10x Genomics, Inc. (TXG) Earnings Call Transcript
August 11, 2022
Earnings Call Speaker Segments
Hi. For our next panel, we're happy to be hosting 10x with us. We have Serge Saxonov and Justin McAnear. Welcome. And if anyone in the audience would like to take questions, we have iPads up on stage, and there's instructions on your table on how to ask them. So maybe just to start off the things off here.
So the last couple of quarters have been a bit challenging. There was the Omicron wave in Q1. Q2 had some macro headwinds. You also mentioned on your call earlier this week that you experienced slower-than-expected rebound as we emerge from the pandemic environment. So just, I guess, given all this happening in the market and the broader macro picture, could you just start off on what gives you confidence in the single cell market and the opportunity there?
Yes. So kind of big picture question. The way that I think about things, first of all, is kind of stepping back and thinking in terms of first principles. So the cell is the fundamental unit of biology, right? And we kind of -- we always know there's a reason that we all have for [indiscernible] cells and they're all different and they do different kinds of things. So we've always known that like cells are important. The reason that things have not been measured to the single cell context until recently is just limitations of technology. You would never in your right mind think of -- if you have the capability to think of like take your tissue and then kind of munch it all together and measure the average. It's only the limitation technology that had us limited to that for up until several years ago. And so that's kind of one fundamental premise in our mind, all of ultimate level of research whenever you're measuring biological samples, really should be doing -- you should be doing the single cell complex from first principles. Now over the last several years, because of the availability of technology, we now have a huge base of empirical evidence to support that notion as well. Back when we first entered the market in 2016, there about people were like, well, yes, I'm not sure about single cell analysis probably useful for oncology because we knew that to mural heterogeneous probably useful for immunology because we knew that there is a certain cell originating when you look at the immune system. But what we have learned since that every single biological system, you look at every single tissue is hugely heterogeneous. And in fact, the fundamental biology is an understanding what's happening at the levels of individual cells and how they interact with each other and the gene expression networks within those cells and between those cells. That is where the biology is. That's why -- so if you want to understand any given biological system, if you want to understand the health and disease and what makes disease different from healthy, you need to look at the level of individual cells. And I have not heard a single rational argument to the contrary from anyone. To the extent that people resist this notion, it is based, I would say, purely on inertia. And if you talk to people, if you really press on them, I think everyone agrees with the fundamental thesis that the world has to go in this direction. Now like what is the -- given that premise, like why isn't the world there already? And the fact is you do have to relieve multiple bottlenecks along the way to make single cell ubiquitous. First of all, there's sort of -- the initial step is to have like a core workflow measuring cells at high throughput that -- be able to do that easy, cost-effective and so on. And we did that with our Chromium instrument with our initial technology. But from the beginning, we've always said there's like -- there's a core workflow, there's also sample prep issues getting from -- just starting with the tissue and getting it to the point where you can run it, put it into Chromium, into our system is a challenging proposition. And something that sophisticated labs can do, but it becomes more challenging as you go kind of broader and broader. And especially if you go to a broader set of samples and tissues. There's also the bottleneck on the other side in terms of data analysis. And again, more sophisticated labs can address that, but it gets more and more challenging as you go to the broader universe of biologists and researchers. And then there is also the pricing issue. The single cell experiments right now are over $1,000 per sample. But if you want to imagine these things becoming ubiquitous in research -- the world of research needs to get down to something over of a few hundreds of dollars. And so all of those -- so those kinds of throttlers exist there. They've been addressed somewhat over the years, but not anywhere to the extent that they need to and they will be to make single cell ubiquitous. And so kind of that's my mental model is that we know the end point. We know that where things are going to end up. But as you go towards that endpoint, you're going to hit inflection points in and asset build along the way that you resolve by addressing these different throttlers. And then stepping back from sort of first principles. We also have a lot of evidence from just talking to our customers, right? When you talk to people who are doing this kind of research, they're all looking to scale up. They have all kinds of new applications they are thinking about new larger projects. On the call, I pointed to some of the very first cohort studies that have been coming out of single cell just recent papers. And that's -- we know that's just the tip of the spear. There's a lot more that's behind that. And so empirically just talking to researchers and about where they think the world is going and what they're planning to do, there's a lot of pent-up momentum there as well. So that gives us a lot of confidence from that side of the world as well.
