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

Good afternoon or really late good morning. Dan Brennan from UBS life science tools, diagnostics and pharma services analyst. Great to be joined here on stage at day 2 of the Genomics conference with Serge Saxonov as Co-Founder, CEO of 10x Genomics who, for everyone who's dialing in, knows well. Company reported last night, so it's timely. I know in the years past, when we've tried to have Serge come, it's kind of been a week earlier, so it's been quite difficult the week before the quarter. So I'm glad that we're able to have you be here in such a timely fashion. So certainly -- well, first off, welcome, and thank you for being here.

Thanks, Dan. Glad to be here.

Terrific. Terrific. And feel free, anyone who has questions on the webcast, try to shoot them to me. Happy to try to get to those during the presentation with Serge.

So I guess you reported last night, just kind of kicking off from a high level there. I know quarter came in better than expected despite broad lab closures. Just maybe a softball but high-level question. Like how would you characterize the results versus your own expectations and kind of what deviated the most?

Oh, yes. So this was an interesting quarter. So when you ask about expectations, you have to kind of specify which part of the quarter, which would -- right. I mean when you look back in April, things were looking like crickets, right? There was almost -- everyone just kind of went home, things were shut down. So relative to that state, relative to April, kind of the first couple of weeks of May, like, way -- I would say definitely way above those expectations because things were just really, really slow. It did start kind of picking up starting about mid-May or so. But we're really -- but still, kind of fairly slow to start with. There was definitely much more activity towards the end of June. And so definitely satisfied. Like that was happy to see. So relative to that, we definitely came in higher than what I was expecting throughout most of the quarter.

So it was really more so the way you planned the quarter in terms of the activity or the ability for researchers to be at their desks and kind of doing -- or at their bench. They returned quicker, and hence, you saw a bigger capture and kind of bigger revenue impact from that?

Yes. Again, I would be careful relative to the timing, right? Well, they started returning. Again, we do -- we had no -- like when you go back to April, it wasn't clear when people were going to return. So you were sort of like -- even talking about expectations, it was a little difficult. But yes, I would say as sort of the trend picked up, especially towards the end of June, and that's where sort of the difference came from what we were expecting came in.

Okay. I know COVID was a drag this quarter, certainly. Although you did see, as you mentioned, significant demand for your immune profiling product. Could this product be material contributor to revenues going forward?

Well, I mean, it has been already. For sure, we expect it to be going forward as well. I mean it has lots of applications across many different areas. Again, immune system is sort of the fundamental element of human biology, body's therapeutic and diagnostic system. We were really excited about it for a number of years since launching in 2017. Most of the applications we had seen before COVID have been in cancer, immuno-oncology and autoimmune sort of diseases. But now all of a sudden, we have a big infectious disease sort of interest in market. And that really has exploded. So I think that definitely will now be a long-term sort of fixture of our business.

Right. Sorry. That's the way I should have phrased it, which was really more the contribution from infectious disease, COVID, how much could that be a driver.

Yes.

You -- I know on the call, and obviously, you just kind of alluded to it in the opening question, 25% of the labs were open at the start the quarter, but 60% were open or thereabouts to end the quarter. Just in terms of U.S., Europe, China, like how have -- how has that progression evolved? I mean, I think on the call, if I remember correctly, or maybe not, I know China and the Europe has certainly been ahead of the U.S. But how would you characterize this kind of state of labs opening and activity across the different regions?

Yes. It's been a bit all over the place and another sort of example where things are pretty hard to predict. In a sense, we're expecting Europe to be slower than it actually ended up being in the second quarter. So that was good to see. America was pretty heterogeneous. You kind of saw some middle of the country opening up earlier, but the costs have been pretty slow as you might maybe expect kind of retrospectively now. China has been pretty strong, but the rest of Asia Pacific is more like the rest of the world. So also pretty heterogeneous and fairly slow for the most part.

Interesting. Because we've heard from some other tools companies, not nearly the dynamic, early-stage, product-driven growth that you have, but that there were some funding issues in China, intra-quarter things changed. Was there anything from a top-down basis in China that you guys saw from a government funding basis?

