Illumina, Inc. - 1780182 - ILLUMINA INC

All right, good morning. I'm Doug Schenkel from UBS. It's my pleasure to welcome Jacob Thasen and Ankur Bhingra, CEO and CFO of Illumina, respectively. Thank you both for being here with us. Thanks for inviting me. Yeah. So today we want to focus our discussion on five areas just to give everybody a roadmap. We want to talk about growth. We wantto talk about results from Q3 and how that affects how we should think about Q4 and the path into 27. Then we wantto unpack a bit more on what's going on with core sequencing, clinical and research demand, and then try to get into a little bit of strategy. So an ambitious roadmap, but we're going to get there. So, Jacob, let's start with demand today and what needs to happen to deliver on the long-term growth framework. Starting with the state of the business, how would you characterize end market demand and customer purchase behavior heading into 2027? All right. So thanks for that. And let me start by saying this year has been fantastic for Illumina. We have had great momentum in the market. We have Q3 went very well. We were beating the expectations for Q3 and also raised for Q4, so raised for the full year, both on the top line and the bottom line. So we feel really good where we are. We continue to see very strong demand in the clinical space where we have seen consumables grow in the mid-teens. We have placed more instruments the last 12 months, or the X instrument the last 14 months than we did in the first year of the launch, which is, I think, have never happened before. I was going to say, I don't remember that happening at any point in the Illumina NGS era. Yeah, and some of the drivers behind that is, as I mentioned, first and foremost, the clinical business continues to have strong momentum, but also we went out here earlier this year and communicated a roadmap or innovation that will continue to really build out the opportunities you can do on the X platform, both in terms of better flow cells, more capacity on flow cells but also other innovations that and i think customers are seeing that is that when you bet on illumina bet on the on the x platform you are part of an innovation life cycle also so we excited about that the research market is still weaker it is improving sequentially but it's still it's the clinical that is growing so with that what we went out in 24 when we when we had our last time we were out there and talked about our strategy, we went out saying we would step ourselves into growth, where we believed that 25 would be the mid-single-digit growth, and then 26 would be mid-simple-digits, and 27 then would step ourselves into high single-digity growth. And we're still on that trajectory. It's going to be our consumables that will be the main driver that into 27 and we see that momentum um and we also communicated committed to an expansion of margins of 500 basis points x mna and we on track to deliver that also so to be clear uh 2027 we are very much on track for high single digit revenue growth and at least 25 and a half percent operating margin as a starting point well i i'm not here to commit to any uh you know guidance for 27, but that's what we communicated in our strategy and we are in that trajectory. Okay. Very quickly on academic government, building off of what you just described, post-election, it's only been a few days, but I would imagine the psychology of releasing budgets potentially has the potential to get better. Yeah. I think overall, I mean, I think in what we are seeing, of course, academic is a part of the research segment itself in how we talk about it externally. But there's no doubt that we have seen over the last month that the grants are flowing now in the system, and I think there is expectation also at least that the grants next year will be in the same level as this year. Maybe improvement, we don't know, but it's likely going to be in that area. So I think that part is better under control. What is still not, you can call it the algorithm for the individual PI, is still Not fully known. Who's actually getting the grant? And if I'm usually getting a few grants per year, am I getting the same level of grants? So I think that uncertainty still keeps the PIs from making longer-term decisions, especially purchasing instruments and other things that are still weaker. But I think, you know, you need a few more quarters where they get comfortable in how these so-called grant algorithms work, and then we'll be in better space. But at this point, we're not calling out that this turns of, I mean, improving in the market. We're just seeing that that is eventually going to happen. Clinical is the key driver to growth. We talked about academic government. Ankur, you and I over the years have talked a lot about the third leg of growth in biopharma. Are you guys seeing any increase in interest from biopharmacology, especially given what we're all talking about in AI, drug development and database generation so as we as you can see when we laid out our strategy in 2024 we also said there's a third leg around data and pharma services that we would start building a business on so we have we started investing in that business about a year and a half ago and we started talking about the billion cell Atlas that was one of our big foray to start building really differentiated capabilities and data sets, moving into areas where we can start getting to causality of biology and start proving that. That part is now, with the AI investments, is beginning to emerge like a brand new set of demand that we see a pathway over the next several years coming from that. So