Great for that. Thanks for that overview. So when you think about new or potential customers that either don't conduct single-cell research, they are used maybe very limited amount of single cell research, what do you think are the key factors that are holding them back? And then how do your recent launches, including the fixed RNA and nuclei isolation kits address those barriers?
Right. So there is a -- so for a lot of new customers, I think there is a sort of impression somewhat kind of, again, inertial impression that single cell is something complex and sophisticated and difficult. And in some instances, it is, and especially when it comes to the sample prep as being the kind of the first challenge always in these things, again, going from your initial tissue that you get, or do you cell spatial to something that you can easily run on the Chromium, it's -- there's a challenge there. The other thing that I would point to that is often underappreciated. Every -- all the single cell experiments that have been done up to very, very recently, have been done on fresh life tissue, like you actually -- you get your [indiscernible], you get your tissue slice and you have to prepare it right at that point to go into the instrument because you need to work a deal with live cells. And so that imposes this massive constraint in terms of logistics, in terms of your processing for doing single cell experiments. And it's a big challenge, especially for someone who is just getting into the ecosystem to line up all the different stakeholders in order to run these experiments. And so that puts a fairly significant barrier. And then it becomes a particular big barrier for people who are coming from a translational side if they've got sort of biobank samples or like if they -- again, dealing with patient samples that are available -- that you need to analyze just in time. And our products -- so we released 2 products recently on a sample, perhaps the first really kind of products of that kind. One fixed R&D profiling, which is more than a sample per product, but it does address a lot of sample prep issues, allows people to fix their samples at the point of collection and now you can time shift to a play shift where you actually process them for single cell analysis. And we see that as a huge enabler. And when we talk to people that does really like one of the huge, huge, huge constraints in terms of running single cell and especially for translational researchers who have been less of the kind of use case -- who's been using single cell less for those kinds of reasons up until now. And the -- and also last month, we talked about it very recently. We actually told the world that this kit allows you to run single cell on FFPE samples, which is coupling new capability and allows you to now go back to biobank archived samples and run single cell for the first time ever, on samples that have been collected previously and not just the go forward basis, again, opening up applications for new kinds of researchers. And on the translational side, we also released, like you said, a nuclear isolation kit, which is another product, specifically aim and simplifying sample prep. There's been a lot of interest for using nuclear for single-cell analysis, close to something like if you look at papers, there's something like 20%, 25% of all single-cell analysis is actually done on nuclei for reasons -- for multiple reasons, part of it is that you can -- that allows you to freeze your tissue and then work in frozen tissues and also allows you to work on a lot of samples for which cells disassociation becomes too challenging. And so people have gravitated towards nuclei in a lot of businesses, but it's an incredibly difficult process to actually clean up nuclei. And for the most part, it's only the most sophisticated loss we've been able to do this. And those now kind of democratizes that for everyone. So those are -- I think these are like pretty significant advances on the product side to enable it for new customers. And I guess one other thing that I would just mention because I alluded to pricing as being an issue as well for single cell analysis. And the way that we have gone about addressing that is promoting the use of multiplexing, where you put multiple samples together into a single lane and this way you can almost proportionally decrease your per sample cost. And thus, for the customer, you get lower price per sample for us, but the deal is that they run more samples, right? And that's -- I think that's a trade that's good for both parties. Traditionally, multiplexing operations have been more challenging because it's another step that you to sample prep, which is the kind of one of the most [indiscernible] parts of the workload. With fixed RNA profiling, we actually have multiplexing built in right into the product itself right to the probes. And so it's no harder to run multiplexing than running single-plex. And very, very early days, but it is another lever that allows new people to enter the ecosystem and run more experiments to the lower price point.