I wouldn't say -- not on that front, no. I mean, there were some issues earlier in the quarter around sort of sample shipments and kind of limitations around that. And a lot of our business goes through service providers over there. And samples were no longer being shipped as much to service providers as before. So we had to place some instruments locally in hospitals and such. So there are some logistical constraints certainly been there. But at least we didn't perceive a funding sort of crunch or limitation.

Got it. And then I know last night, you made a positive comment, or you were discussing maybe the outlook for funding to the extent it improves. We had Eric Green on earlier today from NHGRI, and he didn't really break any new ground, but he just expressed really strong support from Congress. So with almost 75% or thereabouts of your revenues from academic customers, like how do we think about the leverage? I mean, if we get a $5 billion bump next year, I mean, how material is that, you think, to 10x in terms of kind of the impact?

Yes. I think the way -- I kind of mentioned that, maybe not on this earnings call, but before. Like every time you have -- like one of our biggest sort of competitors is really inertia, right, the old way of doing things. And every time you have a new kind of a discontinuity, that, in some sense, helps us because it resets people's kind of thinking and sets them up for new projects. And because we have sort of the forward-looking technology set and kind of what we believe is the future of the life science technologies the tools that benefits us, right? So I do think like we're kind of at the sharp end of the stick. And so I think when there is new budgets that are getting allocated, I think that large fractions of those are going to go to genomics, are going to go to single cell analysis and spatial analysis because that's what kind of future-leaning people are looking at, and this is what the new projects are getting oriented around. So I feel fairly confident as far as like, yes, when budgets increase, when new money comes in, more like we should benefit disproportionately from that.

Interesting. And I'm sure it's hard to disaggregate because you've got so much momentum and new product-driven growth. Sometimes as funding isn't perfect, I'm sure you're going to grow right through that, maybe not as quickly as you want. But some of the feedback in the U.S. we've heard is like a lot of academic medical centers are facing a lot of pressure just given what COVID did to their hospitals and things like that. So foundation, university funding, I don't know. Is that at all -- I mean, do you see that at all as a potential headwind? And even though if the government funding's going to get better, you have these other pressures from other sources of funding in -- across labs? Or not really something you focus on?

Potentially. I mean, I think there's some like other geographies outside the U.S. might feel the pressure more so. So I think I kind of see it as there's sort of 2 trends. One is that there's generally going to be more interest and more investment flowing into biomedical research. I think there's very little question on that. I mean just kind of everyone across the board is realizing just how important that is. So I think that's definitely a trend, and that's kind of what I referred to the NIH increase, and that's what we're hearing is going to be happening. But sort of the other countervailing trend somewhat is the uncertainty of the economy, especially in some geographies, whether it's just general sort of macroeconomic pressure, that's potentially going to decrease the overall budgets. I think on balance, I'm pretty optimistic because even in the context of reduced budgets, we tend to get the -- again, the disproportionate share of what remains because then people think more carefully about what experiments actually yield the most value to them.

Right. Okay. And in terms of geographies, is it Europe? Or is it specific countries?

Europe is what I'm kind of -- again, Europe is kind of heterogeneous. But yes, EU and sort of the U.K. having sort of their own issues to deal with.

Right. Okay. So maybe kind of taking a big picture zooming out from the quarter and just kind of funding issues. And obviously, I don't cover the stock right now. But if you look out, say, 5 years, what -- I mean, what have you laid out? I know you've got a TAM analysis out there, as do many growth companies. But how do we think about like a longer-term trajectory maybe that you've discussed during the IPO or subsequent to that in terms of top line growth or revenue target? And kind of how does that shake out between instruments, consumables and kind of single cell and Visium?

Yes. So I mean, we tend to -- first of all, we're an applications for a German company, and we focus on like actual usage of our products. So much more so on the consumables, right, rather than instruments. Instruments are obviously great because they're enablers, and they provide sort of that tangible touch point in the customer labs. But ultimately, our business is about the applications and people running experiments. So consumables, they already are like a dominant portion of our business, and they're going to continue to be so. If anything, it's going to grow. So from that perspective, in terms of instrument placements, obviously, we're tracking those on Chromium. Visium doesn't have an instrument. And as far as we see, there's no really ceiling in terms of labs who are going to be using these products for the foreseeable future. So when you look at the 5-year road map, I mean -- or 5-year sort of time line, there's -- we don't see sort of any impending asymptotes on that, right? Lots and lots of labs that have not -- that are not using single cell and spatial and will be in the future, for sure. As far as sort of single cell versus Visium, Chromium versus Visium, I mean, I think, obviously, single cell is somewhat more mature, if you want to call it that, in the cycle given that Visium just launched last November. But we're still very, very early on in this inning. So there's tens of thousands of labs that are not using single cell and only thousands that are. And so lots and lots of growth I had for that. And Visium is, again, a few years earlier in the cycle, but has the same kind of trajectory. With the additional wrinkle that is going to -- what it's looking like is going to be adopted task in a translational sort of side of the world, which probably ultimately bodes well in the clinic as well.

