 customers around the world, 35,000 patients a month, put us in an ideal situation to continuously be exposed to new streams of data, more and more complex, and develop smarter and smarter AI algorithms, right? How this is being materialized, so to your point on another conversation you had with Ross, is it enables you to be much more precise on what is being called secondary analysis, which means being able to properly identify specific mutations from the raw data that sequencers and next generation sequencers have produced, such as, for example, gene fusions or gene amplifications or very complex biomarkers like HRD, which are required for PARP Inhibitors, right? This has been continuously, for us, a huge differentiator. A second way for us of using AI, and in particular in that case machine learning, is because now we have almost 1,000 institutions using SOPHiA GENETICS, 35,000 patient cases today and ramping up in the U.S. in particular. They are taking decisions of diagnosing in the platform, right. We record these decisions. We can leverage on these decisions to better classify new type of mutations and variants and expedite the interpretation of a similar case in an institution where it's going to be the first time they are discovering this patient. You know, in the platform, most of our customers do interpretations in three minutes, right. You can imagine that how sophisticated our geneticists and pathologists, just by doing so, we already save a lot of money to the system. In the future, to the point of Ross on digital twins and so on, we may apply new models which might be a bit more sophisticated, a bit more complex, in particular with deep learning, to be able to project patients and see how patients are going to respond to treatments. I don't know if you had any follow-up to that. No, I think that's quite good. You know, the analogy I always use is, you know, for us, you know, people are now more aware of autonomous cars, right? If you were in San Francisco at JPMorgan, you can see the Waymo, right? Why did Google become more successful at that is the diversity of data and algorithms that they've seen over time allows you to then program and train a car to go in the streets of San Francisco or London or wherever. You know, think about many of the existing companies that play in our space. They're using the same instruments, the same chemistry over and over again. It's like they're driving in a circle, right? It's the most perfect circle you've seen. They're beautiful at doing it, but it's a circle, okay? That algorithm, if you tried to then use it and put it in San Francisco or London, wouldn't work 'cause it only knows the circle, right? You really need that deep data diversity or else you're not able to really have incredibly powerful algorithms, which is, again, I would say, why we're at such an advantage. With the investments we've made, particularly with Gen Two and some of the other elements we've invested in the back end that we don't always talk about, now we can deploy and incorporate more modern approaches and new technology very quickly. The lead between us and everyone else every day is growing, right? Which again is the most important thing of a network model. Again, going back to your prior question of decentralized, centralized, this is why a number of the centralized labs are coming to us, 'cause they're looking at our, you know, cost of goods sold per unit and their cost of goods sold per unit despite having big volumes for the U.S. and despite having home-built their own systems. They know that as we get to a million, you know, patients per year, you won't be able to keep up, right? Many of them are having to think about, "Okay, maybe I won't take your whole platform, but can I use those algorithms? Yeah. Can I use these capabilities?" "Can you fix this for me?" "I wanna bring on this menu item. I'm in all of these other areas, but I'm not in heme," right? "How do I launch that quickly," right? Again, there's no one perfect solution for it, but the investments we've made in being bleeding edge on AI has allowed us to really be meaningfully different, I would say, than any other business you look at from that perspective. We've gone 23 minutes, and we've only mentioned, I think, MSK-IMPACT once or twice. Yeah. I just wanted to understand on MSK-IMPACT, I think you mentioned 70 customers. Maybe just elaborate a bit on where you sit today with MSK-IMPACT. Is it like, obviously, it's a flagship product that allows you to kind of decentralize assessments around the world? What are the economics as well for you? I mean. Very good. Yeah, maybe just discuss that. First and foremost, to me, this is a real, again, sort of validation of our business model that, you know, the top academic medical center in the world that had, you know, these two marquee assets trusted in us to then bring those solutions to other parts of the world, right? The attractiveness is, you know, you're taking this Ferrari of a product that was built on the Upper East Side that only, you know, was touching 10,000 patients a year because it couldn't operate in other labs, and now you're deploying it all over the world, right? Including in other parts of the U.S. You have the clinical validation that had been done by MSK. You have the, obviously the brand behind it. You, with our platform industrializing it, now you can run it in places like Latin America at a cost base that makes sense for that market, right? If you were to send it to the USA at $3,000 or $5,000, like zero demand, right? If you can sell it in Brazil for $1,500, now there's a real demand for the product, right? We've been able to really, through open innovation, partner with these top epic academic medical centers, MSK being the first. Now you see- MD Anderson. us working with MD Anderson and the Mayo Clinic, and be able to take these technologies that only exist in these top centers and really democratize and bring that to the rest of the world at a price point that makes sense with attractive economics to us, and also brings back to MSK, right, you know, quite a lot of data and quite a lot of information. Also allows them as a academic organization to have real global impact, right. Which for them, I think is incredibly important. It's been a great partnership. We'd love to do more of this. The point is, you know, everyone shouldn't be designing their own liquid biopsy test. We know MSK-ACCESS, right, other than the other market-leading test, right, that you know, is the most validated test in the world. Same for MSK-IMPACT, right. Why shouldn't others be able to use