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

All right. Good morning, everybody. I'm Tycho Peterson from the life science team. Welcome to the JPMorgan Healthcare Conference. It's my pleasure to introduce our next company this morning 10x Genomics. Just a quick reminder, there is a submit question function on the website if people want to have questions asked during the breakup. And with that, let me turn it over to Serge.

Let's start with the slides. Thanks, Tycho. Hello, everyone. Let's go to the next slide. Before I move forward with the presentation, I wanted to invite your attention to our safe harbor statement on Slide 2 and to visit our website for additional disclosures regarding any forward-looking statements that are made during the presentation today. Next slide. Last year, again, the company had very strong performance and execution. Our revenues recovered strongly after dropping precipitously because of the pandemic. Our instrument installed base grew by over 40% and is now at over 2,400 instruments around the world. Outside of the impact of the pandemic, our customers, on average, use over $150,000 a year in consumables per instrument. We now have 1,000 patents and patent applications that have risen out of the innovations underlying our products, and there are now over 2,000 peer-review publications that have come out of our customers' labs. This is more than double the number from last year. Next slide. And it's not just the number of publications, but also their impact and breadth. Our customers have been making fundamental discoveries across oncology, immunology, neuroscience, infectious diseases. In fact, it's hard to think of an area of biology that has not been affected by the discoveries made using 10x products. Also, last year, expanding from basic science, we've seen a large increase in the number of papers focused on translational research with potential for clinical applications. Next slide. Last year, we also shipped multiple new products, including a new instrument in Chromium Connect, our combined epigenetics and gene expression solution and the next generation of our immune profiling solution. The team also made great progress on a very ambitious product roadmap, some of which I will describe in a few moments. Next slide. Last year, we also made 2 key acquisitions in ReadCoor and CartaNA, which together with our internal innovations will form the foundation of our third product platform in the emerging In Situ field. Through these acquisitions, we obtained great technologies, great teams and a strong intellectual property portfolio, including over 100 enabling patents covering multiple technical approaches. And going forward, we intend to invest extensively in this platform and build many great products for our customers. Next slide. We have also deepened our global reach by building out a new manufacturing center in Singapore and significantly expanding our commercial organization. We now have close to 300 commercial employees supporting a diverse revenue profile with 50% of our revenue coming from outside the U.S. And we have now expanded well beyond our initial core sophisticated genomics customers to a much broader universe of biology researchers, customers who care much less about specifics of technology but are much more focused on questions of science and medicine. It's been incredibly rewarding to reach this kind of impact so fast. But what's truly exciting for us is that this is just the beginning. Next slide. This is the century of biology. Because of advances in miniaturization, computation and compounding effects of accumulated biological knowledge, the progress in the life sciences is in an exponential trajectory. Some of the greatest value creation opportunities in history are ahead of us. Opportunities like curing cancer, like solving Alzheimer's, getting rid of the infectious diseases. All of these advances are becoming tangibly possible, but they will not happen tomorrow. They will take time, but we see them unfold over the coming years and coming decades. And the key challenge to realizing the future, to realizing this potential is that we actually understand very little of the underlying biology. What we do not know and what we do not understand is vastly greater than what we do understand. And addressing this challenge requires building new generations of tools and new technologies to measure and manipulate biology. Because that is how we will accelerate our understanding and ultimately our mastery of biology. Next slide. And so from the beginning, we built 10x with that premise in mind. Our goal was to become really good at building technologies and tools to lead this revolution in the life sciences that entail being good at a number of very different disciplines. This is something we invested and nurtured from the very beginning. We built deep expertise across chemistry, biology, hardware, data; worked hard to set up the right processes and culture to enable tight multidisciplinary work. And we have innovated across all these areas, pushed the state of the art and put a lot of the innovations together into the products we brought to the market over the past several years. Next slide. Because most of our customers are biologists, not technologists, we strive to build products that are complete end-to-end solutions. Starting with the customer sample, going through the laboratory workflow through data analysis, through visualization to get as close as possible to the answer that our customer, the research is looking for. We sell instruments. Those provide a source of upfront revenue. Then, our customers purchase consumables from us in order to use those instruments for different applications. This is a source of recurring revenue. The consumables include enzymes, different chemicals, microfluidic chips. They're