Good afternoon, everyone, and welcome to RBC Capital Markets 2024 Global Healthcare Conference. I'm Conor McNamara, the Life Science Tools and Diagnostics Analyst at RBC. It's my pleasure to welcome SOPHiA GENETICS to the conference, and on stage with me is Ross Muken, the CFO and COO, if I'm not mistaken. Sorry. It's great. Welcome to the stage. Thank you for being here, Ross. Thank you for having us. It's our first time at the conference. It's been fantastic, so I appreciate you welcoming us. Have you got the kale chips yet? Because that's the sell. Okay. Well, I think I stayed too, so you have that to look forward to. So for those of you that don't know Ross, he's a legend on the sell side covering the space. So he's been up on stage a lot more than me doing these things. But that'll lead into the question of, you know, you've been on this side of the business, you've seen hundreds and hundreds of companies come through your door, through who you've covered, who you've decided not to cover. So after looking at all of those companies, what was it about SOPHiA that said, "Hey, this is where I want to be for my career"? Yeah, so for me, having seen sort of the evolution of the space, right? And I was talking with someone this morning who I've known for about 20 years, and I was recalling back to originally when we covered Affymetrix and Applied Biosystems, the first Illumina, right? And many others, you know, how sort of the sequencing space grew up. You know, I always had sort of a fascination in genomics in general. And then I would say, you know, over time, you know, I expanded my world and did a lot in software and health tech and other pieces. You know, I remember Jay Flatley, the former CEO of Illumina, talking about one day there'll be a company that can ingest data all over the world and be able to help unlock insights on disease and really advance cancer and rare disease in a number of these different areas. You know, that was originally somewhat in their view of where BaseSpace and other things were going, right? You know, I always became fascinated with this concept, also real-world evidence, and how can the patients of today help the patients of tomorrow? So I met SOPHiA and met Jurgi, our CEO, in a modest breakfast spot in the Geneva airport and learned the story. I was really compelled by what they had built and what they had done and really believed that it could be a business that could be scaled to really significant size, right? And can also make a big impact both, you know, on patients and on drug discovery and development. And so here I am. But you know, it's hard, right? It's hard building businesses. I've seen a lot that have been successful, a lot that have failed. And in the end, you know, you need a real end market, right? And you need a real product that's differentiated, and you need to execute, right? And you need the capital to be able to do it. And I think we have a lot of the makings of most of those pieces, and we have a lot of good fundamental drivers that's helping our industry that have been in place for a long time. I mean, more people getting sequenced on NGS-based applications, more desire to sort of unlock disease. Who doesn't want to live longer, right? I don't think anyone here wants to die from cancer or see a child with a rare disease. And so the funding is always sort of present. And so then it's about how do you take technology and make it happen, right? And it's not easy, but I think we're doing a pretty good job to move the needle there. Great. Thanks for that background. So if you just look, you know, you've seen a company that's, you know, gone from private to public, you know, super high growth. You know, your growth is still one of the highest in all of Life Science Tools. Right now you're on this path to profitability. You know, what are some of the key hurdles that you see going forward from here? Because you know, when a company makes those types of transformations in a short period of time, you know, sometimes there's some snags in the road. But you know, if you look at the company going forward, what are some of the hurdles that you may see and how you think the company will execute against some of those hurdles? Yeah, so one, I would say just to level set, it's really hard to grow a business while you're cutting costs. It's just not natural, right? Even if you're starting from a cost base that is elevated, just psychologically for employees, when they see, you know, you severing other employees or taking away system spend or refocusing on the R&D end, it's sort of even if you're doing well, right? Top line, it's just not a very natural feeling. So I would, one, I'll say it's hard, right? And so we recognized back in 2022 that the market was changing and that the preference for how long businesses would be funded at high levels of loss was going to be short-lived and that we needed to get on a path of sustainable growth quickly. And so we spent quite a bit of time, I would say, looking at where our dollars were going, right? So starting with R&D, you know, we have 20 projects, you know, in flight. Are all of them high priority for our customers? Are we sure each of them, the market opportunity is immediately there? Can we