Got it. And in terms of the like your new product flow, like, I mean, that's something that's very dynamic for the company. And when you look out over a period of time, whatever that period of time is, 3-plus years or so, like what have you discussed in terms of the pace of the new products and the contribution from new products? I mean, today, what you have is very exciting, and it gets you a lot of growth going forward. How much has that changed? How much do you add on top of that over the next couple of years, do you think?

A lot. I mean the -- kind of the way we look at the business is there's certainly -- if we just look at our platforms right now, and you can sort of turn off all R&D., there's tons and tons of growth just to keep the adoption again. As I mentioned, we're very, very early cycles of adoption. At the same time, the way we look at the world is, A, like you can never assume that there's not going to be competition. I mean, obviously, these are huge markets, and lots of people are interested in them. So we're going to keep investing in the platforms to keep improving the products, adding features, adding more capabilities to keep pricing ahead. And there's lots of sort of market expansion of when we could also drive through new product features and new products that we're going to be releasing. And then also just thinking on top of that, again, this is -- the products we have now driving the current growth, these are the products that we sort of invented and developed some number of years ago. And we're always thinking about the products, what we should be -- like what should we be inventing now and developing now and building now that's going to drive growth 5, 10 years from now, right? And that's kind of our mindset.

And in terms of Chromium, I know you kind of mentioned there's really no limit. And again, I don't have a model right now. So I'm just wondering, as a driver of kind of customer adoption and then kind of pull through, how do we think about kind of what have you discussed in terms of when you look out on placements, like I'm not sure how the Street models it. But like what have you shared in terms of the trajectory of those placements and maybe an upper band or a lower band? Any color on that front?

In terms of how many placements we expect kind of any given year and going...

Just going forward. Yes, yes.

Going forward. Yes. We haven't really talked about that. I mean you can look at sort of historically where we've been, and we had upwards of 600 placements last year. We had upwards of 500 the year before. And we expect something along those -- like, I mean, it wouldn't be unreasonable to expect those kinds of trend lines to continue, right?

Got it. Okay. And then, obviously, you've got a host of different applications in single cell. This is -- and this might be obvious, I'm not sure, but like which of these do you think has the greatest revenue potential? Like which one of your current products like applies to the biggest opportunity set? I mean it's hard to choose amongst your children, I'm sure. But I'm just...

Right. Right. Yes. Well, I mean, so look, the most natural answer, the most likely answer is you have to think about gene expression, the single-cell gene expression product. This was our first single-cell product we released back in 2016. It's on version 3 now. And it's certainly the biggest revenue contributor now, and it's hard to argue against its importance, right? RNA is probably arguably the most important molecule in biology, maybe competing with proteins somewhat. And you get like incredible amounts of insights from measuring on a single-cell level. So I think that's going to continue. Having said that, there's -- we talked about immunology earlier, and that has certainly keep like that substantial potential as well. I would also kind of emphasize that a lot of these products are sort of as we look to the future, there's going to be some amount of convergence because we talked about multi-omics. We released the product -- well, yesterday actually now, launched that combines epigenetic profiling with gene expression. So these were 2 separate products. They're still 2 separate products, but now, there's also product that does the 2 together. You can also do gene expression together with proteins with our products. You've been able to do this now for some number of -- for maybe 1.5 years or so. And that, I think, is also obviously very, very powerful. So there's also kind of when you look at it from a multi-omics perspective, there's a convergence of all like the different measurements that we should expect to see in the future. And ultimately, it's about getting the most comprehensive high-resolution, high-throughput view of every sample.