different for different applications. And the customers have to buy consumables from us in order to use the instruments. We then provide the software for free to enable the full solution. Next slide. Now these products have enabled our customers, the researchers to make incredible new discoveries. And perhaps the greatest revelation of the last several years of biological research, again, much of it enabled by our products, is the pervasive cellular complexity that underlies just about every biological system. It turns out that every tissue harbors much greater diversity of cells and cell types than we had previously thought, all of them interacting with each other in a complex interplay of massive gene expression networks. And what this implies is that to understand biology, we need tools that can measure these systems at the right resolution and at massive scale. And in the absence of that, it's incredibly difficult to make progress in science to understand disease or to develop therapies. Next slide. And to give you a sense of just how difficult and what we mean by resolution of scale, on the left is how the world had been measuring gene expression until recently. You would take your biological sample, take all the cells in the sample and mix their contents together and then measure gene expression profile of that mixture. And that gives you an average profile of gene expression across the cells in your sample, effectively hiding all of the underlying complexity that you see on the right, where now with our chromium platforms, for the past several years, you can take your samples, separate out all the cells across thousands to tens of thousands of cells and measure gene expression profile for each cell individually. And now you can see all of that underlying biology that was previously hidden. Next slide. So going forward, it is unambiguously clear to us that in the future, the vast majority of biological tissue samples will need to be analyzed at large scale and at high resolution. And we have been investing in 3 core platforms that together will enable precisely this future for our customers. First, the Chromium platform, which I just mentioned. The way it works is that you start with a solution of cells from bladder dissociated tissues and each cell is then individually interrogated to measure gene expression or other analytes or a combination of them. And the results of this interrogation are recorded in fragments of DNA, which are then read on a conventional DNA sequencer. This generates massive amounts of data that gets processed using our software. Chromium could tell you what is happening in your sample in individual cells, the fundamental unit of biology. Now with our second platform, Visium, you can tell where things are happening. Visium is a new platform. It's been on the market for just over a year. And here, instead of dissociated cells, you analyze slices of intact tissues. You put those slices on special microwave slides, then the molecules from the tissue slide are captured on those slides. The information is recorded at DNA fragments, and those fragments get decoded with a DNA sequencer and then with our software. This is quite similar to Chromium, but you capture information about where the molecules came from. And third, as I mentioned, we have recently started developing of our third platform for In Situ analysis. The idea behind In Situ is to measure large numbers of molecules directly in their native tissue and with subcellular resolution. This is different from Chromium and Visium or most current analytical techniques, which require that molecules be removed from tissue before measurement and analysis. Within In Situ, we will build an integrated system, which can be viewed as an analogous to IHC or FISH-based approaches, commonly used in pathology. But scaled to vastly greater multiplex levels with vastly greater amounts of information content. In situ capabilities will be highly complementary to both Chromium and Visium. And in particular, In Situ should serve as a natural validation tool for discoveries made using those 2 other platforms. And as more research and more translational work gets done with Chromium and with Visium, In Situ will provide the natural format for many of these applications to be adopted in the clinic. And in the long run, we expect just about every tissue will be analyzed using at least 1 of these 3 approaches, whether for basic science research or for medical applications. Next slide. In fact, our products are already starting to sweep away many of the conventional tools of standard biology, and they're doing this across the life sciences, across what are conventionally viewed as distinct market categories, whether it's molecular biology, cell biology, protein biology or even just generic commodity lab equipment. Next slide. We previously outlined our near-term market opportunity within the research tools market as those areas are where people are already looking to do high throughput research like next-generation sequencing, microarrays or flow cytometers. This represents about $15 billion right now. And as more research moves to the high-resolution, large-scale way of doing science, more of the rest of the life science research market will become available to us over time. Next slide. In addition, there will eventually be many powerful clinical applications based on single-cell and spatial analysis of tissues. Our In Situ platform will be perfectly positioned to bring many of those applications to the clinic. If we make modest assumptions around numbers of potential samples in pricing, we estimate that the size of this opportunity is around $10 billion. And while clinical applications represent an exciting set of future opportunities, the biggest needs and opportunities in the near term are in discovery and translational