lots of discussions happening in the market across a variety of customers, whether directly within large pharma or the small pharma, as well as a completely new set of emerging customers within the AI space. So a series of discussions, lots of interest, and we think that we are very well positioned when that demand begins to show up eventually in our numbers, both from a technology perspective as well, as specifically from a reach and scale perspective, we're very well-positioned to be able to benefit from that. If I tie all of this together and try to bring it back to the high single-digit growth target for next year, is continued growth in clinical along the lines of what you've been generating, stabilization in the academic government and market, and some contributions from biopharma, is that enough to get you there? Or are there other things we should be contemplating as we try to figure out the bridge? And I think that's still the framework. That's always been the framework, which is around clinical, driving the primary demand, our consumables, and our X business, getting past the mid-single-digit growth. So the core sequencing business getting to that point, and the additional contribution of one to two points coming from both new products as well as the pharma services side of things. That framework still holds to get us to high single-digits in 2027. All right. One follow-up. Yeah. So if I'm doing the math right, two points of growth, I think that's like it's under $100 million in revenue, but it's close. I think it's around 90. What conceptually could you be rolling out that would generate that much revenue in a year? Yeah, so the series of new products that we have launched right now, if you think about the combination of our single cell, whether sold as a kit or as a service, if you Think about our spatial product, whether it's sold as as a kick or a service as well as the biopharma side of the demand, those three combined make up a big chunk of it. And then on top of it, we've also launched, we acquired Somalogic and now have it a year of being into the proteomic space, including an NGS-based assay, which is a very, very attractive data set given the unique capabilities the SOMA assay has, and it plays very clearly within both in the bioforma demand side, but also within the AI data set side of things, where the combination of whole genome and proteome gets you to a level of insight, which at a larger scale doesn't exist today either. So all of those combination has always been the case to get to that couple points of growth. Lastly, at least in this section, pricing. Obviously a key area of focus for years, really going back to the launch of the X. Are we on the cusp of pricing normalization? Yeah, so I think just to step back a little bit on how Illumina have been driving prices and then demand over the last two decades is that, you know, if you go back in 2006, 20 years ago, the cost of sequencing a genome was, I think, $6 million or something like that. Now we're down in the hundreds. So we have really substantially driven down the pricing to get to this point. But at the same time, there has been a substantially bigger demand. So there's been this elasticity game that has worked out very well. By the way, had Illumina followed Moore's law? had we been the Semicon, following that, we'd been a $50,000 genome today. So we've been beating Moore's law a lot. So if you want to be a Semicron, you would have been way behind where Illumina is today. So obviously, that's a strategy we still believe in, meaning that there is a lot of elasticity out there. But the algorithm is changing a little bit again here, that it's not only the sequencing. Driving down the cost of the sequencing might not get you to elasticity. And the reason is that the other components from a workflow perspective, from what a customer is actually seeing, where library prep, automation, software, and other things starts to be at the same level, you know, from a cost perspective. So, that's why we have shifted Australia into the highest quality inside with the lowest end-to-end. So, focus on the whole workflow for the specific application from our customers. So, we will continue to focus on that. And that will be application where we're saying, hey, sequencing is still very expensive. So we need to drive that down to get the elasticity going. But there are other areas, and I think you can look at single-cell, proteomics, spatial, and others, where the library prep is actually the driver of the cost. And you need to thrive that down in order to get more demand. So that's the way we think about it overall. But if you then zoom in and go back to the X, where we did, when we launched the X platform, we did take the prices down substantially. that we are starting to see, especially in the research space where we have most of our business converted over to the X platform, that headwind is behind us. Where in clinical, it's still happening a little bit, but the substantial part is behind this today. So there's more pricing normality now we are moving into. Yeah, and I appreciate you walking through that because if I think about it and if I'm listening right, there's really two parts to this. One is, with the old playbook, lower price drives elasticity. You're getting back to a normalized level. But importantly, price isn't the gating factor for a lot of applications. It's essentially the adjacencies. And when we think about things like Fluent and Soma, these are examples of what you're doing to basically not just reduce the cost of sequencing, but to reduce the entire bill of materials for customers. Is that fair? That's absolutely correct. that thinking just that cost per gigabase is the only driver anymore, that's what we call the old way of looking at it, but the cost of workflow, and in order to really drive that, that's why we went out for the fluent acquisition that was in single-cell proteomics with Somalogic, and we also come out with our own spatial assay here, which is good examples of areas where the cost of the sequence is actually the smaller part of the whole cost of the workflow. Another thing you talked about was the robustness of sequencer placements, X placements this year. You placed, I think it was over 95 instruments in the second quarter. It was still over 80 in the third quarter. Anything you can share in terms of replacements versus creating incremental capacity coming out of 2026? 