10x Genomics, Inc. (TXG) Earnings Call Transcript & Summary

Hello, everyone. This is Rachel Vatnsdal from the Life Science Tools and Diagnostics team here at JPMorgan. Thank you so much for joining us for the first presentation of the day. I'm joined by the 10x Genomics management team. So as typical, this will be a 40-minute presentation. First part will be a presentation followed by a Q&A. So with that, I will hand it off to the CEO. Serge?

Thank you, Rachel. All right. So this slide contains important information about forward-looking statements we plan on making today. Now with that, I'll start with our mission. Our mission has been the same from the very beginning of the company, since the earliest days when we started. The premise for starting the company was that this is the century of biology, that life sciences is on an exponential trajectory driven by advances in technology and computation in the accumulation of biological knowledge. And that this trajectory, these advances are going to transform the world. You can think in terms of curing diseases, advancing human health, transforming the human condition. The key hitch, the hitch -- the key throttler to this trajectory, to this promise is that we still understand very little of the underlying biology. What we don't know, what we don't understand is actually much greater than what we do understand. And so our goal at 10x has been to accelerate the understanding, the mastery of biology to ultimately advance human health. And the key challenge, right, the most salient feature of biology is its inherent immense complexity. Each one of us is made up of close to 40 trillion cells. Each one of those has this enormous complexities of molecules interacting with each other in all kinds of complex and dynamic ways. And we posit that to address that complexity, you need tools, you need technologies that can measure biology at really large scale, at really high resolution that matches the complexity of the biology and that the legacy tool set of life sciences is not really adequate for that task. And that's what we have set out to build as a company. So in particular, the key to understanding biology is that you need to understand it at the cellular level. The cell is the fundamental unit of biology. And it is actually kind of a striking mind-blowing fact that up until fairly recently, we didn't really have the means of measuring biology at that individual cell level. You would take your sample, take all the cells in that sample, and you would mix their contents together to measure that mixture, which gives you an average profile. So this is kind of akin to, you're trying to understand how cars work, measuring how much metal, how much glass, how much plastic is in each car. But now for the past 8-plus years, we have had the technology to measure individual single cells. And what single cell analysis really gives you essentially is the parts list of human biology. And more recently, there has been an emergence of spatial biology, a new field that lets you see how cells and molecules are arranged with respect to each other in tissue. And that essentially tells you how the parts fit together. So these are really foundational things. And our view is that eventually, every relevant sample will need to be analyzed with single cell and spatial context. And so at 10x, we have invented, developed and commercialized technologies to give researchers access to this kind of information, the single cell and spatial information. We build instruments, consumables, software, and we strive to provide customers with end-to-end solutions to be able to analyze their samples, to be able to see biology that they could not see before. So our Chromium platform on the left here really catalyzed the single cell revolution when we launched it 8.5 years ago. Out of the gate, it was one of the fastest-growing technologies in the history of our industry, and we believe it's still very early days for the platform. Our Spatial franchise comprises 2 platforms, Visium and Xenium. Spatial is still a relatively new area, but growing really fast and is really poised to revolutionize multiple areas across life sciences. So the foundational strength of our company is our innovation engine. This is the ability to develop breakthrough products at speed and also knowing what products to develop. So since the very beginning, we worked really hard to build out deep expertise across multiple disparate fields and create the right culture, the right processes, the right structures to enable really tight multidisciplinary collaboration at speed, so you can develop many amazing products in parallel. And the way we approach things is that we think really hard about where the world is going, what questions researchers are going to be asking in the future, what projects they're going to be embarking on and then work backwards from there to determine what technologies and what products need to be developed in the service of those questions. And once we gain conviction, we move rapidly to bring great products to market. And so our innovation engine has been really productive across the years, many amazing products, many breakthrough innovations, revolutionizing multiple fields of scientific research. And so from the beginning, we have invested intensively in building out the right foundational capabilities to reach this kind of scale that we have now so that now going forward, we can keep leveraging the scale for more growth and more impact going forward. We have also scaled up our commercial organization for global reach and top-notch customer experience. We have a large global worldwide sales force, a best-in-class support organization that's really obsessed with customer success. We have really deep expertise across multiple applications with these really sophisticated applications. And we consistently hear from customers just how much they value our support organization. And it's important to appreciate that given the disruptive nature of these technologies of these applications, these markets, it's important, really important to have the commercial force with the right kind of expertise. We see our commercial organization as a critical complement to our innovation engine, both by virtue of them delivering all these innovations to our customers, but also because we're able to form deep partnerships with our customers, that allows us to see what questions they're going to be asking in the future, where they're headed with their research programs and then feed that information back into our innovation engine to build products that can reinforce our position in the marketplace. We have also built out really strong capabilities in our operations organization. The goal here is to be able to manufacture and reliably deliver products across the world. So to drive really high quality, high consistency supply chain control. And also the investments we've made give us really great structure, cost structure to go forward as we scale. And so as with everything else, we invest in foundational capabilities that we can then leverage as we scale. And that becomes particularly important as we seek to expand to more customers and more customer types, especially in some areas like translational applications and biopharma, where some of the requirements around quality, consistently supply chain are more stringent than others. Yesterday, we announced our Q4 and full year 2024 results. We had over $610 million in revenue, exceeding the high end of our guide. We sold over 1,000 instruments last year, and we maintained a healthy balance sheet. But the real story of the year was really that 2024 was a year of change for us. We launched multiple new products across all our 3 platforms. Any one of those launches would have been the story of the year. We did all 3 simultaneously in 1 year. This did entail some pausing among our customers as they