research. And we're investing aggressively in our Chromium and Visium platforms to accelerate that research. Next slide. The Chromium platform was launched in 2016 and ushered in the single-cell revolution that has been affecting just about every area of biology. Since the initial launch of single-cell gene expression, we have released many new capabilities and versions of our products, focused on expanding the range of applications supported by the platform, including immune profiling, epigenetics, proteins and multiomics. The platform has quickly reached over 2,000 labs, and it is clear that this is just the beginning. Single-cell approaches will become the standard for many types of biological experiments across tens of thousands of labs around the world. Next slide. And to build on this momentum, we're investing aggressively in product development to further accelerate Chromium adoption. We're doing this along 4 major directions: affordability, sample prep, informatics and addition of new capabilities to the core platform. Our goal is to bring new customers into our ecosystem, increase usage by our current customers and to keep opening up new applications and use cases. First, on affordability. Our customers often say that they have large studies, many samples that they would love to analyze with single-cell resolution. Unfortunately, the cost per sample is often too high, and they end up take -- needing to take and choose a subset of samples to analyze with Chromium. The rest of them using all their less informative technologies like [indiscernible] sequencing, microarrays, PCRs, ELISA's. To address these issues, we've been investing in new products to reduce the cost of single-cell experimentation and increase its usage. Next slide. Last year, we launched our targeting solution, which can reduce the sequencing portion of the cost by up to 80%. Instead of sequencing the full transcriptome, our customers will only need to sequence a subset of genes. This is an end-to-end solution where customers can order prevalidated panels or they can construct their own custom content to focus with just the genes they care about. Next slide. In addition, we're now launching a new product called CellPlex, which allows our customers to combine multiple samples together to rather than a single 10x channel. We developed a special chemistry, which is part of a complete solution that includes reagents and full software support. CellPlex can reduce the cost of analyzing each sample by 60% if the researcher has many samples to analyze. And our experience with customers strongly suggests that this will accelerate adoption and increase the total dollars spent on single-cell experiments. CellPlex with targeting will now allow our customers to scale up their projects to much larger studies. Now on the other end of the spectrum, with many new customers, new customers face a challenge in getting started because even the initial smallest experiments entails substantial costs. Next slide. And to address this challenge and to reduce the activation energy in getting started, we are now launching a new logs throughput kit that's priced substantially lower than our standard reagents. New customers can now try single-cell experiments at a much more affordable price entry point and scale up from there. We expect also that many of our existing customers will make use of this reagent because it will allow them to run pilots and optimize experimental conditions to make -- to take on new kinds of studies. This LT kit is going to be shipping this quarter. Next slide. Now turning to Sample Prep. For single cells, one must be very careful with the processing of samples, when preparing tissues, extracting cells and transporting them. Cells are inherently fragile, highly dynamic objects and mistakes in upfront preparation can really affect your downstream experiments. In fact, there are vast numbers of potential samples that could benefit from single-cell analysis, but are currently inaccessible because of sample prep challenges. To address this area, we have developed a special new chemistry to measure gene expression that works with specially fixed cells. We will be launching a new reagent based on this chemistry in the second half of this year. We expect that this product will greatly expand the number of samples available for single-cell analysis. And also address many of the challenges our customers face around sample prep and logistics of sample collection. Next slide. On the other side of single-cell workflows, there is a symmetrical challenge that our customers face around informatics. Single-cell experiments generate large amounts of data. And to make use of those experiments, one needs to become adept at processing the data storing it and then analyzing and visualizing it. And many sophisticated labs have the resources and the capabilities to address their own bioinformatics needs. But as we move out to more and more labs around the world, the biologists, the translational researchers, the informatics challenges become an increasing barrier to single-cell adoption. To address this bottleneck and to accelerate adoption, we have now launched the 10x Cloud. This software as a service solution allows our customers to store their data and run their analysis in the cloud at no extra cost to them. Users get seamless access to the most optimal computational infrastructure for single-cell analysis. And this solution scales very easily in accordance with the customer needs. We launched 10x Cloud in a limited release last year, and we will now open it up for everyone. We see this effort as a long-term investment with many new features and new capabilities coming in the future. Next slide. Last year, at this conference, I suggested that the single-cell revolution took off in 2016 because people for the first