SOPHiA GENETICS SA (SOPH) Earnings Call Transcript & Summary

All right. Good afternoon, everybody. Luke Sergott, I cover life sciences tools and diagnostics here at Barclays. I have with me Jurgi, CEO of SOPHiA GENETICS. Thank you again for making. We're just talking to you -- your third time or at least being interviewed by me, second time at Barclays. So I guess what we can start here is, if you want to take a couple of minutes and go to the overview of the business and really what I want you to think about is how the business has changed over the last 12 to 18 months since you were here last time. And really the trajectory that you guys have going over for the next 2 to 3 years and the groundwork that you've laid and really kind of how you're expecting that to really flow through.

Sure. So it's a good question. And as you know, we went public in July 2021, right? And back then, there were kind of some questions about SOPHiA as well. And I think we've been able to answer to all those questions. So back then, we have demonstrated that our model, which is a cloud-based tech platform was very important in the field of precision medicine, what we call data-driven medicine. And we have demonstrated through the adoption of this platform in many countries and many hospitals that there was an eagerness of having such a platform for hospitals to compute data they would produce from precision medicine, in particular in genomics, but now beyond that, compute as well imaging data. The questions at the IPO time in 2021 were, was SOPHiA compatible with the U.S. market? I think that's a check now. We've demonstrated that despite the U.S. market is more centralized. We are compatible with that. We just announced, for example, that the reference lab called synergies, thanks for the usage of SOPHiA DDM. The second question was whether SOPHiA could go beyond genomics in terms of computing data and we have demonstrated, I think, in 2022 with a study called DEEP-Lung around non-small cell lung cancer that not only we could deploy those capabilities in a year time in 25 centers, including 6 in the U.S. to follow 1,500 patients. But as well that by doing so, we are creating value, right? And number three was okay, is SOPHiA the [indiscernible] capable of supporting the biopharma industry. And indeed, right, with our footprint, our technologies, our multimodal capabilities, we just announced that we send, for example, a deal with AstraZeneca, where we're leveraging all the data we gather in the clinical market and the technology to support them pre-approval of drug. So I would say last year has been a tremendous year for SOPHiA. We demonstrated that check, check, check, we could answer to these 3 questions. Plus Luke, we've been demonstrating that we could meet market expectations in terms of growth. We're being, to some extent, impacted obviously by the FX, given that most of our revenue is being down in euros. But outside FX, in constant currency and putting the little COVID business, the other side, we grew 44% in Q4 and 39% on the 2022 year, right? So pretty, I would say, substantial growth. And this with margins, which for the full year 2022 were at 68%. But I think a lot of questions that were around the model around the potential of SOPHiA have been definitively addressed in 2022, and we're very much looking for now to the future.

All right. So you finished the year 40%, 44% in Q4. you're engaged in AstraZeneca. So you have a deal with QIAGEN. There, you are working on a consortium. So talk about some of these partnerships, what you're actually doing there, the value you're bringing and how that will be -- drive long-term benefits for you guys?

So one side, our strategy is to create the biggest network of connected hospitals, right? And we do so by having these hospitals use our platform in the cloud while they are computing the data. And on the other side is to leverage on this data, in particular, with the pharma but to accelerate the penetration in the clinical market, partnership like the one we announced today with Agilent on a combined solution where basically Agilent is going to market their comprehensive genomic profiling solution together with SOPHiA DDM is a way to further penetrate accounts where basically eventually to our salespeople, we wouldn't be able to reach this account, right? And similar with QIAGEN, which indeed we announced now about a couple of weeks ago, where QIAGEN is going to combine their QIAseq consumables, so NGS consumables with our platform. So this type of partnerships are really enabling us look to fulfill Mission One, which is get more adoption of the platform in the clinical market and get more data. And then partnerships like the one we announced with Astra demonstrate, I would say, the value of this data. So the data that we gather in the clinical market are indeed valuable for the pharma and in the case of this lung data, this was interesting pre-approval for Astra, but we are being public as well about what we are doing with them on HRD testing for PARP inhibitors, which would be an effort that we would do with the pharma for the post-approval needs.

Okay. And so on the -- so you're really just driving both ends of the sword there. And so can we dig in a little bit more on the pharma side, how -- it's still really early penetrated. Where can you take this business essentially? Are they mining the data? Are you selling access to the data? Or is it more of just like a partnership? Will they have this drug, we can develop CDx for you in a comprehensive genomic profile?