And any early feedback from customers on these products?
Yes, for sure. So the nuclei kit has been received really well. Initially, like I said, there's a lot of people -- the sort of the initial sophisticated people who have been running nuclei and have been kind of suffering the pain of it, and it's very -- they've been very eager to jump onto this kit. I think our sales force has been quite busy promoting it because it allows the running of some of our most kind of high flagship reagents. So good feedback. And on a fixed RNA kit really good feedback. This is something that a lot of people have been waiting for because they realize that the sort of the constraint of working with life tissues, just prevents a lot of kinds of experience from being run. There's been initial runs where people have been doing head-to-head comparisons of this kit versus our other kits. And really, really spectacular results. We kind of expected that. We developed a kit that has really, really nice properties in terms of sensitivity in terms of kind of sequencing efficiencies or other characteristics. But the kind of -- I guess the third thing I would say is that the FFPE compatibility has been receivable a huge [indiscernible]. Lots , lots of people who say this is a complete game changer because it sort of changes your mindset in terms of how you even think about single cell that people weren't even kind of contemplating that this was going to be possible.
Great. And a question for Justin. Earlier this week, you gave some color on your earnings call on updated guidances. Just any early view on 2023? Are you expecting to get back to that higher growth? And would it be reasonable to think about what the typical seasonality looks like there?
Yes. So there's a lot to be excited about 2023 with the new product launches that we have going on. So that's going to be the first full year of Xenium, the first 4 year of cytosis and fixed RNA as well. And I also think in 2023, we're going to start to see some of the improvements in taking commercial execution to the next level as well. As far as seasonality goes, it's important to remember, too, that Q4 is typically the biggest quarter of the year, and there is a seasonal drop off from Q4 into Q1. And based upon more recent results, I would say, 10% to 15% coming out of Q4 into Q1. But as far as specific numbers for the full year, I don't want to get too far ahead of ourselves. I want to get through Q3 and Q4 first. But I think that we're on solid footing heading into 2023.
And Justin, another thing you mentioned on the call was that you expect to be cash flow positive by the end of next year. Can you just tell us a little bit more of the plans there? And how should we expect the traction in the cadence?
Yes. So being free cash flow positive by the end of 2023 is our plan. We believe that, that's achievable under multiple different revenue scenarios. Up until now, we've been investing heavily to drive future growth. And while we're still investing now to drive future growth, given the uncertain macro environment that we're in, we do think it's important that we prioritize cash flow and creating a healthy financial profile heading into the future on the path to ultimate profitability. As far as cash burn goes in the near term, we do expect to spend about $140 million to $150 million of CapEx over the next 12 months. That is going to be front loaded in the next couple of quarters. And most of that relates to the new operations facility that we're building in Pleasanton. That's going to be complete in Q1. We're evaluating financing options for that after it's completed. So like a mortgage or something like that. And we expect CapEx to drop off after that. And then with our increased focus on controlling headcount growth and controlling non-headcount spend as well, we do believe that free cash flow positive by the end of next year is possible.
And maybe moving on to Visium. Serge, you announced the launch and preorder availability of 2 new products with the Visium portfolio, the CytAssist and then the Visium for FFPE v2 earlier this year. Any initial customer feedback there?
Yes. There's a lot of excitement. I think there's -- the Visium FFPE v2 was something we kind of sprung in the world. We got -- talked about it before last quarter. Definitely lots of interest. And we talked about the fact that FFPE has been growing, Visium FFPE has been growing quite rapidly. And so we do expect that to -- that trajectory to continue and feeling really good about it. And I think the -- the customers have shown a lot of interest in that product and the next version. In CytAssist, now, this is a new instrument for Visium and it really addresses the key issues in the workloads that we've seen in adoption. And just routine use of Visium, that has been the big obstacle in that you have to -- the vision slides are pretty expensive [indiscernible]. Your typical histopathology techs are just not used to dealing with those kinds of slides and created a fair amount of friction in the use of the product. CytAssist addresses all of that. And so lots of interest from customers, lots of enthusiasts from our field teams now. Still early days, but I think the signs are quite exciting and positive. And I think this is going to be a huge enabler for the overall Visium platform and accelerator for it going forward.