2026. Yeah, so again, a step back here and think about what we have seen in the marketplace is that we had our 6K platform, as we call it, the old platform out there. It's still alive and doing quite well in the clinical space. There is a certain amount of customers simply stayed on that platform. It is a good business case for them or a good business for them. They have already validated the assay, and it still runs out there, There's then been many more that have actually moved on to the X platform. But when they have made that shift from the 6K platform to the X, instead of just porting the assay over, they built bigger assays because there's still a lot you want to look at from a genome perspective. So getting to a lower price point was not just capturing margin, but really to build and expand the insights you can get from the genome. So that's what we have seen. And that's where we're seeing that most of our customers today are expanding you know their capacity out there so we see some stabilization on the 6k platform all obviously still kind of you know moving a little bit downwards but but we see substantially more placements on the X that is more expansion rather than conversion okay but two quick model one questions it seems like in the fourth quarter you're expecting a reduction relative to it Well, something similar to Q3 in terms of the number of placements. Is that right? Yeah, I think just, I mean, you can go into it. But last Q4, last year was the start of what we saw elevated placements, so we did more than 100 placements in Q4. So we still believe that we would have an elevated placement here in Q5 this year, but, of course, it's a different compare we are up against. Okay. So that's more a compare issue rather than a demand issue. Okay. But sequentially, it is possible you could place more in the fourth quarter. in the third quarter. We would always replace all the, we'll sell all the instruments we can to our customers. Okay. But then for 27, we should think of instruments as not being a contributor to the high single-digit. Yeah, maybe Ankur, you will take that. Yeah, I think that's where we stand today. That's maybe a decent way to think about it. Given the elevated level of placements we've had in entire 2026, the instrument placement in 27 isn't the one that is contributing to the step-up. The step-ups up in growth is still largely larger install base we still look at consumables being the primary driver of growth within that again still largely clinical and then the and we talked about the contribution from the NPI so it's still very much a consumables driven. Okay and last model one question I think we should start to see an increase in utilization for box next year relative to what we've seen this year. Yeah great question as we've said especially within the clinical space our customers when they add capacity. It takes a little bit. Yeah, they're expanding laboratories, and it takes a Little bit longer to get the instruments up and running and getting them to the full capacity utilization. So the large placements this year certainly bodes well going forward from a consumables perspective. All right, let's talk about clinical as an end market a little bit, maybe more on whole genome sequencing specifically. um this has obviously been a fantastic story over the last few years as we look at the role you've played in enabling a lot of the most exciting things that we're talking about i mean certainly at this conference but you know more broadly than that uh not just on wall street but on main street as well um where do we go from here um and how does the move to broader sequencing You talked about the fact that most of the time when a customer moves from the 6,000 to the X on the clinical side, it's not the same assay. It's an assay where you're sequencing wider, you're sequencing deeper. Simply put, when we pull all that together, how do we think about the clinical growth outlook from here? I think you should, if you take the big view on this, is that we're not going to stop making bigger and bigger assays before everything is going to whole genome. And we are far away from that, meaning that if you look at a rare disease, yes, we're going from an exome to a genome right now. That's a 15x more sequencing. If you look into cancer, all of that, right now, if you Look for therapy selection, you might look at 500 genes. You have 20,000 genes, and then you have all the non-coding part of the region. You have a huge amount of expansion you can do over time. So, clearly, there's a lot more biology we need to understand in that, and thereby, if you look at the long horizon, there is plenty of room to expand into. So, I think that's what you will see, and that's just looking at the genome part itself. Then you can add the other omics on top of that. Clearly, the proteomics