evaluated the new products and to decide whether they should switch over their projects, their research programs onto the new products. But all these products have actually been met with really, really great customer response. Great feedback makes us really optimistic about the products that we launched and about how it sets us up for the future. We also, on the single cell side, introduced a number of new products with reduced pricing. And this is part of our overarching strategy that we have articulated earlier about driving the elasticity of demand. We believe there's huge potential to expand single cell further by reducing prices. And this is part of that strategy. And finally, we embarked on a major reorganization of our sales force to really match the growing diversity of our products and our customer types, again, to invest in the foundation to allow us to scale to the future. And so while all these changes entailed some near-term challenges, we do believe that we're confident that they're setting us well as we go forward for the long term. And the reason we have been making these changes, the reason we've been making all these investments is the tremendous opportunity we see in front of us. When you look at how our products are used, and this is by design, they're essentially replacing much of the conventional toolkit, all right, across the life sciences. They're not displacing any particular technology or any particular method. Rather, they're really transforming, changing the way that research is done. And so they're not also confined to any particular application, any particular therapeutic area. In fact, despite the fact that these technologies are relatively recent, it is really hard to think of an area of biology where they're not making a major, major impact. There have now been 10,000 papers in high-impact journals making use of these products across every field of biology, every therapeutic area, every disease driving really foundational fundamental discoveries. And the reason for that is what I said earlier, the cell is the fundamental unit of biology. And so we see this market as fundamentally not being constrained by applications. The endpoint to us is clear. Ultimately, all samples need to be analyzed using these approaches. But the question is really about the timing to get there. How quickly will scientists convert to this new way of doing science? And so when we think about the market, think about where we currently are and then expanding out to the labs out there that are using -- in relevant areas, that are using techniques, approaches that are adjacent to single cell and to spatial technologies. And if those labs were to adopt our technologies at the rate roughly of the current customers, then that becomes -- we see that as our serviceable addressable market, and that comes out at about $13 billion. If you then expand beyond that to all labs in life science research, and if they were to adopt our tools at the levels of existing current customers, that would come out to $21 billion, which is our total addressable market, which is still a relatively small fraction of the overall research tools market, which is $75 billion. Now it's important to note here, here, I'm focusing exclusively on the research tools market. This does not contemplate potential applications of these kinds of technologies in the other areas, especially in -- particularly in clinical context. And so regardless of how you look at things, our current revenue is only a tiny percentage of the overall market, which means we have a tremendous opportunity to grow and expand to more customers and more use cases. And so given this position, we have multiple levers of growth ahead of us. Among the main ones is, first of all, expansion within academia, within mainstream research. Our customers are still, by and large, concentrated among innovators and early adopters. And there is a great, great opportunity to expand much more into the sort of the middle majority part of the market and beyond. We started with these technologies very much in the realm of basic science. And over the past years, it's been expanding more into translational uses and especially with the recent advances we've made on the product side, with our [ viral ] technologies that are compatible with FFPE, thick samples, other advances we have made, there is more and more uses within translational research, and there's a huge opportunity for us to grow forward -- to go forward in that area. And third, we're particularly excited about potential in biopharma. We're particularly underpenetrated in biopharma at this point, between 15% to 20% of our business is there, there's potential to grow to 50%. And fourth, kind of underlying all of this, we intend to keep driving expansion through product innovation, to keep delivering lower-cost products to tap into elasticity to deliver new applications to keep streamlining workflows to remove -- to keep removing barriers and obstacles to adoption for more customers and more routine use. And so overall, our technologies are positioned incredibly well to take advantage of the set of opportunities in front of us. So first, on single cell. Chromium is the unambiguous leader in single cell analysis. It's the platform that catalyzed the single cell revolution. It supports a wide range of applications and allies. The system is really well known for really high performance, robustness, data quality, ease of use. It also has a huge ecosystem of data sets, publications, customers, protocols, and that brings a lot of value to our customers because it allows us to calibrate, get -- put their results in the context of other results, collaborate with others, onboard new applications, learn from their collaborators. And so the Chromium platform has come far in a relatively short amount of time. At the same time, we believe it's still very early days. The vast majority of biological research that could benefit from single cell doesn't yet. Which is why last year was the biggest year of Chromium product launches in our history. We introduced a new microfluidics architecture GEM-X and a slate of new products and capabilities. Once again, we raised the bar on performance, on data quality, on robustness, on scale, rolled out powerful new capabilities to improve ease of use on the sample prep side, core workflow, data analysis and all of that at a lower price as well. So we established a new standard for scale and cost. You can now run million cell experiments with a single chip, a single run millions of cells. You can also do so where you're reaching cost points of $0.01 a cell, really revolutionary. And also with our on-chip multiplexing products, you can now get down to $600 as sample doing single cell at any scale, whether it's just getting going with pilot experiments, whether it's expanding into more routine use at any scale. And so as I said, our goal is to democratize single cell analysis to drive it to ubiquity, to routine use. We believe there's huge elasticity in these markets. And this past year, we took major steps for enabling that going forward. Now spatial is naturally complementary to the single cell franchise. Comprises 2 platforms here, Visium, which is more focused on unbiased discovery using NGS and Xenium, which is more targeted. It's an integrated platform that uses direct imaging to the single molecule analysis directly in tissue. As with single cell, there's a wide variety of applications. These platforms have the best performance, best quality of data. This has been shown time and time again in multiple benchmark studies. They also stand out for their workflows and ease of use. Importantly, these platforms are compatible with FFPE and also allow you to do H&E staining and immunofluorescence on the same section as the spatial analysis, which makes us a natural bridge into standard pathology workflow, into translational