this? That's what we want to be able to do, because otherwise everyone's going to try to do this on their own, and it's never going to work, right? They're gonna go to the send out model, which works for some, but frankly, most institutions would like to have this own capability themselves. In doing so, we want to create a global liquid biopsy network, and we think that that will ultimately be probably the largest, you know, player in that space. You know, that may take us some time, but so far the early adoption has been fantastic and MSK has been a great partner. Others really want to be able to work with them and us around this and will also enable other products like we talked about, like digital twins. What's the volume that you've done outside the U.S. with MSK-IMPACT? Have you shared that? IMPACT, we have not shared the volume on. You know, the competitor product is doing over $100 million of revenue, right, in market today. We're going after a very sizable immediate SAM that, you know, we think we have a better product suited for, and we're winning some of their largest customers immediately over the next probably 24 months. That's all access to liquid biopsy with that current? Yes. Okay. Maybe just, touching on the pharma business. It's still not at the point where you're breaking it out, but you're giving 31% growth ex-pharma yesterday. You're dropping a lot of hints. Just kinda help us think through the size of that business, the growth profile and, Sure. Yeah, just your, you know, kind of your strategy there. pharma is obviously still under 10% of revenue for us. We'd like it to be, you know, a much bigger contributor. You know, we, I would say, had some challenges, as you know, in that business going back to kind of late 2023, 2024, and we made some strategic choices, right? Particularly as we're pushing to profitability of really focusing our investment and also honing where we think we can compete and win. I think now we've got a real good feel, and we're seeing that market response. You saw four new contracts in the quarter, right? That will contribute in 2026 and 2027. Small, but can grow. One in particular is with a top pharma, right? That we think could be really substantial. I think we've figured out product market fit. I think there's a lot of momentum. You know, at JPMorgan, much smaller conference than this earlier in the year, I met with most of the top 20 pharmas, right? You know, we're getting now kind of the validation that we're on sort of the right place. Certainly we still have work to do, right? There's a lot of entrenched players in that market that are incredibly big and successful, and so displacing them is not easy. I do think we're making some inroads with a really differentiated model. Again, a global hybrid, centralized and decentralized model with data and algorithm capabilities. Stay tuned for more from us this year. We're really confident that business will return to growth and maybe by 2027 and 2028 much more material growth. Maybe just one more follow-up. Like if you drew, say, a pie and you looked at a lot of the R&D kind of sleeves, if you will, that pharma's focusing on. Yes. right? Where's the area that they're really utilizing SOPHiA for, if you had to pick one or two areas in that R&D continuum? Mm-hmm. Yeah. Right now, I would say, you know, in that sort of phase II, phase III, whether it's CDx, whether it's CTA, and then eventually deployment. Whether it's, you know, patient stratification, patient segmentation, really optimizing for clinical launch, commercial launch, that's today where we're spending a lot of time. We're moving back. You know, again, we talk about transcriptomics and other things. Right. We're gonna be moving back toward phase one in discovery, and then we're increasingly with some of the digital twins and other things, pushing into phase four in real-world evidence, right? You know, the practical reality is if I had an extra $100 million to spend, there's a lot we could do and we can accelerate this. We're obviously also very disciplined in trying to drive to profitability. We're trying to be very diligent with where we place the investments and again, very focused so that we can win in some very specific areas where we think we have a level of differentiation versus a Guardant or a Foundation, and we're doing quite well there. You know, ideally over time, we can expand into other parts. It's going to be a bit more, I would say, pragmatic solely because we don't have the capital to throw at some of these things, right, to really accelerate until we get toward profitability, which we'll be at in the next, you know, call it 18 months. Maybe like five years from now, does the company look very different? Hopefully, you know, the growth is gonna continue, but when we think about, you know, how you're situated, your business mix, like what's the future look like for SOPHiA? I mean, for me, you know, this is why I'm here, it's one of the few assets I saw across the space that I thought could really go from $100 million to billions, right? You know, again, going back and having been, and you've been around the space too, you know, there were a lot of very, prominent CEOs, you know, particularly the two legacy CEOs ago at Illumina had this vision of where, you know, NGS testing would go for oncology and other areas. I think we're best positioned today to be able to fulfill some of that vision. You know, even going back to Cerner and others, you know, trying to do population health, all of this is kind of coming together and AI is enabling it. you know, really being this intelligence layer for precision medicine and this AI platform for precision medicine to me is the future, right? I think we are at the crossroads of a lot of those mega trends. you know, having been around a long time, nothing happens quickly, right? you know, even again, going back to sequencing, Illumina, this big dominant player, I remember when they were teeny-tiny, right? people were questioning the validity of NGS taking on capillary and other things. I think, you know, we're at a, an inflection point. It's not gonna happen overnight, but I do think we end up growing up to be quite a substantial player. I think a lot of the, you know, competitors in market realize that as well, right? We have a lot of engagement with them, ideally, we're really helping transform how precision medicine happens in hospitals all over the world over the next decade or so. Terrific. Well, I think with that, we're out of time. Ross and Jurgi, thanks for being here. Thank you, Dan. Thank you very much. Appreciate it. Great job.