dimension is going to be more and more important. That's why we acquired the somologic business. So adding proteomics inside on top of it is going to give you even more insight. Of course, methylation, we came out with the five-phase library prep that allowed for looking at both methylation and at the same time when you look at the genome. So there's a lot of more. You can expand both looking at genomes and deeper sequencing, but you can also expand looking at more omics. And that's the direction the clinical business is going. So we believe that if you just look at that from a technology perspective, there's a lot of opportunities ahead of us. And that means that that market is going to expand for a long time in front of us, as always. Correct me if I'm wrong, but a lot of what you described is pretty critical to driving growth and improvement in outcomes in therapy selection, monitoring some of the more complicated areas, but better reimbursed areas of cancer care. What about screening? We're on the cusp of what seems like will be the first FDA-approved MSED. In CRC screening, you're seeing tremendous growth using assays that are run on Illumina. What about the importance of screening to your business? Yeah, I think it's still early days on that. I mean, first of all, I'm excited as a person, as a father and also a son, that my parents and, you know, the whole family here can soon get screened and actually get a good screen for early detection of cancer. I think this is something that is really going to have impact in how our overall fight against cancer. We all know that if you can find the cancer early in stage one and stage two, you have a tremendous better outcome in your, you know, recovery of the cancer. So that, I think, is super exciting. We're still in the very early days of this, both in terms of actually having very extremely good assays. I think we're starting to have good enough assays, but there's still a lot more we need to do. And I think that speaks to, again, this, that you need to see much larger assays going forward. But we are right now at a time where we get something that works well. But if you really want to look at the grantability, you need to sequence much deeper into this. So that is definitely something we are excited about. But we're still in the early stages. It's really not truly meaningful in our numbers yet. But over the next period of time, that will start to show up and be a growth driver. Yeah, and the one thing to add on early detection is you're seeing both sides of development, right, especially using multiomics. There's a lot of use of methylation. We're beginning to see approaches where proteomics is being added within the assay as well. And the direction of whether you're going to multi-cancer detection or a cancer-specific early detection, both pathways are improving dramatically, right? You're beginning to see approaches in lung cancer with stage 1A sensitivity of 70% plus, which is phenomenal to get to. So lots of good development happening in either multi-cancer or targeted as well. Yeah, it's interesting, right? I mean, most of the focus, understandably, has been on multi or CRC. It does seem like we're on the cusp of seeing some nice advancements in lung and other cancers. And very interesting multi-omic approaches being used, especially in the early detection. All right, so we keep talking about multi-omics, and you've done a lot in terms of making methylation cleaner and faster and more consistent. We've talked about somalogic. On soma, when do we start to learn more about the kitted soma approach on sequencing? Yeah, so just to remind again, when we acquired SomaLogic, most of their business was a service business, still a service business, and using also the array platform as the readout. We did work with, collaborated with SomaRogic before we acquired them actually to develop an NGS readout of the SomaMir. So that is in the market today. That is starting to, that is getting momentum. As always, when these new technologies come out, you need to get through the standard research to clinical continuum. So we are in that space right now where we get the evidence out. The proof points are really great. We had at AHSG here a few weeks ago. We had a great talk also showing that the performance of the Somalogic assay is significantly better than what is out in the market today. So we're really excited about that. But as always, you know, you need it in the hands of the researchers. You need the publications to come out to show it. And we're excited about what the evidence we're seeing. So the momentum is there. And we started to see it in The Numbers when Ankur was talking about some of the growth additions we will have next year. So Molartic is definitely one of them. And the Kitted Assay is definitely a vibe of it. Okay. I want to go back to academic and government for a minute. A lot of the challenges in that end market have been outside your control. I mean, it's been policy. I'll leave it there. I think the psychology, you know, hopefully starts to get better in terms of releasing. You know, the money's flowing. I don't think it's all getting spent. So maybe that gets better. The question is, are there things that you can do to be more proactive in working with those customers to basically drive demand? I mean, that's where there's a little bit of an old playbook, a traditional playbook to drive demand. What else are we going to hear more about what you're doing in that end market next year? Yeah, I think what we're most excited about there are some of the new assets we come out with, which speaks very well to where research