applications and beyond. We see this as potentially the most significant technology revolution since the arrival of NGS and with potential to have even more impact going in the future. but it's still very early. In fact, some of the most fundamental capabilities just got established last year. 2024 was a big year of spatial product launches for us as well. We launched Visium HD, which gives -- enables unbiased whole transcriptome analysis at single cell scale. We launched Xenium 5K, which increased the plexing levels by an order of magnitude to 5,000. We launched multimodal cell segmentation, which is a really sophisticated approach for being able to identify single cell boundaries in your spatial data and much more in terms of content, in terms of software capabilities. And all of these got really great reception from our customers. And so when you put it all together, you really see we have the most comprehensive, the best performing and most widely adopted set of spatial tools in the market. It's also important to appreciate just how complementary these platforms are to each other. Heard a customer on say that biology is like a black box and the different 10x tools allow you to have different vantage points into that black box. And so having them under one roof provides a lot of value to our customers. And we see this time and time again where customers are using these platforms and combinations, Chromium followed by Xenium, Xenium followed by Visium and so on. So there's just a big advantage to customers having access to be a part of this 10x ecosystem in terms of getting the best insights, the best value and the best support across their research. And so we take pride in developing best-in-class products that push the field forward, the frontiers forward. And last year was really another great example of just the incredible productivity of our innovation engine. Going forward, we intend to keep leveraging our R&D capacity, to keep delivering more and more value to our customers, more applications, more biology, more investments in workflows and lowering cost over time. To take the best advantage of all that innovation and all this opportunity, we're also putting in place the right sales structures, like I mentioned earlier. And the key notion here, the key goal is to be able to execute on multiple different imperatives in parallel to make sure we can drive CapEx equipment sales, especially on the high-end for Xenium as well as being able to nurture and expand utilization among new customers, at the same time, being able to maintain our existing customers and help them expand the new application and into more routine use. And also, as I mentioned, putting in place a new structure, a new organizational structure around biopharma to be able to bring focus specifically to that business. And importantly, by virtue of clarifying that focus, this structure is set up to be efficient and leverageable for growth with only modest additional investment going forward. One of the most exciting trends over the past few years has been the expansion of single cell and spatial into translational applications, especially to enable larger cohort studies. We have had customers coming to us more and more now, telling us about interest in running big projects on clinical samples. Many are focused on cancer, some on autoimmunity, many on neurodegeneration, many other areas. And really, what they're looking to do is to understand the fundamental biology, look for drug targets, discover biomarkers, the end goal of really enabling precision medicine. We see this as early days of this trend, both in terms of the numbers of these studies and also the scale of them going forward. And while we believe we have only scratched the surface of what's possible in academia, we're even more excited about the potential to grow in biopharma. As I mentioned earlier, we're currently at about 15%, 20% of our business is in biopharma. We expect this to grow to 50%. And there is now increasing evidence, compelling evidence of the utility of single cell and spatial across the entire process of drug development from target ID to drug discovery to preclinical through clinical trials, lots of amazing use cases. And our goal, our opportunity now to extend those use cases throughout the whole ecosystem to more companies, more departments and our new cell structure is designed to do precisely that going forward. One of the most powerful emerging applications in biopharma and actually more generally as well are these large-scale CRISPR screens. And the idea here is to be able to use CRISPR editing at really massive scale to go with the single cell where the cell becomes a unit of experiment to make changes to genes in individual genes or in combinations to see their effect on biology. And this way, you can figure out gene function, find regulatory networks, figure out causality in a really, really rapid fashion. And this prioritization is an incredibly powerful way to accelerate science, find drug targets, test potential interventions. We have seen this becoming a big wave recently driven by decreasing cost of sequencing, advances in single cell and advances in algorithms and data analysis. Also, our GEM-X Flex assay, which we launched at the end of last year, is particularly great for these massive experiments because of its scale, because of its robustness, lower cost and particularly high sensitivity. So we're seeing lots of growth of this application across both academia and industry. People are now looking to use these experiments, very large scale, putting together with advanced algorithms to really build predictive models of biology. We see this as a really foundational direction because it's really about figuring out how biology works, which brings me to my final point. We have this great set of opportunities poised for great growth going forward. But on top of that, the world is now going through a major revolution, a revolution that will supercharge many of the things I talked about today. The revolution in AI has huge potential to transform our understanding of biology. And we're seeing a lot of interest among top cutting-edge scientists in building out virtual models of biology of cells, of molecules of tissues. Many of our customers are working on this. And the big thing about all these new AI advances is that they need a lot of data, right, a lot of high-quality data to be able to see molecules, to compile molecules, cells and tissues. And of course, that's precisely what we have built, the tools to generate lots of large-scale, high-quality data. Conversely, from our side, from the beginning, as we embarked on building out these tools, we knew that ultimately, the biggest bottleneck is going to be able to analyze this data. Once you produce this large-scale data, how do you go from there to inside. And the emergence of these AI approaches provides the perfect way to address that bottleneck. And so there's this incredible complementarity and synergy between the capabilities and needs of AI and the advances that we've been making with our technologies. And so we're really excited to be working with many customers to enable them to build ever larger AI models of biology of molecules of cells of tissues. And we see that this convergence of the 2 revolutions and on the life science side and on AI is really how we will ultimately master biology, transform human health and realize really the premise of the century of biology. So putting it all together, we're on the verge of a transformational time. As a company, we're in a great place, established leadership at the nexus of great technologies in large markets, really strong competitive differentiation, multiple pillars of growth going forward. And we have scaled the company to be able to enable growth going forward to leverage the investments we've made to achieve best-in-class financial profile. Thank you.