Okay. You've -- I mean, on the pull-through side, too, I know you've got an average pull-through, but that's an average of some really high users and, I'm sure, some early adopters, and it's been kind of steadily ticking up. I don't know what it was last night. I don't have a model, but I'm not sure what it was in the second quarter. But it's been similar to Chromium. It's been kind of growing at, whatever, $8,000 or $10,000 a year per user. I mean, is that -- is there a chance that, that goes more asymptotic that begins to go up more as these, I guess, the experience level and these heavy users become a bigger contributor? Or is the right way to think about it, that kind of steady pull-through? I'm not sure what some of the applications you mentioned and some of the familiarity and kind of publications, if, in fact, there's a reason to think the slope of the curve shifts upward?

Yes. So that's a good question. And certainly, I mean, the challenge here is that the average hides a lot of different dynamics that are happening underneath, right? And the other thing that I would just mention is we haven't -- it's hard -- the latest data we can realistically speak to is something like going back to the middle of Q1 because the once corporate heads sort of -- you lost that signal. I would say there's multiple dynamics that are going on, and the question is which ones are sort of -- will dominate in any given time. So our earliest users tend to be the heaviest users, to a large extent, because they have been increasing their usage across time. And so when you kind of split up our customers by cohorts, the ones that joined the earliest and the ones that joined 6 months later, 6 months later, they're all kind of tracking on this sort of parallel trend lines in terms of usage. But again, the earliest want to use it more. And so then the actual average pull-through becomes a function of how fast are people ramping up, but also how fast are we installing instruments. So when you bring in a lot of new users into the ecosystem, right, for a while, your pull-through is going to go down while they're like kind of -- while they're sort of adopting the technology or ramping up, getting their grants, figuring how to use it most effectively, those kinds of things. In the meantime, of course, our older users are still kind of have been ramping up. And so that was -- that has been the countervailing trend. And so up to now, it has mostly balanced out in a way where the average pull-through has been going up, but that's not like -- yes. It's not a guarantee that, that's going to be the case in the future because of the -- if our instrument placements start outpacing that dynamic, which on balance, probably would be a good thing, right, potentially, that could drive down pull-through for some amount of time.

Okay. Okay.

But again, I would say, kind of, ultimately, in the long run, we're looking in terms of share of wallet, like what is -- what are the researchers spending their dollars on? And we kind of see that ultimately, everyone should be running their experiments on the single -- high throughput, single cell or spatial context, right? And that's kind of our goal. It sort of matters less precisely where the instruments are. It matters to make sure that the samples are actually being run through 10x.

Yes. Okay. What -- I mean, the competitive landscape in single-cell genomics, like who's out there today? Who's on the horizon that you worry about or you focused on?

Yes. So we certainly had kind of a big spike in competition back in about 2017 with the Bio-Rad product probably being sort of the one that attracted the most attention. That has not at all done well in the market. And so we don't really see that as competitive really at this stage. There has been -- Becton, Dickinson has a nice product that's out there in the market. And there's always sort of upstarts that we look at that -- that's more of the sort of the unknown unknowns that we have to focus on, which is part of the reason we're keeping the -- keep innovating. So like, again, an example of the immune profiling product, for example. To the extent that people would have considered competing against us, recently, now the bar has gone that much higher with the release of the new one. And that's what we've done with gene expression previously. That's what we've done with our other products as well. So kind of part of the imperative for investing in innovation is to keep ahead of any competition and to make it hard for people to even think about investing.

I want to ask a question about pharma, but maybe just one on academic. Is there a -- you talked about share of budget or kind of share of wallet. Is there a view, like if you look at like the way the government funding is working, like is there a view or do you track like how much single-cell funding is kind of as a percentage of total? Is that going up? Does that matter? Is that easy to track? I'm just trying to think through in terms of a share of wallet...

Yes. I think it's quite a bit harder to track now because it's no longer like, hey, there's like this thing, single cell, and there's a bunch of single-cell researchers not getting single-cell grants, right? It's much more -- because it's now like really kind of widespread. And so it's much more about biology and the questions that people are asking and then they end up using single cell for that. So I think it's getting -- the fact that it has migrated from being a technology thing to just being kind of a pervasive part of how people generally do biology makes it somewhat more challenging, I would say, to track.