is going right now. Our strata map assay that is looking at spatial is very, very well received in the market. It's the only one that is completely hypothesis-free, meaning that it will look at everything in the transcriptome, not only on the coding part of the transcriptomes. So I think there's a lot of excitement out there. We actually see more. We're still in the early stages of that, but we see more demand than we were expecting in this. So there's lots of momentum in that. So leaning into this right now, getting the academics to pick this up and get them to do some, just a few, and see that it actually works and works well in their hands, have been very successful. It is how we are seeding the market right now. So when the money is really starting to flow again, that that would be a focus area for them. We have a range. I mean, I think even the Somalogic, as we talked about, the Somascan and the Somaseq assays have a lot of interest from the academic market also. So we are seeing a lot of interest in that. So it's a lot of the things we have done here over the last few years. I mean, PerturbSeek has a lot of interest. We work with some great partners, for example, also to drive that forward. And we start to see a lot of customers that we have developed. We're developing the BillionCell Atlas, but then there will be a lot of customers, both research, but also in pharmaceutical that want to build their own you know, perturbed seek atlases on top of that that would combine it with the bigger atlas. So we start to see a lot of interest in that space also which is in the single sale area. And I think overlaying all of this, I think it's important to note there's more flexibility with your architecture than you've had traditionally. You have more menu that gives you more levers to pull to work with customers and I don't want to go back to pricing but you have a lot more flexibility than you did a few years ago to basically more dynamically price yeah i think that that's important again you know if we want to move in um for example in spatial i mean how do you really i think there's an opportunity here to uh disrupt that market also um you know right now spatial has been um researchers have done a very few samples in the studies because it's been so expensive to do that if you really want to do good research you need to get up to 50 or in the hundreds of samples to really get a good statistical view on on what's going on from biological perspective and so getting to that point and that's what we're trying to do with stratum also allow that to unfold i think it's going to be an explosion in in the understanding on spatial so we excited about that and that the way we that's again back to the highest quality insight for the lowest end-to-end cost and not only looking at one component but think about it what is the customer experience what are the customer challenges both from a price but also from an interpretation perspective we worked on all these parameters the software our software component is is super important here the whole dragon pipeline the dragon pipelines we have that makes it easy for customers to go in not only look at you want to look at multiomics You don't have five different softwares you need to navigate into. You can actually upload it all into our software and look at the different omics in the same software very easily. So we tried to make this super efficient for our customers. And the Dragon Compute, it makes it possible actually to get your results out actually within the same day, where sometimes actually analyzing could take days, if not weeks. And, of course, we want to make that experience better for our customer, but it also means they can go back and sequence more, right? So that's why, you know, building a customer experience is helping us drive more business. A lot of what you described seems like it would be relevant to the third leg, but maybe even broadening that, like very, well, specific to AI. I mean, we're talking about AI drug development. We're seeing new companies being created around AI. There's a demand for more data sets. And for a little while, I thought, like, wait, we haven't really made sense of the old data sets yet. Let's start there. But that's not what seems to be happening. Some of that is, but I think folks want these spatial data sets with more information. They want more single cell information. That's good for academia, but I don't think it's good I think it could be even bigger for you guys if these new companies or AI motivated companies start to lean in. One, do you agree? And two, are you seeing any tangible evidence that this is starting to happen for Illumina. Yeah, I think, first of all, we do agree that we think that there's a huge opportunity in front of us. If you step back a few years ago, everybody was saying, well, with AI, it's going to be very challenging for the tools companies to survive. Nobody is going to do measurement anymore. It's all going to being predicted through AI. Well, that might be a future, but I think that future is way far away. And in order to get to that future, you need to do a lot of data generation before you can start to really get those models to work. We are in a world right now, if you take papers that is out there from the scientific community, it's not always reproducible, the result that is coming out from one institute. And if you look for the next one, they have difficulty to reproduce it. And that means that if you feed that into a model, you have very, very noisy data that you feed in, and thereby also will have noisy outcome. So in order to really build data sets that can help