Perfect. Thank you, Serge. So maybe just first up for Q&A, I wanted to dig into the preannouncement yesterday. Congratulations on the nice solid beat, both on single cell and on spatial. If we look at your comments during the third quarter earnings call, you noted that you were really not expecting that typical 4Q seasonality given just where we're at from a macro perspective. So can you walk us through some of the drivers? Did you see a budget flush? Did macro improve throughout the quarter? And then was any of this as a result of some of the updated commercial reorg that you started as well?

Yes. Good question. So it's important to note a couple of points to make here. First of all, as far as the macro environment, I wouldn't call that out as being particularly different than what we saw early in the year, certainly in Q3. We did call out the fact that given how the year had gone, it would not have been -- we weren't expecting normal budget flush that you see every year. We did see more of that than we're expecting at the end of Q3. And that has -- was concentrated pretty much exclusively, I would say, in the biopharma area. So as far as our changes we're making on the sales side, this is very much a work in progress. We're really happy with the progress we have been making, but very much trending along the lines of what we were kind of expecting. It's hard to say -- it's hard at this stage to say that we should attribute kind of what happened in the quarter to that process. I think we would have been probably more challenged to capture some of that -- those budget flush dollars in the absence of, let's say, the new biopharma team in the organization. But it's still a work in progress, and it will take some amount of time for those changes to bake in and get fully realized as we're proceeding through the course of this year.