Great. And then I guess, what have you seen on both Fresh Frozen and FFPE? I know it's early in the life cycle, but any projections on revenue growth or what that profile might look like?
Yes. So just at a high level, now that we've had an experience about a year of -- with the FFPE product, it certainly I think as we look at the trajectory, I think that has the potential to grow faster than the Fresh Frozen for some of the reasons that I kind of alluded to or talked about in a single cell side, just being able to work with archived tissues with the fixed tissues is much more convenient from a -- just a pure logistical perspective. It's also -- this is where the biobank samples are and especially combined CytAssist, I think we expect there to be a lot of growth on that side.
And I guess just with the FFPE capabilities driving more of this for CytAssist, you seem to be expanding into more, I would say, translational markets there. Can you explain to just maybe how you stack up or where you see the competitive landscape versus GeoMx? And are you expanding into these markets?
Yes. So with Visium FFPE specifically, we've talked about this, it does kind of represent an entry into much more of a translational space for us, and coming over from like the sort of our traditional core strength and research discovery markets. And so that definitely has been kind of proving out a lot of customers who are coming into using Visium FFPE are oftentimes new to 10x, and they're coming from the world of tissues. And we certainly see that continue. In terms of like what really differentiates the platform, it's like at scale. I mean that's one of the kind of central premises of what we build at 10x is able to measure lots of things at high scale. And we Visium, you've got -- each array has 5,000 separate measurements that you're making. And it's that resolution and scale that is really -- doesn't really exist anywhere else in the commercial product where you have unbiased discovery across your entire tissue. And so the premise that we're driving with the Visium platform is that it's the ideal platform for translational discovery. That's what sets us apart from everything else that's out there.
And maybe moving on to Xenium. Can you just run through the announcement you made at AGBT and what's been the feedback in the 2 months since the conference?
Yes. So we've shared some of the specs, and we've been of the Xenium platform. We've been talking to customers since that point as well. Lots and lots of interest. I mean the whole in situ space has been incredibly intense, noisy, buzzy, all kinds of interest from customers. And we talked about this earlier in the year. Just the amount of interest in this platform and in the space in general has just been kind of off the charts over the course of the past year plus. And the -- we've been engaged with a lot of conversations with customers on the Xenium platform. And lots of resonance specifically about how we're approaching it. Certainly, lots of resonance, we're just being kind of given that it's coming from the 10x ecosystem. We talk about the performance of the platform of the customers around sensitivity, specificity, plex levels. And the thing that we really have pursued and really from the beginning of kind of standing up the platform as to build something that's ideal for routine use. That has always been sort of the cash release with these approaches from the very beginning, going back to the initial investment is that you can run -- you can generate really beautiful data, but it typically takes you a really long time to get there and great for our power point, great for maybe a publication, but not really suitable for commercial routine use. And that's what we've really emphasized and that's where we're focused on delivering. And part of that is delivering on throughput, and we intend to have the highest throughput of any platform out there at launch, and we'll keep leaning into that. Part of this turnaround time, part of it is end-to-end ease-of-use. So we invest in software a lot. That's one of our -- traditionally, has been one of our strengths and certainly is something where we're getting a lot of attention on the Xenium side as well. The other part of it, too, is that we recognize, given that these are targeted -- inherently targeted applications, you have to be very thoughtful about how you deliver, what kind of content you deliver and how you deliver that content to customers. And that's -- in all our conversations, that resonates really well. because our approach is to have gene panels that are specific to particular tissues and particular application areas and then it also allow a significant amount of customization on top of that for customers. And we're working with the KOLs on any given tissue in any given biological system to build up these panels while in the meantime also offering customization for as well. So the whole sort of set of features and the whole ecosystem of 10x where you've got all the 3 platforms, Chromium, Visium and Xenium resonates really well. And we're on a really strong trajectory towards the end of the year towards launch now.