that and feed your models to start to get into a predictive quality, I think we are having recognition right now, we're not in predictive quality at this point, you need to have large standardized data set. And I think that's a big opportunity for us to start to generate that with our partners. I mentioned Broke before, also they'll be doing this together, to set the standard for how that looks like. But also then on top of that, if you are an AI first company that wants to build your own data set, now you can actually add it on top off the data set we have created to help train your model. But I think it's also important in biology not just to focus on one dimension. We've been excited about the single cell or the perturbs seek and the billion cell atlas, but that's not enough. You need to look at, of course, both whole genome longitudinal data. You need zu look at many other functional data sets to really start to understand biology that goes beyond just one dimension. So I think that's important to understand that in order to get into predictive biology, you need to be able to look at many omics, probably of the same sample, and look at the different and, you know, perturb your sample, so to say, and see what the outcome is. And we are very well positioned for that. That's why the X platform, you can look at all these omics on the platform. We have the software. You can read it out and look it from the different angles. And we also have the power to build big data sets. So we're very well-positioned. But that said, it's still early days. It's still starting to happening. But I predict that over the next few years, this will be a real growth driver. How do you feel about your competitive positioning and going after these opportunities? I mean, there's been headlines about different providers working with folks in Asia. We had Roche here earlier today. I guess the question would be, are you seeing anything different now? And then as you think about the future, you described how are you positioned to capitalize and be the go-to partner? Yeah, I think we have a very good position. I just spoke to it, that it's not only about being the sequencing provider. It's about being able to build those data sets and not only sequencing, but doing the spatial, doing the single cell, doing the proteomics, and combine it all together. And there's so many more dimensions. When I say proteomics you can also perturb and get a proteomics output. We haven't even talked about that. Or you look at your many other types of models that you can use our technology for. So you can go out there and put press releases in that you are a sequencing provider. But that's not the point. The point is that if you just do that today, as I mentioned before, if you go out and you work with individual PIs, what the model will actually show is better to predict is what the PI did. And they can actually predict better the PI because every lab does things a little bit different. So you need to get into a place where you can build those big data sets that is reproducible, standardized. And we need to do that in one place and do that where this is setting the stage for the whole industry. And not only for one dimension, but for multiple dimensions. That's what we're focusing on. But look, I mean, look just at the, we don't go out and do press releases and every time we sign up a partner, but we have seven partners in our 1 billion set atlas. That is more partners that many of our competitors have ever signed up. So I think we feel really good about where we are. But we focus on the opportunity rather than go out and talk about each individual partnership. All right. In closing, and we've talked a lot about what has you excited about the long term. We've talked about Q4. We've talking about 2027. with all that in mind what do you think investors most underestimate about alumina well i think we have uh we have as as you mentioned before three strong legs that i think is going to play and i talked about the highest quality inside with the lowest end-to-end it plays in all markets it's placed in the clinical market going workflow focused especially in the decentralized that is up and coming um it goes in the as we talked about in the ai space because customers need full workflows full insight that is standardized reproducible and it goes also into the academic market um if you want to do a space shield you don't want to go and buy different things you want to get one vendor that can help you get your whole end-to-end workflow with the right price point and the right way to read it out and i think that is that is what we're building today we've talked about our ecosystem and how strong that is in the inside ecosystem. Imagine even a future where customers are coming not only to buy the sequences, the best in the industry sequences and our workflows, but they also come here, which they already do today, to get insights. Because the data we're generating right now, both in the academic market, in the AI market, but also in the clinical market is something that the customers, our customers can use for their interpretation and create even deeper insight. And I think that is a flywheel that is going to be super powerful for, for Illumina. And that's what we excited to build. That's what We're building that ecosystem up right now. So I think That is something That will keep us being the go-to vendor in the industry and the tools provider for especially NGS and of course, all the omics excited about that. All right, let's leave it there. Thank you so much, Jacob. Ankur, really appreciate you doing this. Thank you. Thank you very much.