cycle them differently, right? And so when you start looking at that and speaking to the customer base, you can whittle down your list quite quickly. And then we started discussing, all right, you know, in our type of a business, are there things we can do in our infrastructure, our architecture with Microsoft, with NVIDIA, with others to leverage existing technologies to materially improve our cost structure, right, long term? And so we started some of those projects. So that really put, I would say, R&D under the lens of what's high ROI and what do we need to invest in now to take cost out later? And then on the G&A side, that's just, you know, plain X's and O's and sort of grinding it out, right? It's like, what do I need to do to close my quarter faster so the my audit costs go down? Or how do I renegotiate my D&O insurance? Or can I get by with not having this module of Salesforce and we do this in Excel, right? And can we fix this process and pull a bit of headcount out? So G&A is very much blocking and tackling, and it's what big companies do. And small companies don't do it well, but you have to be super focused on it. And then on the sales and marketing side, it was really around, all right, have I deployed my headcount effectively? Have I done my territory planning right? Do I have my front of the funnel correct in terms of my cost of acquisition of a new customer? Can I work with partners, right? Are there others servicing these folks that could sell our product, right? Do I have underperformers that I can call and then redeploy, right? So you just kind of have to take a look at the business segment by segment and really get deep into it and kind of understand where you're spending that capital. And it takes a lot of time, right? And it's not fun, but it's needed. And then once you get there, then it becomes a bit more habitual. And then you have to say, all right, I didn't expect this to come out. What do I do to offset it? And then it becomes a reflex of kind of being ahead of the curve with where costs are going and then being reactive around what you do. We also have the benefit as a software business. You spend the money upfront and then you reap the rewards of the revenue. So as I sell incremental new logos, new customers, or add applications, the costs that go along with it outside of commissions are very little. So my incremental naturally is quite high. So I then choose how much of that do I drop down versus how much of that, right, do I reinvest in some function? And so we also, I would say, have the advantage of, you know, unlike many of the other companies you cover, we don't have all the downstream service or revenue cycle or other needs that require more labor. Once the software is out there, it's now margin generating and it's quite more straightforward to drive cost. Okay. Thanks for that. And just you mentioned the sales force and kind of the sales process. And can you walk me through that? So you guys announced a certain number of new logos in the quarter. What is the ramp from time a logo is announced to when they start paying you guys and when they're at full capacity? Does that continue to ramp up through the life of SOPHiA? That's a great question. This is what we eat and breathe every day, right? Most software companies talk about land and expand. We're the same. I would just say the only difference is, unfortunately, you know, or fortunately, it depends on how you look at it. We operate in healthcare. And so everything is just elongated, right? If we were like a fintech or consumer tech company, we'd probably be much bigger today because things move faster. So from when a lead comes in to when we do our discovery meeting, we identify the need of what that institution wants to do from a precision medicine standpoint. And we sign a contract, can be 6-9 months, right? Which sounds long. In enterprise software, that's not terrible from lead, okay? We'd like to see that closer to 6 months, but let's say 6-9. Then you choose your solution. You want to go live. We can implement our software in like a few weeks. It's not really that challenging. The hard part is if they're starting on a new application, let's say solid tumor testing or maybe MRD-AML, you know, depending on what sequencer they have, what chemistry they have, what state they're in, what country they're in, the level of validation you need to do or the level of concordance you need to show sort of depends. So that could be what we call de novo routine, which is under three months to deploy. Or it could be sometimes nine or 12 months if you need New York State or another large regulatory body, right? So that is less in our control and also depends on their familiarity with the technology they're using. So today where you see people moving at some points off of some Illumina sequencers to other manufacturers, that could add 3 months is what we've said because people don't have familiarity with that chemistry or with the technology. So it's a long cycle. The good news of that is our churn is low and we have good visibility. And so, you know, while it takes a long time to get to sort of revenue, once it gets there, it's pretty sticky. And then once we get launched with an application, on