And I guess just maybe expanding on that, can you talk a little bit on what you thought M&A was the right strategy to get in within in situ?
Yes. So we started working this -- certainly looking at in situ space a long time ago and then started doing some internal development on it as well in advance of the acquisitions. We made the acquisition, so there's sort of several reasons. One is you get the technological know-how for people who've been working on this and there's a lot of intuition that people build up over the years working on tissues and on these systems and. And just for those who might not remember, we acquired CartaNA, It's a Swedish company that's been sort of working on approaches for a long time and then ReadCoor company, sort of a spinoff from George Church's lab, again, working on the stuff from very early days and got somewhat complementary technological know-hows. ReadCoor had more emphasis on the hardware, CartaNA more emphases in the chemistry. And so it's just that -- so the technology and the experience from people was quite valuable. Another important sort of value proposition, especially with CartaNA. It actually had been in the market for a while. They had customers, they were running a service. And so there's a lot of knowledge that we and customer relationships that we got as a result of that. And then I say the final thing was intellectual property. We did a thorough survey of the landscape before entering and that was a really important enabling intellectual property that we got those acquisitions.
I guess maybe just talk about the broader M&A strategy. Any areas you think that might be complementary or you'd be interested to move in for inorganic opportunities?
So we're always out there kind of looking and we're always looking at it through the lens of our internal strategy. And we don't look for -- talk a lot of companies for the sake of increasing revenue. It's much more. We like to think that we kind of -- we have a sense of where the world is going. Now when we work backwards from there, what technologies are necessary to get there. And we certainly are -- we spend the resources to developing technologies internally, but we also recognize that we don't have a monopoly on smart people and inventions out there and so always kind of scanning what the world out there is coming up with. And so it's an ongoing kind of effort. We don't have any sort of bright lines that we're going to do this kind of M&A but not that kind of M&A. It's based, again, from first principles based on our what fits our strategy. One thing that I would also emphasize, and I think where we have a particular strength is that because our product development engine kind of spans from 0 to a complete product, we can take really, really kind of immature assets or really early inventions or technologies and put them through our product development process and make them really awesome. And I think that gives us an advantage over relatively maybe other more mature companies that have to wait until something is more paved before they can pull the trigger.
And then on the recent call, you talked about some of the reorganization there within the commercial business. I think you now have a Chief Commercial Officer that just started as well. Maybe could you just take a step back and when we think about the productivity of a typical 10x salesperson, how long does it take for these new reps to become productive?
Yes. So the typical sort of rule of thumb we use was about 6 to 9 months historically. Although I think there's a lot of nuance into that, especially because our product lineup has gotten so much more complex over the last several years and that set of applications, set of customers has gotten so much more diverse and so much more complex. I think it's become more and more of a challenge and we're seeing that with the new reps joining to kind of -- to really get up to speed. If you think back to like the early days of the company when we were -- we had 1 product and 1 application, and you -- it was pretty natural, you hire kind of better end Genomics sales reps. And after a fairly quick sort of baking period, that would be ready to go and they can go back to their initial Rolodex, whoever they used to sell for Illumina, whoever they used to solve for our metrics and that works pretty well. But now like fast forward to now, our customer base is well beyond like your sort of standard Genomics people and the product set is well beyond anything that's just genomics oriented. Again, we're talking about translational customers. There's pathology, there's tissue. There's all kinds of cell kind of flow type customers. So it takes -- it would be reasonable to expect that the whole process would take longer. And in the absence of putting a lot of conservative effort into training people and having the processes to get them up to speed very quickly, and that's one of the priorities for us now going forward with the new commercial leadership to really lean into that.
And so we've talked about the 3 platforms, the Chromium, Visium and Xenium. I guess, ultimately, how do you think these fit together? And would there be any cannibalization among the platforms?