time could run thousands of experiments for routinely. The increased scale of experimentation has been transformational for the life sciences. But biology is incredibly complex, and many of our customers have been intensely interested in larger and larger experiments. And we agree, we strongly believe that greater scale of experimentation will accelerate new discoveries and will drive further market expansion. So with that in mind, last year, I outlined the goal of enabling our customers to run routine 1 million cell experiments. Next slide. And this year, they will be able to do exactly that with the launch of our new instrument, the Chromium X. The Chromium X is powered by our Next GEM technology. It is designed for very large experiments with up to 1 million cells per run. It will supercharge many existing applications across single-cell biology. It will also enable big new areas like large drug screens, massive immune profiling experiments and population-scale studies with single-cell resolution. This instrument will launch in the second half of this year. Next slide. So while the Chromium platform is well-established in many labs, it is still very early days in its adoption. We're going to keep investing aggressively in product development and commercialization to keep driving single-cell expansion and impact. Next slide. Now turning to the Visium platform. We launched the Visium -- the first Visium product for gene expression analysis just a little over a year ago. And it has quickly become a key catalyst for the spatial genomics revolution, as evidenced here by Nature Methods, which put Visium on its cover for its method of the year issue. The platform has received -- was received with great enthusiasm by our existing Chromium customers. And also by many customers who were new to the 10x ecosystem. Most importantly, we have seen strong demand from translational researchers who have been using Visium to characterize biology of disease, understand response to therapy, discover and validate new biomarkers. The single biggest request for translational customers, in fact, the necessary condition for most of their research is compatibility with formal and fixed paraffin-embedded samples, FFPE. This is the predominant way that patient samples are collected and stored. It's the standard part of pathology workflows. Next slide. But the challenge is that FFPE samples are notoriously difficult to analyze. And that's because the molecules in those samples are greatly abused and degraded through the process of fixation. So when you run them on Visium, your gene detection sensitivity is dramatically lower when compared to fresh frozen tissues. But our team at 10x loves big challenges. And so we have now developed a new Visium product designed specifically for FFPE tissues. Next slide. That new product, Visium for FFPE, is going to be shipping in the second quarter of this year. It is a complete solution, comprising all ready-to-use reagents and software. It is the first technology to enable true discovery in FFPE samples, delivering the full transcriptome across the entire tissue. It uses a completely new chemistry designed from scratch. It's not poly-A-based, which means it's much more robust to the effects of sample degradation, and we can measure even more classes of RNA molecules. Next slide. But what's truly remarkable is that the sensitivity of this product is on par with what we see with analyzing fresh tissues with standard Visium. This performance exceeded even our internal aggressive expectations and is very exciting to our customers. Another key request we have received from our Visium customers is to help us sample the handling and logistics. Most importantly, our customers would like to analyze archive samples that have already been mounted on conventional nonVisium slides. Next slide. To address these issues, we will be launching a new instrument next year called [indiscernible]. This instrument will take tissues mounted on a standard histology slide and transfer molecules from that tissue onto a Visium slide all while preserving the spatial location of those molecules. We expect that [indiscernible] will really simplify the workflow for many of our customers and will significantly expand the number of samples that could now be run on Visium. Importantly, it will be compatible with FFPE. So customers will be able to go back and analyze the vast numbers of archived FFPE slides. Now the Visium platform is incredibly powerful for elucidating spatial biology. It makes measurements of a very large scale, but it does not resolve individual cells. The cell is the fundamental unit of biology, and our customers have been keenly interested in reaching single-cell resolution in their spatial work. Next slide. And so next year, we're going to be launching a new version of Visium, Visium HD, which will deliver single-cell resolution. Visium HD is based on big fundamental advances in the underlying microarray technology. It will come with a resolution that's 400x higher than the current Visium and over 1,500x higher than the original pre-Visium technology. We believe that this together with all the other investments we're making, we'll establish Visium as the single best platform for scientific discovery and translational research. Next slide. And now if you're interested in more details about this or any of our upcoming products, we're going to be doing something special this year. Next month, we will host a special virtual event called The Experience. We'll describe in detail all of the products I talked about here. We will also show lots of exciting new data and many amazing discoveries that were made using 10x. Please join us there. And I'd like to finish by thanking our incredible team. You guys never cease to amaze me and never more so than this past year. Thank you.