Got it. Okay. How about pharma? Like what -- I mean how big is pharma? I think it's certainly a smaller customer, a much smaller customer than academic. And can you speak about the pharma opportunity? And how does Chromium Connect -- is that -- is Chromium Connect related to pharma? And can you speak to that product as well?

Yes, for sure. So I mean pharma has always been -- we've always been excited kind of from the beginning by the potential of pharma, I guess, because, again, these biological insight's great for academic research. But ultimately, this is where the biomarkers are and that's where the biology is. That's how you can figure out which drugs work, which ones don't. And you see a lot of that evidenced in academic papers as well, especially now. What we started -- when we first started out, we've got presence in pharma since the very beginning, but it's been mostly in sort of the tech development groups, in kind of early discovery parts of it. What's been happening now, and you don't see it in the numbers yet because there's sort of this transition, is the expansion into kind of downstream workflows, more downstream sort of into development and other parts of the pharma value chain. There's quite a few clinical trials that are also kind of gearing up in various ways to look at single cell. So this is where we're pretty excited, and this is where you can sort of -- as we transition from [ that ] groups into pharma, this is where you kind of -- you can start seeing the growth happening in the future. Because as single cell, and later, spatial gets incorporated into standard workflows, the number of samples, the number of work that happens there is pretty -- is very large.

And in terms of Chromium Connect?

Yes, right. So Connect is definitely a big -- probably the primary driver there is actually the pharma. That's why we developed it because it has walkaway automation. That's the whole point. Like in academia, the fact is there's a lot of very cheap labor and -- which is not typically accounted for. You have postdocs, you have grad students. But in pharma, they do value that element quite greatly. And so yes, we see Connect as like one of the accelerants, specifically for the pharma business. That's -- This is where we've had most of our interest, although not exclusively. Definitely sort of some big academic labs have also been purchasing and been interested, core labs and such. But yes, the primary imperative has been pharma. That's where the interest has been coming from.

And before we shift over to Visium, just in terms of clinical utility, I mean, certainly, it's a very, very powerful research tool. But in research, and then if you're going to translate that into clinic, where does it -- where does like single cell as an -- kind of like a concept or application, where does that stand from a clinical basis? And where do you see that going?

I think it has pretty boundless potential because it's the same rationale. To the extent that you're looking at biomarkers, and you're trying to understand what is happening, whether -- look, whether it's for target discovery, of which we have now plenty of evidence, and a lot of it published, that single cell is really crucial. Like if you want to understand the pathways that are being hit, and which ones to affect, there's really no other way to get it than single cell. But once you -- so that's the kind of the first stage. But then when you look at biomarkers, it's kind of the same thing. Like a biomarker in a particular cell means a very different thing than a biomarker in a different cell. And you really need to know the cell state, and there's no other way to do this realistically other than single cell or spatial approaches. So the potential is obviously there. There's just kind of -- it's not even potential. At this point, it's -- the use case is very clear. I think it's the question of the technology sort of adoption curve. And pharma typically follows, especially kind of the leading academics. And then getting the right workflows in place, right, like automation, what I've been talking about, like figuring out a lot of logistics around sample collection and sample prep. Those are the kinds of issues that need to get solved now. It's not the fundamentals of biology or biological utility or clinical utility, I would say.

Okay. Maybe switching over to Visium. So I think you discussed last night, over 600 customers have adopted or used Visium to a certain extent, up from 400 last quarter, I think, 200 in Q4. So presumably, we know from capital commitment, there's a willingness for customers to engage. I mean, obviously, it's a really exciting space, and you guys are a leader. Is there a wide divergence between Visium customers who were just like, "Oh, I'm going to toy with it a little bit, check it out" versus ones that have begun to embrace it already amongst those 600 [ number ]? I'm assuming there is, but I'm just wondering like that 600 number, like kind of what is that capturing effectively?