average, since we've been public, we've grown our NDR about 125%-130%. So that means same store customers are expanding onto new patients or applications, 25%-30% a year. That's quite good in the software world. And we think we can do that for quite a long period of time, just given our menu. We today only have the average customer on about 2.5 applications out of the, you know, let's say 9 or 10 major ones that we think they can adopt. And so there's still quite a lot of room. And even if you compare us to other cloud-based consumption businesses, it's usually not until year 2 or 3 post-signing that you really get up to kind of run rate and true performance of that customer cohort. And so we're not that atypical in that sense either. Okay. So when a customer, after two years, does a customer typically all of their sequencing volume go through SOPHiA or is it that? I wish. Okay. So it really sort of depends, right? If they started with us and they're moving off of Homebrew, so where they were building their own solutions, you know, depends what else they're doing, but maybe. They're also still sending out often, right? Maybe they're sending it to Foundation Medicine or Tempus or Guardant or someone, right? So that would be more U.S. and Europe. It would be Eurofins and, you know, Brazil would be Dasa, et cetera. So it depends where you are in the world. So some will be doing their own or sending out. But if you started, let's say you bought your Illumina sequencer and you started on TruSight Myeloid or you started on TSO 500, you know, you might keep that. And then let's say you're moving to liquid add our MSK-ACCESS solution, right? So then you'll be running Illumina and you'll be running us side by side. Not the most efficient. We would argue they should harmonize and onto our software. Even TSO, their chemistry, we can run with our software. So, you know, over time, we try to basically convert the customer, but it really sort of depends on how much labor do they have? Where are they in their maturation? What other things are changing, et cetera? Yeah, because that's one of the things that, you know, we've talked about before is if you're in a large sequencing lab that has multiple different types of boxes, the advantage that you offer is you can have the same output on all the boxes, which I think is very important for a sequencing lab, whether it's on the clinical side or even on the research side. So I'm just baffled that certain labs don't adopt all the volume. And maybe that's just something that happens over time, but it would still be more efficient to have the same output. And there's a bit of like ego in it, right? So, you know, in some cases, for some of the earlier solutions, you know, if I'm at Stanford, right, maybe I wrote my own code and I built my own solution. We would argue, wonderful, impressive, hard to industrialize and scale. So you think about with like the NovaSeq X or the T7 or Ultima's box, just the sheer amount of data that's coming off these machines. It's going to be quite hard to manage that with other applications on other systems. Like I was just in the U.K., we're doing a lot of business now at the NHS and Oxford, more popular there, right? Home team. And so everyone was asking, like, can you support Oxford for the following applications? Because if not, then they're running like one part of their lab on one software and another part on another, and then the two don't speak to each other. And it's super inefficient. Okay. You can, right? You can use every. We can adjust our algorithms to essentially any platform. How has pricing trended? You mentioned, you know, all the additional output that's coming and even, you know, with Illumina and their NovaSeq X bringing costs down. So, you know, call it you guys get $200 per run, give or take. And as the price of the sequencing actually comes down, you know, does that make it more or less likely that your customers are going to pay the same price? Or do they ever push back and say, like, I'm paying, now I'm paying more for the software versus the sequencing? And then as the absolute volume goes up, like, is there any additional pushback just because the absolute numbers get so high that it becomes cost prohibitive for them to pay per click? Yeah. So for the most part, we fit into COGS or OPEX, right? And so as you think about it, and primarily COGS, as long as reimbursement is consistent, right? And we can drive them, I would say, better output. There's not much, I would say, focus on our element of price on an absolute basis. Now, what may happen is someone may trade up from a 100-gene panel to a 200-gene panel and maybe price doesn't double, right? Maybe it goes up 20% or 30%. So that improves the margin. And so on a same-store basis, we're trying to increase price about 3%-5% a year per customer. But then we're also seeing this dynamic that as the sequencers get more powerful, we're seeing a mix shift to larger and larger panels, which obviously produce more and more data. So if we would have made $50, you know, many years ago on like a 20-gene panel, today maybe we would make, you know, $200 or $180 on a 120-gene panel, but then maybe we'll make $450 on a 500-gene panel, right? So it also sort of