Yes. That's always kind of this ongoing question from the -- almost from the beginning, kind of at what point the space will become sort of overtake sound application single cell has been using in what context and so on. So first, I would preface it by saying there's a certain level of uncertainty that no one in the universe yet knows precisely how it will work out because somewhat comes down to questions of science and just biology, we just don't yet know. But for us, part of our strategy is that we specifically invest in these 3 platforms, so it doesn't really matter which way the science goes and which it way kind of -- how the world works out because either way we're going to benefit because we're going to have the platforms to support the future regardless of how it plays out. We do think that there is a very natural sweet spots for the 3 platforms. You -- certainly, Chromium associate single cell is here and now and has tons of momentum and lots of lots of -- just lots of widespread use. And I think that's going to carry it forward kind of almost regardless what happens on the spatial side. There's also applications even if you think to sort of the infinite future, there's still going to be applications that will always be best used for the associate single cell analysis. So if you're starting with blood, for example, those that comes -- that's essentially a cell suspension. You're in spatial context for that, there's lots of experiments having to do with combinatorial drug screens or perturbation screens where the unit of experiment is the single cell. And again, you kind of doing that disassociated -- with the dissociated approach like Chromium is the best way to go. There's also kind of a bit more of a subtle point around a lot of the analysis that we see that is done in single cell, really comes down to essentially taking a census of cells in your tissue. And for that, you don't actually need to measure the full block of tissue that you have. You don't need to measure 10 million cells that you have in there, it's enough to sample 10,000, 100,000 cells. And in fact, it ends up kind of doing the full kind of spatial readout might be overkill for that purpose. And so we can see that a lot of the associated single-cell analysis is going to stay there in perpetuity for that reason. So that's sort of on the Chromium side. Again, we don't -- like in the near term, we don't see any cannibalization realistically. In fact, there are going to be sort of spatial single-cell approaches or mutually reinforcing. I'm just sort of talking more about asset to it. Like I said, Visium is -- we see that platform as being ideal for translational discovery, spatial discovery, you have tissue. You have a biobank -- like a biobank of tissues with some clinical data, you'd like to find biomarkers correlate the clinical data with underlying molecular signatures. The best way to go about it would be through a Visium platform. I think maybe with an additional nuance that these days because of what we announced earlier, earlier last quarter was you can now also run that through a chromium using FSP to fix on a profiling kit. And so I think the -- like you might want to run that in conjunction, but that's sort of the best for translational discovery, we see Visium as fitting kind of as the best use case. But once you know what you're looking for, you have the gene panels, you have a particular system cells than sort of the fully integrated approach where you have the minimum amount of manipulation of your molecules and that would be the in situ Xenium approach would be the right way to go.
And maybe just for Justin, can you just provide us maybe a little color on some of the regional performance you had during the quarter and maybe just thoughts on outlook for the rest of the year. I know this may be with China lockdown specifically, how do you see that normalizing? And just remind us what the impact was in the quarter?
Yes, sure. So for our Q2 results, I would say the biggest impact on Q2 was the China lockdowns. We expected those to abate by mid-May. They went through the end of May into June. And even when they started opening back up, there was still a level of disruption with not so much widespread lockdowns, but lockdowns by block or building. And so very disruptive for companies in our business that sell through service providers that are working with research customers, processing samples. And so we're not seeing widespread lockdowns now. We don't expect there to be widespread lockdowns in the near future. And so when we look at our updated 2022 guidance, that assumption is built into it. But it's not back to 100%. There's still a certain level of disruption there. But we have seen, so far, in trends this quarter, we -- things are definitely improving.
And then maybe if you look out across, I'd say, the broader genomics landscape in Q2 in Europe, there was maybe some softness there for some of the companies that have reported. Just can you maybe run through what you've seen in Europe? Have you seen notice any changes in demand? Or has there been FX headwinds that have caused any impact there?
Yes. So FX headwinds were an impact for us, mostly in Europe. The euro and the pound have both weakened against the dollar over the course of Q2. We did see some impact in APAC as well with the one in the yen, not to the degree of the euro and the pound, but still some impact there. So I think that was a decent headwind for us in Q2. That level has persisted now as far as the exchange rate. And so what we're assuming going forward is that it stays basically in the neighborhood that it's in. We also had some internal execution issues as well in Q2, in particular, our cold chain logistics issue with delayed customer reorders as a result of that.