Yes. No, that's actually kind of an interesting thing because coming -- we grew up in Genomics, right, 10x. And one thing about Genomics, there's always like -- you can sell 50 just about anything. There's always going to be 50 customers that will buy like a technology just to try it, right? It's not been the case with Visium, I wouldn't say. Like we -- the emphasis has been very much -- the new customers have been pulling at it from a translational side, and existing customers are sort of our big sort of single-cell adopter people. And it predominantly appears to be the case that people are like buying it because they have specific projects in mind or specific questions they're looking to answer. So relative to others -- I mean, I can't say there is no sort of tinkering that's happening, but relative to what I've typically seen with new technology launches, this is much more sort of intentional or directed. Like I've got samples, I've got questions, like, this should help me see them. And one of the metrics that I mentioned yesterday, too, that is the first time really we can track, is sort of repeat orders. Because again, Visium has been on the market for -- just since November. And then we had the big kind of COVID disruption, which erased a lot of the market signal. But now we are certainly seeing a substantial fraction of people reordering and racing ahead in experiments. So that's like a pretty -- again, a pretty encouraging sign, to your question, whether people are just dabbling or really seeing value.

Interesting. And then you announced the Visium clinical translational network. We talked about an improving accelerating workflows. Obviously, rate and spatial cellular relationship in transitional studies, I think you said 45 members, and you cited a few of them. And you talked about really the emphasis on long-term benefits versus shorter-term revenue traction. I mean, presumably, 600 customers, 45, I mean, these are -- these look like leading institutions. Presumably, this is going to be more than just kind of optimizing and kind of, again, R&D feedback group. I would think over the next 12 months, this network could actually be a decent kind of revenue contributor?

Yes. Look, I mean, the idea with the network is to create some sense of community where people can start helping themselves, right, that nucleus. So we're going to help educate, again, provide whatever resources are necessary from R&D or internally to get these people going on their own, specifically, right? These are -- and then for them to be able to help each other. And so that is creating this nucleus and kind of figuring use cases that they can then start running themselves and then amplifying certainly their own projects with the rest of the market. So yes, I wouldn't discount -- I think in the very near term, again, I wouldn't say that this is a revenue contributor on the very near term. But on the medium term, it certainly becomes on its own. And then kind of we expect it to build in itself.

And was that because the product -- I mean, did you do this with Chromium? Was that because the product in the market is new enough that you need like this kind of sharing and swapping of kind of insights amongst these leading institutions in order for them to understand what the product utility is? Or like what was the genesis of it? Obviously, it kind of makes sense for you, but...

Yes, I think it's less about utility because, again, all these people came to us because, presumably, they saw utility. They wanted to get -- I mean, we actually had to turn away quite a few labs as well. So I don't think it's a question of utility from there. And I think it's much more of a question of kind of making -- creating a community for them to sort of share their experiences and streamlining their kind of adoption curve in terms of getting kind of used to the technology. Again, I think it's different because a lot of these people are translational, right? It's -- they're not oftentimes on that sort of frontage of technology adoption. So with Chromium, our initial customer base was sort of genomics people, a lot of people who were like kind of doing sequencing, the broads of the world, and like -- they're used to new technologies, and they also have their own community to begin with. And so that's already sort of embedded. Like the AGBT Conference, for example. I mean, that's kind of a built-in community. We didn't need to do anything like that. Here, it's -- this is again a translational side of the world where that didn't exactly exist before.

Got it. And then I know you said in the beginning when I asked you the question, we talked about a TAM and you said -- I mean, TAM's one thing. Let's just execute on what's in front of us right now. But how do you think about Visium? I don't know what you've outlined. I mean, now [indiscernible] throwing out some numbers. But I mean, obviously, you're really, I guess now we're showing your more kind of overlapping product. But for the discovery side, for the translational side, how do we think about like the market opportunity that you guys see ahead for Visium?

Yes. So there's sort of 2 elements to this. We outlined our -- back last year, our $13 billion TAM for products. And this is really driven sort of by this idea of high-throughput, high-resolution biology and kind of what fraction of the life science total tools market, which is in excess of $50 billion, kind of looks at the world that way. And we see our products particularly suitable for that. We do see that the $13 billion is sort of evolving closer to $50 billion over time because more people will switch over to the high-throughput sort of way of doing things. As far as Visium is concerned, there's really -- you can look at it -- maybe split it in 2 segments, 2 subsets. One is the discovery kind of element in our existing customers. They're complementing the single-cell work with spatial work. And I would say that kind of falls roughly within that $13 billion TAM. But what the $13 billion TAM didn't really contemplate was more of these translational opportunities when you look at kind of tissue-oriented analysis. And so to the extent that we're seeing traction from a translational side of the world, that becomes the -- should become additive over time. And of course, none of this contemplates clinical applications. Again, those are further on the line, but with Visium especially, you can see that coming together probably sooner than we would have expected maybe a year ago.