So now we can run the strategy, we call the 3D, and everything is around data and ML. And the 3Ds are from discovery to development, which are pre-approval efforts, then afterwards, post approval to deployment. So if we take the example of Astra, we started working with them post the approval of PARP inhibitors, we are basically in many countries outside U.S. The testing was not done properly. And so they needed technology partners who could help deploy if you like into labs, collections for identifying a specific molecular characteristic, which is HRD for patients that may be eligible. And so this was really a post approval like effort. But then this enabled us to build relationship with Astra and realizing our technology, they realized that we could help on other programs pre-approval as well, right? And it is what we just announced with the data that we've been gathering around this effort called the plan, where we've been following 1,500 patients, took [ 100 ] clinical data points on non-small cell lung cancer patients.

Okay. And so when you're thinking -- when I'm thinking about the data generation from that, is that part from the partnership, are you able to then leverage the identified data for further partnerships? Or is that Astra's data?

So look, good question. So we never go exclusive ourselves, it is not until today. And that's the position we sell for. So in the context of this specific agreement that we signed, we're going to leverage on the data we gather in the clinical market. But as well on the technology we developed ourselves to compute this data. And so what we're going to do is you can use the algorithm that SOPHiA developed to compute data that Astra has already captured on their side, and we're going to compare the outcome of this data versus outcome of real-time real world data we captured. And so to be very specific to your question, which is a sensitive question regarding the access or the control of the data, at SOPHiA, we always consider that basically the data is being controlled by the hospitals. And so in most of the cases, we can sell insight, but we cannot sell the data. Now there are a few exceptions. This year, another very exciting partnership we announced Luke, with Memorial Sloan Kettering. And so Memorial Sloan Kettering was looking for a partner to decentralize some of their assets. So in that case, it's for 2 tests that they are doing locally. So one called MSK-IMPACT for comprehensive genomic profiling and one called MSK-ACCESS for liquid biopsy testing. And on top of that, they wanted as well to leverage on our clinical genomics database of 75,000 patient cases to help others leverage on those data for taking better clinical decisions, but as well as the pharma accelerate discovery efforts, right? And so in that sense, for example, we can indeed access, of course, with the agreement from MSK to this database for the format so that they can investigate this data and on that basis, be quicker in developing more targeted drugs.

And MSK gets out of it, those drugs are targeted, they're going to use their ACCESS and IMPACT tests.

Exactly actually for MSK...

It's like a broker?

Yes, it's like a broker completing without paying for producing the data and for MSK, I think that's very important to highlight because philosophically, it's important. The world, we are creating is a collective world, world like world of collective intelligence. And MSK understands that they themselves have unique data sets, but limited to the region of New York. And so what they saw is an opportunity while working with SOPHiA to help others, but in the meantime, put all these data from other regions as well in a common data lake so that themselves could as well get access to this data for research purposes. So it's really a win-win-win effort.

And so I mean, the opportunity -- like the seamless connectivity of the data and bringing all these different entities that have operated independently together makes total sense. Are you getting interest from the MSK. I realize it's relatively new, but other integrated networks as well?

Yes. So after MSK, we've been engaging with other university hospitals, and we haven't announced yet any follow-up. But indeed, we have a plan around that to expand this consortium to others.

And then ultimately, you can have -- if I'm thinking about it, you just continue to scale up instead of having MSK and whatever university hospitals that you can ultimately have this overall incorporated SOPHiA global provider network, where everybody is kind of kicking in and if you're left out in the call.

Exactly. You may remember...

That's why a broker.

We have done, and we wanted to create this wide sustainable health care sector where data of a patient today would be used to outside patient, that would be leveraged to help the next patients, right? And I think big academic centers like Memorial Sloan Kettering start to recognize that actually, SOPHiA being the only one being able to create this opportunity for the world.

Okay. And so from a competitive landscape, I mean, there's Tempus to Sema4, those are probably the 2 closest comps to you guys. How do you differ from them? And I mean the ramp that you guys are seeing, clearly, differentiated and offering something very different that demand, right? So talk about the differentiation there.