All right. We'll jump into Q&A. Wow, lots to dig into her Serge. Maybe let's start off on the 3 new platforms. How do you think about how these could create synergies in a typical client use case?

Yes. I would say that, first of all, it's a little too early to talk about the In Situ platform. We -- having said that, we have seen examples of customers using them both in conjunction, Visium and In Situ approaches. There are papers that have already been published and certainly on the single-cell side as well. Usually, the sort of the typical case that we're seeing now that we anticipate kind of going forward across the 3 platforms where people make initial discoveries by doing the -- kind of a survey, census of their tissues to figure out what cells or cell types are present. And then running those on large numbers, potentially large numbers of samples, to understand kind of how those cells are arranged with respect to each other in tissues. And this is where the Visium platform comes in and becomes very useful. So kind of discovery followed by validation and exploration and both platforms supporting each other's findings.

And anything you can say on pricing, maybe starting with Chromium X, pricing? And who do you think the early adopters are? Is it POPSEQ? Is it immune profiling? You gave a couple of examples of use cases.

Yes. So the pricing is going to be on a order of around $100,000, and it's going to be kind of aimed at our -- some of our most forward-looking customers, certainly sort of people who tend to be on the forefront of single-cell research. There's always a tendency. There's kind of a class of research where if you give them a capability, they're happy, and then a few months later, they'll come back and ask for 10x as much. And so these are the people that are on the frontiers of science. So certainly, kind of doing larger single cell sort of census projects, [indiscernible] projects, but also those combinatorial screens for drug development or a large-scale CRISPR based kind of knockout campaigns, immune profiling as well. And I would say kind of a bit longer-term, starting to get into more cohort and sort of population larger-scale studies as well.

And then on Visium, you've kind of given quarterly updates on number of customers. We've had a lot of people asking about revenue contributions. Are you able to start to talk about how material that could be to the business? And how do we think about the HD platform expanding that market?

Yes. I mean, it's still, again, relatively early days on Visium. It's been growing very robustly, as I mentioned since last year. Chromium has also been growing very fast. So we're definitely quite happy with adoption, both the number of the -- the number of labs using Visium has been expanding rapidly and the repeat usage within our existing customer base has been doing that as well. We do expect that Visium HD will be a big enabler in the future -- I mean, it is kind of taking -- realizing the full potential of the platform. And I would say, especially for discovery research, but also it sort of -- it brings together all the different elements for translational research as well.

And then on Chromium pull-through -- had to cite $150,000. I assume that's for the fourth quarter, so in line with guidance. But how should we think about that trending this year, especially with the rollout of the X in the back half of the year?

Well, Justin, maybe you can touch on that.

Yes. So on the first slide, when we refer to $150,000 that's how we think about the business. That's how we think about the business today. The $150,000 is the number that we've given as far as a good number to use for modeling. As far as the fourth quarter, labs have continued to open back up. And we feel that we're back pretty close to where we were pre-COVID. There still are some shutdowns. There still are some labs with reduced capacity, but things have been trending in a good direction for us.

Any notable kind of budget flush dynamics in the fourth quarter? And a separate question we've gotten is, with the reduction in sequencing costs again to those incremental dollars increasingly come your way?

Yes. We did see a budget flush at the end of the fourth quarter. It was somewhat larger than we've seen in the past, and that was reasonable due to the shutdowns earlier in the year. Some of those dynamics we don't expect to carry forward into the early part of next year. But it is true as the sequencing costs come down, we do expect that, that makes more share of wallet available to spend on our products.

How about ReadCoor? And a couple of questions here. One, what are you able to tell us about upcoming milestones, things we can maybe track from the outside? Any timelines to around the commercial launch that you could maybe roughly give us at this point? And then how do we think about the IP? We've had a number of people ask with NanoString's SMI, is there any potential IP issues there? Or is it free and clear?

So I would say, like generally on the In Situ road map and In Situ -- kind of the -- our philosophy around the In Situ platform is that it's not so much as for the ReadCoor platform that we intend to launch. In fact -- I mean, we definitely -- we like -- we certainly love the company and the advances they have made. They've made lots of advances around hardware, instrumentation and put together great technologies and intellectual property. But the platform that we're working on launching is something that we have strong conviction around ourselves, and it's going to bring together elements and innovations from us internally from 10x and from CartaNA and from ReadCoor. And the actual platform is going to be driven by our own conviction about what the customers need. And that's how we think about it. So just to be clear, this is not -- our intention is not so much to launch a ReadCoor instrument, but to build a platform that we have conviction around, is going to really be great for our customers. And we're going to be investing extensively in building this platform. It's not -- there's a lot of elements to get right to get the product out that's sort of to the standards that our customers have now come to expect from us. And so it's going to take investment, it's going to take time. And when we're ready, we're going to talk about the road map and the commercialization, but the time is not yet.

Are you able to talk a little bit about how you think it will compare and contrast with the SMI from NanoStream? Or is it too early?

We're focused -- we have our own conviction about what the market means. And we've certainly invested in sort of all the elements of the technology so that we can build -- on this technology stack we can build. We feel pretty confident we can build a full set of solutions that the market needs. And that's where we're focused on.

On the FFPE capabilities, which you updated on today, how should we think about that opening up the clinical markets for Visium? And can you talk about some -- where you think the early-use case -- use cases maybe?