And then maybe for Serge. Just any commentary around if you look at where biotech funding has been year-to-date in public and private markets, both pretty soft there. Just any commentary on what you're seeing with your customers?
Yes. So general funding. On the academic side, I think it has been reasonably stable. So far, obviously something to watch. But on the biopharma side, we had over the last year or so, quite a bit of interest from biotechs who've come into the single-cell ecosystem. Lots of new companies kind of adopting single-cell products. I think very recently, we've seen kind of looking at the last quarter thereabouts, the amount of spending by those companies has decreased, as you sort of would imagine. So still the number and the interest is growing, but how much they spend is, I would say, each one's spending is decreasing. On the pharma side, it's more of the opposite where I think their budgets are large and at least what we're seeing is that they're -- anything they're increasing.
And I guess maybe just even stepping further in that, any way to quantify how much exposure you have there? And how much visibility do you have into your clients' funding level?
Well, right, like things have turned pretty dramatically over the course of this past year on the biotech side. We don't have much exposure. We've talked about the fact that biopharma combined is on the order of fluctuates quarter-to-quarter about 15% to 20%, maybe 25% of our total revenue and biotech pharma split somewhat close to equal, maybe pharma is a bit more, probably a bit more. So that's our level of sort of exposure. I think -- on the pharma side, especially, I think there's a lot of potential with the new products. This is one of the sort of standing request. We've always had some ability to fix samples, again, because so much of what pharma does is especially, when comes to clinical trials is distributed sample collection, and it was just not feasible to install premium. So the -- all these different sites and train people to run them over there. So we think the new product capabilities are going to be particularly useful for driving more pharma adoption.
And I guess maybe you touched on it brief briefly, but is any additional commentary on what you're seeing on academic outlook and funding there and maybe just even U.S. versus Europe?
At this stage, I'm not sure if we're seeing a material difference. I mean there's some sort of fluctuations around expectations and increased inflation where that money -- who is kind of getting squeezed more in that. So that's something we're watching. I don't think there's anything materially different than what we're seeing relative to the last couple of quarters maybe.
And so I guess maybe then wrapping this up from opportunity side. Where do you see the larger opportunity? Is it academic customers? Is it biopharma customers?
Yes. I think ultimately, as we've said before, kind of at least aspiration-wise, is that we feel like the business should go to like 50-50, roughly academia and biopharma not at the expense of academic business dropping. I think there's a huge, huge potential in biopharma. It could be massive. I think we see a lot of interest. We see a lot of nascent interest and we've only scratched the surface of what's possible. The amount of use we get right now is mostly limited to the early stage kind of discovery side, the side that's most analogous to academia but there is this huge bolus of pent-up demand on the downstream side for -- to go into clinical trials and to start, again, kind of working more on the translational side. So we expect that to increase a lot going forward.
Great. So we're almost here at the top of the hour. But maybe just to kind of wrap things together, what do you think is the most misunderstood thing about 10x? Or what's the message that you want to leave with investors today?
Yes. You know what, I'll go back to the very beginning of the conversation kind of what I mentioned is because there's a lot of -- there's so much variation quarter-to-quarter, so much noise that happens. And when you look at all the different macro environments and all the different sort of market dynamics, but what gives me full confidence in assurance is again thinking things from first principles. We know where the endpoint is, we think about single cell technologies, and I'm including broadly spatial in that context as well. We know the single-cell context is absolutely crucial for understanding of biology. For driving research, for driving on single biology, which means ultimately for clinical applications as well. We know that's the future. That's where the world is going. And yes, there's going to be fits and starts along the way. There's going to be different inflection points. There's going to be different ups and downs, but we know where the endpoint is, and we've got all the assets internally to drive the world to that endpoint.
Great. Well, with that, we're out of time. Serge, and Justin, thank you very much for joining us today.
Thank you, all.
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