depends on the complexity. So I would say, you know, you see Illumina now talking rightfully so around gigabase output per box growth. That's what we're levered to. We want more and more data being produced off of these boxes because ultimately, even if the price per gigabase is going down a bit, there's so much increase in the production that for us, there's growth for the next decade plus. Right. And we've spent this time talking about the software side. And, you know, one of the things that I think is lost is, and you mentioned at the beginning, this AI, this opportunity that you have in front of you to take all of this data that you have, arguably the most sequenced data out there, patient data out there, and monetize that towards the pharma industry. And so I think you've said you've had just over 1.5 million patient samples that have been sequenced. Is there a tipping point where you got to be above a certain number before that becomes a lot more valuable? And how close to where are we to that? And then how should you think about, you know, when does the pharma side of the business, when does that ramp up? Because that's consistently been less than 10% of the sales, but it does seem that that's an exciting secondary area of growth. So again, one, to sort of be able to do the second portion of what you talked about with pharma, you have to win the network. You need to have data streaming. Again, think about like Google as a concept, right? It needs all of us, but ChatGPT now, to input tons of data into the platform so they can build other businesses on top of it. Same concept for us. So we're animating precision medicine testing at scale in order to be able to produce and structure data in a way that can be useful for multiple parties long-term and to also draw insights off of that and to then deliver back value to the clinician and the patient. And so in that, you do, as you're saying, need to get to a certain scale, right, where you have an N of data that's valuable. I would say we're there, maybe not in all drug categories or in all biomarkers, but generally we're there. I would say what we really excel on more than pure volume is the diversity of data, right? You may have seen we just launched an initiative with one of the first cancer centers in Nigeria, right? We've gone into rural parts of India. You know, we're in Taiwan. We're in Vietnam. We had a piece of business in Guatemala and Costa Rica. These are not places, right, you think about in terms of, on a global basis, where complex genetic testing is happening. And so we can also flex the price point to really go to different levels. Even in the U.S., like we're in Detroit, right? Like very significantly. This is not a hotbed of, again, high-complex cancer care. We've got Henry Ford there, fantastic partner. You know, even in the U.S., there's sort of deserts for cancer and oncology. And so I would say in that, the diversity of our data set is also incredibly impressive as well as the breadth. Now, when you think about the pharma piece, you know, pharma, you know, has just gotten into the area of understanding how to utilize data effectively in the drug development, drug discovery process, but still they're incredibly risk-averse in many things. Depends where you go. You know, you've seen a lot of these AI-based drug discovery companies. They're used to taking risks. You take a validated development asset that's in phase II or phase III and you think about adding other, you know, sort of pieces on top of it much harder, right, in terms of the argument to do it. So I would say we're making progress. We're not where we want to be. We do think the mix of the business long-term can be better and more skewed toward pharma. We're, I would say, showing proof points on that. But it's going to take some time. I think, you know, even for businesses years ago, like Foundation, right, you kind of have to get into a repeatable level of where, you know, you find a soft spot or a niche where you can really add value and then you kind of can do that multiple times over. I would say we're still in the process of figuring that piece out of our go-to-market. So again, for us, it's exciting. I think there's a lot of growth potential there. I think we have the assets we need. But certainly it's going to take some time. Okay. Great. And then we talked about this briefly on your earnings call, but there was a webinar this morning, which I don't know if you or I missed it from the FDA on LDT regulation. I did not listen to that panel. But just give us some more color on how you think this regulation on LDTs plays out. Is it net positive, net negative for you guys, net neutral? And then just, yeah, let's start there. Yeah. In general, more regulation is good for us just because we have a validated platform that's designed under design controls. It's QMS-centric that already goes through a full validation program. So a lot of what FDA is requiring is kind of table stakes for us and our customer base. So if you currently have your own Homebrew and you have to try to go under a QMS system and do reporting and all that, it's going to be quite complex for some of the customers. So I would say it argues for them to move to a platform that's