Yes. I would say it's less about the clinical markets at this stage, it's translational. That's where the platform is being used. That's where there's a lot of sort of this demand for which is kind of interesting because a lot -- again, a lot of people really want to use and are using Visium despite -- in translational settings despite the fact that it's really having Visium is -- having FFPE is almost the kind of a prerequisite before doing that. So we see this opening up, translational research and kind of most importantly probably cancer -- sort of cancer research and looking at archived samples, looking for biomarkers, developing prognostics and class of -- classifications of tumor, especially within -- sort of within the general group of immuno-oncology. So we do see this substantially opening up opportunities and just kind of unlocking customers that have been eager to get in another much deeper level than they've been able to so far.

One that came in on e-mail is around proteomics. And could you repurpose your GEMs to do something with protein similar to what Seer has done with nanoparticles and create a proteomics workflow similar to what you've done with single-cell RNA?

So the way we look at proteomics with our platforms is using -- for the most part, using oligo-conjugated antibodies. And with that, you can get to very high plex levels measuring proteins. So that's especially useful in translational side where people have sort of established panels of proteins and where new ones are getting established through a lot of the single-cell research that's happening out there to classify cells and classy kind of patterns of gene expression networks. So that's how we're approaching this -- the proteins market. There's also kind of on the -- again, on the spatial side, the ability to merge the immune fluorescence approaches together with Visium at the same time. So that gives you another way of measuring proteins, albeit at the low plex.

Another similar one that came in on proteins is, don't you need to measure the temporal profile of protein expression, perhaps that would flatten the differential profile and give you a measure closer to average for a distinct type of tissue?

Well, so certainly, having temporal measurements is useful, and that's something that as you think about the long run would be -- could potentially be the kind of capability that people start adopting. I don't think it is the kind of thing that is hugely in the minds of people [indiscernible] right now, not at this stage yet. But certainly, as you think about time course, maybe not like dynamic in tissue, but time course measurements of clinical samples, for sure. And this is where our products can absolutely be crucially enabling at this time right now.

Can you maybe just touch on Chromium Connect? How is the adoption with pharma? How big is the overall pharma business today?

So the overall pharma business is roughly -- has been tracking pretty similar. It's been going roughly similar rate as our academic market, roughly 20%, 25% of our business. The Connect has been doing quite well over the -- since launch. But again, this is a product that's meant to be for special specific use case. And relative -- and for that particular use case in pharma and some kind of specialized settings within academia and core labs, it has been doing quite well.

As we think about kind of the longer-term opportunity, I mean, the current Chromium installed base as you talked about 2,400 placements today is still a fraction of the next-gen market. I mean, how do you think about where the market could go longer-term? I mean, is -- I mean, today, there's 20,000 or so next-gen instruments, is that a good proxy? Or do you think there could be more?

Yes. I mean, one of the key -- crucial things to understand of our business is that there's really no connection with the sequencing that happens. Our customers, for the most part, the vast, vast majority don't actually have a sequencer. And so in terms of the potential -- so they're very quite different markets. We do see that kind of as we look to the near to medium term, the potential placements are in order of 10,000 to 20,000. Kind of quite clearly there is a sort of straight chart towards that. But beyond that, our goal is to get to 50,000 to 100,000 because those are the numbers of sort of molecular or just general biology labs out there. And all of them we see as potential customers, potential users of the system, for sure.

How are you guys thinking about M&A now that you've done ReadCoor? Should we expect further acquisitions this year?

Well, so -- I mean, the way we think about acquisitions is that they're driven really by like overall product development, the product road map priorities. We think about, again, kind of what our customers need and work backwards to invest in platforms and technologies internally and also realize that we don't have monopoly in innovation. There's lots of smart people out there. And so we actually -- we're always on a lookout to see what like -- what innovations have been happening outside of our walls. And if something is out there that makes sense in the context of our long-term imperatives, we acquire those companies and those assets. And that's the philosophy that kind of led us to ReadCoor to CartaNA last year and our previous acquisitions as well. So we're always on the lookout. But that's -- it's really premised on that, our long-term strategy rather than buying things for the sake of buying them.

Sure. Maybe last one, just on the commercial channel. As we think about Chromium X, [indiscernible] and Visium, all these kind of new products you talked about today, how should we think about the scale-up of the commercial channel? And do you need to add additional resources?

We continue to scale. I mean our business scale is extremely well. So we're running up right around about 300 people, and we'll probably hire at least 100 people throughout the course of this year. So we'll continue to expand roughly at that 30% to 35%.

Great. Well, we hit the end of the time slot. So I appreciate you doing the presentation, and enjoy the rest of the conference. Talk to you soon.

Thank you.

Thanks.