So I would say it was not by chance that others would see as well the same work, right? And the value of a collective world where data would matter and would enable from one side, oncologists take better decision. But from the other side, pharma develop more targeted drug and more quickly on the basis of those data. So indeed, you mentioned some of the efforts, I think, who recognize this value. Now our strategy has been quite different from others because the one you mentioned are Central Labs. So the way they operate from our understanding is that they get samples, they produce samples themselves. They may do or not some revenue or some profit out of it. That's their strategy. And then they leverage on this complex data assets that they produce themselves to help the pharma, right, where definitively the value has been confirmed if we refer to recent announcements that were public. So this is fantastic. Our approach is different one. Our approach is to build the same but actually in a decentralized way, right? So really, as a Puretech player, putting SOPHiA DDM, which is our cloud-native SaaS platform on the hand of hospitals and labs every day are producing data. Today, just as a reference point, we compute about 25,000 clinical genomics profiles amounts in the platform. So this is really at scale already [indiscernible] and then while we do that and we bring benefits to the hospitals and they pay us on news as a consumption pattern, we can, as they do, leverage as well on the data to work with the pharma. The good news is I think that us and others you mentioned are demonstrating the pharma the benefit of this model and that it's still very early, right? And that's the data sets that we may compute may be complementary to datasets that other might produce as well. And if I would be the pharma and I spend a lot of money in drug development, I wouldn't take the risk of missing up the development phase of my drug because I didn't get access to enough data early on.

Yes. No, that makes sense. And you're not taking the risk of actually having a run the samples themselves.

No. So in that sense, obviously, that's something that we need to better explain the market. Our costs are human, right? We don't have a lab. We don't have equipment. So as I think our numbers demonstrated in '22, we can increase the revenue while reducing the cost, right?

I thought that you will disclose your CFO is so good.

He is very good as well. But actually, recently promoted beyond CFO, being Chief Operating Officer.

So that's a good role for him.

That's a good role.

All right. So let's go forward here and think about -- so you get the big consortiums. You have this big network, you're providing data and solutions to pharma and the health care system. Talk about the penetration rates that you're seeing in Europe and then U.S. And then from there, we can go into further technology expansion portfolio.

So as you may remember, we started in Europe, right? And we put our platform in the market end of 2014. So we started making our first dollars in 2015. And we've been focused to the European market until at the end of 2018. And so then we started going beyond the European market. So today, we have 750 active customers, including 290, which are using the platform mostly and consume the platform mostly into 70 countries. And as you mentioned, U.S., of course, very important market because we started here more late, but this is a region where we've been seeing as well the fastest growth in 2022. So another very important proof point. And it's a market where today and actually being based in Boston, Luke, with my family, I move for 10 months. And so I'm very active as well in the U.S. market. And it's a market where we see a lot of eagerness of adopting SOPHiA DDM. And I would say even more today that the market is asking obviously, private labs, but as well indirectly public hospitals to be more efficient because our main competition in the clinical market is basically in-house by informatics. And this costs often much more in those on scale as well as our platform does.

And I would assume that over time, the incremental cost that needed to keep that software updated will eventually cause them to switch.

I mean completely, right? And so that's very interesting. So among the adopters, right? For us, the easiest to sign are either the newbies who just got to NGS and were sophisticated labs but didn't have sequencers. And because of the nature, I would say, of tie-ins and discoveries in technology, now NGS is being more and more decentralized. I heard this morning Prulab Pharma [indiscernible] making the same comment, right? So these newbies were using other molecular solutions, testing solutions, but not NGS, right? For these ones, it's obvious. They don't want to build an internal team. And then the other ones at the other extreme are large academic centers like Gustave Roussy in France, for example, which is probably the most premium cancer center in Europe who for many years wanted to do the data computing by themselves with their data scientists until they realize that when you have over 7,000 patient cases a year, it doesn't scale, and that is much more better for robustness and accuracy and cost and turnaround time to use SOPHiA or in that case, SOPHiA, at least an industrial scale solution. So that's a trend that we're seeing and maybe sharing some economics we realize that in some centers, we ask themselves to build their teams to compute about 10,000 profiles a year now. It cost them by $500 per patient to compute the data, which are software, cloud and people, right, so data centers. So definitively, I would argue that the more this industry will scale, the more you will see as it's very classical with any tech player that this will be industrialized and this should be good for us.

Yes. And as you have more content, it makes us so much easier as well.

Well, that's another advantage, right? So indeed, we mentioned even partnership like Agilent and QIAGEN and MSK, which are basically bringing content and applications to SOPHiA DDM. And of course, then for those type of players, if they have already adopted then SOPHiA in a hospital, if they want to launch a new application in precision medicine, let's say, testing in solid tumor. Our platform is already compatible, most of the time with their labs and so we can accelerate the launch of this type of new testing capabilities in a given hospital.

So let's sort of switch gears a little bit into compatibility and talk about the competitive landscape on the sequencing side. So a bunch of new entrants there, especially on the clinical side, are you -- I mean are you agnostic to those instruments? Is it -- is there a lot of investment that needs to be made to do backwards compatibility, walk us through that?