validated like ours. So generally, we would say this is sort of a positive development, I think, on behalf of our customers. Obviously, the way in which this is implemented and the timeframe, et cetera, can have impact. But, you know, I don't get the sense that our customers today, I mean, you know, many of them were not super thrilled about the legislation, but I don't think any of them are particularly worried or changing their buying habits based off of it. We're seeing, you know, and some of this is like the Invitae bankruptcy and now LabCorp is obviously the owner there, and there's been other changes in the space. Some of it is that and just other strategic changes happening at hospital institutions in the U.S. But we're seeing more openness to insourcing and/or a hybrid approach of running some of your own capabilities on a NovaSeq X or equivalent while also sending out some of the more esoteric stuff like MRD as being more prevalent than it's ever been in terms of that balance versus just pure send-out in the U.S. When, you know, Invitae, you mentioned it, but with a liquid biopsy company that has an improved test, why, you know, would you ever be in a situation where you're offering the software on the back end so there's a report that's customizable and consistent? If that's being sent to physicians, it seems like it'd be a much easier thing to duplicate versus what they're doing. Yeah. So without commenting specifically on them, I would say in general, there's actually quite a number of central labs that do use our software, maybe not to its fullest capacity, but many of them already use it for various different items just because we're better, if I'm being honest, in bioinformatics. And so it already happens. I think what's hard is if you've built and developed a program and validated or brought it through FDA, to change elements is not small or trivial. And so I would say it's always a bit of a challenge for them to maybe adopt broader unless we get there at the right time. But longer term, if you want to scale, I mean, again, you know, some of these players have 200 or so people, humans, that are doing annotation and things that we do with machine learning and AI. I mean, it's just not possible as we move to whole genome and other things to keep it up. So stay tuned. Got it. All right. And two questions about your revenue exposure. One, you know, we talked about the LDTs and you are underexposed to the U.S. So, you know, is there a tipping point where that reaccelerates and maybe it's this LDT regulation proposals or, you know, you've obviously announced some logos in the U.S. that, to your point earlier, will take some time to ramp? But at what point do we start to see the U.S. become a more meaningful part of the revenue? Or are you happy with the mix now? No, I think the U.S., obviously for us, needs to be bigger. It's our fastest-growing region at the moment and should be for the foreseeable future. We've had some fantastic logo momentum here. So you saw Mayo. Obviously, we're proud to be partnered with MSK. We've got folks like UCSF and UPMC. I mean, it's really a who's who of some of the large academic cancer centers here and ex-U.S. And so we feel like if those folks that are incredibly sophisticated at the top of the cancer rankings can see the value in the platform, we should be more broadly used. And so I would say, you know, we commented a bit this quarter on the pipeline. The pipeline in North America in general is super robust and we're quite happy with the potential, even if some of those pieces don't convert. Just given the size of it, it should argue for continued, I would say, outsized growth in North America. Great. I'll try and fit this question in. But the other mix is clinical versus research. And you're nearly, I think, about 100% clinical. So would you get to a point where you'd have a research offering? So, you know, that's not getting paid for by reimbursement. And how is that even an opportunity you would pursue? That's interesting you ask. We don't get asked it often. We're actually debating this recently. I think there is some argument via what we call our integrated solution to basically bring research projects to our partners. Think about setting up like a preferred network of almost CRO-like entities that produce precision medicine data in a number of geographies and then helping funnel research and other business to them on our platform so that it could be harmonized and pristine, et cetera. It's something, you know, historically we hadn't done much of just because there's so much to do in the clinical market. But given some of what we're doing in pharma and then given some of our newer relationships even on the clinical lab side, it's been something that, particularly around MSK-ACCESS in liquid biopsy, that's come up quite again and again. I think there's an argument that that tool as well could be used quite effectively in research. We can be super cost-competitive with it as well. Well, fantastic. Well, Ross, thanks again for joining us. This was a great meeting. Really appreciate you having me at the conference. Thank you for having us again, Connor. You do great work for us. We appreciate you hosting. Thanks, everyone, for joining.