Like true clinical? You mean like being used in replacement like IHC? Or clinical...

Ultimately. Right. I would say, yes, ultimately, for actual. Again, not in the near term. It'll take time. Again, it has to go through its phases. But given that the translation applications have been coming at us sooner than later, it kind of stands to reason the clinical applications will naturally come as well.

How widespread do you think the utility will be in like clinical trials? Like how many -- what percent of trials today, do you think -- I mean, it's probably 0% or 1% are doing spatial. Where do you think that goes to for the trials that it makes sense to do --

Yes. I mean, look, if you kind of look at it in the sufficient -- give us sufficient time, I do not see -- if you have a biopsy or need kind of a tissue sample, how -- assuming the cost and logistics are there, why you wouldn't apply spatial and single cell to that sample. Like I would -- that's where the information is. That's where you're going to get vastly more knowledge about a sample and vastly more actionable than otherwise. So I kind of -- I can't imagine that things are not going to go that way in a sort of predominant fashion, where it's going to be more of an exception when spatial is not used rather than the rule.

Okay. And obviously, FFPE, we spoke to -- I think it was Dr. Simon, or is it Dr. Gregory? I don't know why I'm blanking. Sorry for that. No, you're right. We spoke to Dr. Gregory yesterday from Duke on this panel, and he basically indicated, yes, he's working with 10x on kind of developing this FFPE capability. Kind of where -- I think you discussed at AGBT it'll be first half of '21. What are the biggest technical hurdles being worked on to make the platform compatible with FFPE?

Yes. I mean the general issue is that FFPE -- well, there's sort of 2 issues. One is it fundamentally tends to destroy the molecules in your sample. And so they end up, by virtue of being cleaved, being modified, kind of being stuck in the metric, they're just harder to measure. There's certainly multiple ways of addressing it. Again, we haven't gone into how we're addressing them. But definitely, we have seen enough proof of principles, experiments and different ways to -- that there's fundamentally no reason why it can't work. The other challenge with FFPE tends to be that it's a fairly heterogeneous sort of thing. There's lots of -- especially sort of given the time, the age of the sample. So if you go back far enough, there's essentially like archival samples that go back really far. There's essentially no molecules in there to measure, and if there's no molecules to measure, you're not going to get data. So I think it's the heterogeneity. So being very clear about what kind of FFPE sample it actually is. It's a lot easier to make things work for FFPE samples that are just made versus the ones that are much older. But overall, again, fundamentally, the molecules are there. There is no fundamental physics reason why Visium platform can't make it work. And again, we have now a fair amount of empirical evidence for that as well.

Got it. I got a question from an investor, which really just asked about the fact that you're going from discovery in translational. NanoString is going from translational to discovery. So kind of maybe the white space gets a little clouded up. Like how do we -- is this more of a rising tide and the big opportunity? Do you begin to bump in each other a little bit? I mean, the question really got down to how do we compare the 2 strategies, was the question.

Well, I do think the opportunity's very large overall. Kind of our view, and that's the view we've sort of articulated back on a road show and such, that ultimately, right, all of research, the translational research, then I would say, clinical work as well, should be done at the single cell or spatial context. And so kind of our goal, our ultimate imperative is that kind of much the research market and, ultimately, clinical market should be converted to this new wave doing things. And so when you look at it from that perspective, the market is huge. And lots and lots of opportunity here. As far as sort of NanoString, where you kind of I think -- again, I don't think -- I think mindshare-wise, for sure, there's definitely, again, on those conference, and there's definitely sort of that competition. As far as customers are concerned, I don't know if it's that intense at this stage.

And kind of what would be the biggest planes of, I mean, resolution? Well, obviously, price is one thing, right, because I mean, there's no upfront cost, which is tremendous. But what do you think the most important things are in terms of -- is it the resolution? Is it the flex? Is it ease of use? Just kind of what do you think are the key factors, in your mind, that you would want to continue to stay the bleeding edge on from a competitive standpoint?