That's a very important question. And for you, it was an obvious one when we started our journey in 2011 with no technology and basically developed our technology with users, right? And when you would visit hospitals, you would realize that they all have different workflows. And there is a good reason why you have different workflows. And we recognize that this is something we couldn't change. We couldn't tell a hospital by at the time [indiscernible] or the Illumina, right? So indeed, we are agnostic. And just to give you an example, I was visiting one of our main customers 2 weeks ago in Brazil. When we started working with them back 2019, they were using only 1 Thermo Fisher sequencer. Today, they are using 2 Thermo Fisher sequencer, 4 Illumina sequencer and 1 MGI sequencer, right? And they grew very quickly with us. And I think they grew to some extent as well than to us because of our menu, because of our accuracy and because of our universality. So now that we see other players coming up, obviously, we see that with good adds, right, not because we don't like the established players, but just because we believe that genomics is still very early. And there are 17 million new cancer cases a year. Not everyone is being tested today, 6% of the population suffers from [indiscernible] disorders, right? So we need more devices into hospitals. And of course, this requires an healthy competition and different solutions depending on the different needs.

Okay. And so can you talk about -- because there has been a ramp-up in all these technologies, there's been essentially a pause in demand across the industry. So I mean you guys sit at the top watching it all flow through the system. So talk about the duration that you see within the system of the soft or this air pocket, if you will, and how you see it getting better?

Well, we don't see that, that was right? So I think our numbers demonstrate that, right? Our growth on a constant currency of 39% in 2022 is a result of more volume and improve the ASP, but more volume is the main driver in our model because we are being paid on consumption. So I don't know whether we don't see that because maybe many players bought sequencers, including at the time of COVID when they wanted to as well do COVID surveillance testing. And now they are reproposing the sequencers for other applications in oncology [indiscernible] disorders because others are, I don't know, launching new capabilities. But in -- on our side, we see volumes continue to grow. We see sequencers becoming bigger and bigger, so which means more and more volume. And so computing becoming more and more important. And we think that as it happened in the tech industry, for example, including with Oracle that, at some point, data analytics will probably be as much more value to the data production.

Yes. I mean, right now, that's one of the biggest hurdles to adoption as doctors don't want to -- they don't know what sequencing is. They have 15 minutes to figure it out. I just want a piece of paper that say you have cancer or not. Yes. So you clearly answered, you are filling a role on the back end of the analytics side. But the market is still driving forward from a volume perspective. Talk about some of the portfolio expansion opportunities that you guys have to really drive that land and expand consumption model?

Yes. So indeed, there are some applications that are, I would say, growing more quickly than others, right? So last year, we put in the market capabilities for HRD testing and related to PARP inhibitors. Today, this biomarker is required for ovarian cancer, but hopefully, will be as well at some point, applicable to other cancers, such as breast cancer and prostate cancer. And so this is an application with which we've been growing triple digit, like last year. So we expect to see strong growth on HRD testing. CGP will be an area of focus as well for us this year. So we announced that we had this partnership with Memorial Sloan Kettering, on MSK-IMPACT. Another one today, we announced with Agilent. We are already compatible with Illumina's TSO500. And then I would say beyond that liquid biopsy testing. So for us, it is still early. I think others have been very good at doing liquid biopsy testing as a central lab player. Now the oncology see the value of liquid biopsy testing for some type of patients. And I think leveraging on the MSK-ACCESS technology and brand within SOPHiA DDM, we expect as well the significant adoption at the end of this year because now we are in a stage where we are productizing that, right? So oncology definitely will be important, CGP multi-modality and pharma.

Okay. That kind of goes into my last question here on the guide, the 30% to 35% constant currency really kind of on par, if not a little bit of conservatism there versus what you did to end of the year. Walk us through the dynamics and how you see the year shaking out? And really what's baked into that conservatism?

So our model is a consumption-based model, right? So what we have in our models is everything that -- where we have a high level of predictability, which is what is already being produced and routinely computed in the platform. plus contracts that we have signed in the backlog but not yet in production. So in other words, when we signed a hospital typically, it is going to take them 3 to 6 months before they purchasing our platform for that specific application, right? So this run rate of usage of SOPHiA DDM plus the backlog contracts give us a high level of visibility in the future. The one thing that is difficult to predict today, Luke, is any significant biopharma contract that we may sign and where eventually would be a significant add-on to ROI.

All right. So it'll be upside from there.

I mean, hopefully, we'll have upside in the partnership as well with QIAGEN and with Agilent and with Microsoft are recent, we just gained 40 salespeople from Microsoft to sell SOPHiA DDM. So if they are successful, of course, we will have upside.

That's great. All right. Thanks.

Thank you so much. Thank you, Luke.

Very nice. Thank you.

Thanks.