Great. That's helpful. Then I wanted to dig into the spatial numbers a little bit. Specifically just on Xenium, can you walk us through instrument placements for Xenium? How did that trend in the quarter relative to your expectations? Spatial consumables overall did much better than expected. So can you walk us through some of the drivers there on the spatial side this quarter specifically?

I think we're happy, obviously, with the results. I think, again, I would attribute that to -- compared to the expectations going back at the beginning of the quarter to somewhat more of a budget flush that we saw. We also saw just kind of as we proceeded through the quarter on the internal side, there was greater rigor in terms of pipeline management, funnel management, addition of opportunities to the pipeline. So that has been trending well. I do want to say that the macro conditions so far are fairly similar to what we had seen before.

Yes, then maybe just going back to your comments on the commercial reorg. So I appreciate it's still early days, but can you just walk us through what's the latest expectation for how long that transition will take? At this point, how many positions do you have open? Were you able to fill some of them throughout the quarter despite it being the holiday season? And what's just kind of the latest that we should expect there?

Yes. And I would go back to what we said on the last earnings call, and I think we're still on that similar path going forward. Our intention is to hire out the teams. And you also need to give a period of time for them to kind of bake into the new roles and new roles of -- new kind of roles and patterns of operating. And so we're targeting the middle of this year as kind of the point at which it's the team and the whole organization is functioning at full or close to full capacity. So we're happy with the progress we've been making. Again, trending roughly along the lines of what we were projecting, expecting. The team, the biopharma team in particular, has been making progress in getting built out. We've made some progress in hiring on the Xenium side, although there's quite a bit more work to do on the CapEx side. But yes, things are on track and proceeding fairly close to our expectations from before.

Perfect. That's helpful. So maybe sticking on 2025 then. So I appreciate that you guys are going to give guidance a few weeks from now. But just in terms of 2025, you've at least talked about the first half being pressured as we go through some of these restructuring efforts and also just the macro backdrop as well. But that said, you're also going to face easier comps. So given some of these new product launches, given some of the commercial reorg, how should we think about the drivers of 2025 at this point?

Yes. So there's kind of multiple factors at play here. Our kind of baseline assumption is, yes, the macro was a particularly challenging story this past last year. We don't expect it to get better. Don't necessarily expect it to get worse, but it's sort of -- that's our baseline assumption, right? And we did make a lot of changes, as I said, on the commercial side and sales force, and that's going to take some amount of time for those changes to work themselves through. And as I said, kind of we are targeting middle of the year for them to settle in. We're also -- we also launched a whole lot of products last year, especially towards the end of the year. And those products are meant to drive into elasticity as well. And this is one of the points we've been making that we want to be cognizant of the fact that when you kind of launch these products, the initial effects tend to be some amount of pressure on the top line as you have lower prices as that starts -- over time, that starts driving up volume. In the long run, it's absolutely the right thing to do because it drives the expansion of the market, drives the expansion of demand, but it merits being more cautious in the near term in terms of the impact on the top line.

Perfect. Then one of the trends on 2025 that I think all investors are curious on is just the funding environment. Given the new administration, there's been some comments regarding NIH budgets or just Department of Government efficiencies. So can you walk us through what is your outlook as it stands today on what we could see from a budget dynamic? And then have you seen any impact to customer behavior so far post the election cycle? And lastly, can you just remind us what is your direct and indirect exposure to NIH funding as well?

Right. So just first, maybe starting with the last question first. So as far as like NIH is concerned, you should -- the way to think about it is that something like half of our business, about 50% of our business is U.S., a little bit more. Of that, something like 40% is financed through -- funded through NIH or 75% of that, let's say, is academia and then something like 40% is funded through NIH. And so you get down to about 20% as NIH of the sort of total business. The direct NIH exposure is about a few percent. So relatively small. So even on the scale, even though we are often heavily weighted towards academia, despite that sort of the fluctuation in NIH, only have a modest impact on our business. I think in general, I think there was -- to some extent was a story of last year, sort of the expectation of what might happen with NIH. And I think some of what we saw last year was already customers anticipating sort of the uncertainty of the funding and kind of being more conservative and more cautious in their spending. So some of that has already been baked in even before sort of the election and to some extent after the election. I think it's important to keep in mind that while there could be a lot of consternation at this point, NIH, by and large, I mean, everyone, it's -- there's a bipartisan sentiment that people want to cure diseases, right? And after everything is said and done historically, NIH almost universally comes out in a good spot. And so I think it's probably most logical to kind of look to sort of the historical patterns and figure that there's not going to be some major slashing of NIH. But it is a reason to be relatively more cautious when I think about the rest of the year.