Well, so for us, and it's been one of the central premises for our product platforms at the company is scale. Biology is super complex. You need to be able to measure lots of things simultaneously. That fundamental is the big driver. That's at the core of the Chromium platform. It's at the core of the Visium platform. It's the ability to measure many, many objects, whether it's cells or whether it's a high-resolution of the tissue sample. And this is where we're well ahead of anyone else, and that's where we're going to keep driving. It's that scale and it's the resolution, which kind of go hand-in-hand.

How much flex do -- are you able to do or will you be able to do with proteins, do you expect?

Yes. So proteins is the other dimension. Being able to measure lots of molecules. So for sure, proteins, we will be able to do. I mean, we've shown data for that. Very, very high flex. And again, with gene expression too, we can do the full transcript on clearly. So it's those dimensions. Measuring lots of molecules, again, whether it's RNA proteins; and then measuring lots of spots, 5,000 with Visium and, obviously, the platform [ microarray ] could scale much, much beyond that as well.

Okay. What stimulation between Visium customers and Chromium customers? Like I think you talked about a little bit on the call. Is there like -- how will that relationship play out in the future, your ability to kind of own the customer, if you will?

So at this stage, like, as I mentioned on the call, there's a substantial fraction of customers that are just Visium customers now coming to us, but the majority are still both the Chromium users as well as Visium users. And it's a pretty natural workflow. Part of the reason why we're excited about Visium in the first place is that you use the single cell, the Chromium approach, to kind of gain a sense of all -- census of all the cells in your sample. And then you run Visium in parallel to map those cell states, cell types onto your tissue. And so they're very naturally kind of used in parallel and pretty complementary to each other, complementary data types and complementary workflows, and being essentially tied together in software. And so that has been -- seems to be being borne out on the market so far, and we see that being pretty powerful as a general pattern.

Okay. Okay. And in terms of the -- I know there's some other -- I know there's a bunch of private companies as well in the spatial market. Like any technologies. Readcoor comes up, but I don't know how advanced they are, and I haven't -- I know there's a bunch from Garry Nolan's labs. Any other technologies do you think are worth -- that you guys have on your radar screen from a competitive landscape?

Look, I mean, we're always looking, and it's definitely a very interesting space. The value proposition is very clear, right, the market potential, and lots of customers have been looking at technologies in the space. I would say one of the issues traditionally here has been there's like a lot of academic approaches that work in a particular lab, but have had lots and lots of challenges scaling commercially into -- like into a product then commercially. And so I think this is where -- again, we've looked at all these approaches back before acquiring Spatial Transcriptomics, which became the platform for Visium. And we like Visium because, again, it's scalable in many ways that other platforms have had challenges. Again, a lot of these approaches have been around for quite a number of years now, but very hard to make products out of them.

Understood. So obviously, not covering the stock. I hit up on a bunch of different areas, but maybe missed a couple. What areas, maybe in closing -- obviously, the story's well known. But like what do you think maybe I didn't touch upon, or anything to conclude the conversation with about 10x that maybe we didn't cover?

Yes. I think we covered most of it. I think one thing just sort of that tends to be -- you kind of touched on this a little bit. There tends to be kind of the view, I think, over time; less so now, but before, around there's kind of a market for single cell, there's a market for spatial and kind of -- and how does it fit within the broader biology. And our view is that, again, much of biology needs to go -- will go to single cell and spatial approaches. So it's not so much like how big is this market, is, one, is everything going to kind of get converted to those? So kind of flipping that view, I think, is important. And I don't know if all investors kind of understand that yet. The other thing I would just emphasize, since we're talking about 10x, it's really kind of the ultimate source, I think, of our success so far and kind of confidence in the future is like is the team. And I think this is where we invest most a lot, a lot of energy. A lot of our sort of thinking around strategy and being able to see maybe ahead of others is a function of the fact that we have like awesome people here. And our execution ability has also now, we can kind of have a track record of what again is a function of having awesome people. And so that's one thing that oftentimes kind of in these kinds of conversations gets overlooked because you see the manifestation of it, but the [indiscernible] the people and culture.

Awesome. Well, Serge, with that, thank you again for being here. Really appreciate it after the quarter. And good luck at everything, and hopefully, we look forward to staying on top of the story.

Thank you. Appreciate it. It's great. Bye.