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

Great. Thank you, operator. Good afternoon, everyone. This is Derik De Bruin, the Senior Life Sciences and Diagnostics Tools Analyst at Bank of America. Welcome to our 2021 virtual Viva Las Vegas Healthcare Conference. My colleague, Mike Ryskin from Bank of America is also here. And our next company up is 10x Genomics. And with us from 10x is CEO, Serge Saxonov; and CFO, Justin McAnear. Gentleman, how are you guys doing?

Great. Thanks for having us.

Thanks, Derik.

So 10x was actually -- it's hard to believe that we just did the IPO in late 2019. It feels like -- it feels like a much longer time than we were previously. I could say a lot of the things that we -- a lot of the conversations that we've had on 10x over the -- over this -- over that period still involve a lot of conversations about what exactly the company does? Why is it differentiated? So I think for those new to the story, could you spend a couple minutes talking about your platform? Why people should care about single cell analysis? I mean Mike and I are old time lab rat, so we get it. But I think we're more rare in that understanding of this one. But I think it would be great to sort of do just a basic nickel sketch on 10x, Serge?

Yes. So stepping back a little bit, kind of the premise of the company is to build technologies to accelerate science, and ultimately, kind of clinical diagnostics and health care based on science advancements. And one of our central premises is that biology is incredibly complex and in order to address that complexity, in order to drive new understanding, you need technologies with really high -- large scale and high resolution, being able to measure lots and lots of things at the right kind of resolution, the right fundamental unit of biology. And the fundamental unit of biology is the cell, the single cell. And it's -- for people outside of biology it's kind of actually sometimes surprising, that's largely counterintuitive is that until recently, when we measure biology, we would take a sample or take all the cells in those -- in that sample, and would mix the contents of that together and then kind of get an average profile. And with 10x, even going back about 5 years, like when we first went commercial, we introduced the sort of technologies to be able to analyze biological samples at the single cell level, where you actually individually interrogate each cell, measure its entire gene expression profile or other analytics like proteins and epigenetics across thousands -- tens of thousands of cells in a single experiment. And from first principles, you would have expected that to bear fruit and be very useful, and it has, in fact, turned out to be the case. In fact, it has turned out to be more useful than people anticipated, even the kind of the bullish people at the beginning. It turns out that just about every single tissue and every biological system is highly heterogeneous, only cells are doing different things. Whichever disease you look at, whichever kind of fundamental biological question, that ends up being central. And you see -- now, we've seen multiple thousands of publications that have come out using 10x products to kind of -- to establish that as the foundation. And then kind of going -- more recently, we also launched a platform called Visium platform for analyzing tissues with spatial context. So in -- on top of that kind of knowing what is in there, like with individual cells, the fundamental unit of biology, starting to get a sense of how things are arranged with respect to each other in tissue. And that also turns out to be incredibly useful for understanding the basics of biological processes, and ultimately, driving new discoveries in diagnostics and cures.

Great. Makes sense to me. I think one of the challenges we've had with 10x, I think investors have had to. And I just literally did 2 of these e-mails in the last couple of weeks and this 1 is people -- because you're not selling directly into a clinical end market, there's no patients, there's no number to sort of figure out and say like, oh, what our technology can use this patient, here's the penetration rate, like this, how do you sort of define the TAM, right? I mean that's ultimately this. It's like, I think, intuitively, as coming from our science background, we know that scientists are going to want the technology. We know there's a lot of interest. We can sort of see it. But I'd be darned if I have a really good idea how you define the bigger market. So how do you look at the TAM? How do you look at the opportunity, and sort of put that in terms of where your penetration rate is now?

Yes. So it is a good question. It's the right question because it is a challenging question. The answer for the reasons you precisely mentioned, there is not -- we're not replacing a particular technology. We don't have a specific patient number like disease prevalence that we're addressing. We are going through the research market, and there's a couple of ways to triangulate on the total opportunity size, at least directionally. One is just the total number of dollars that are spent within the ecosystem. And again, this is just focusing on academic market. There's going to be clinical opportunities down the road as well, but setting those aside just looking at the academic market. There's the dollars kind of spend on ecosystem. And our view is that this is a foundational approach for how you design. So ultimately, it should transform or move much of those dollars into the ecosystem that's based around single cell analysis. Every time you do a tissue-based -- you start with tissues or cells, you really should be analyzing that individually those cells and tissues with either spatial or single cell analysis. And the total amount of dollars that people spend on tools is sort of in order of $60 billion right now. And if you kind of start zooming in where people are doing more high-throughput experiments and kind of looking together large scale data, which is kind of our sweet spot, even that gets down to more like $10 billion to $15 billion. And that's for the near to medium term as this is roughly the space that we anticipate to be operating with them. Although these boundaries are pretty fluid because we do see people kind of coming into the ecosystem from well outside those areas. You can also look in terms of -- just kind of to get more tangible maybe in terms of just placements, okay, how many labs are out there? Given that we kind of -- our ambition, ultimately is to get our instruments into every lab bench. That's how we can subsidize the market. And that starts getting into kind of 50,000 to 100,000 kind of placement if you think in those terms, as the potential for it, whether it's instrument placements or consistent users of our reagent products is our target. And relative to that, obviously, we're very early on. There's 20 -- about 2,400 instruments out there, the Chromium. That number is growing rapidly, but percentage-wise is still very low relative to the potential.

Yes. But I mean, is every lab going to need one? I mean I think there's some labs that sort of like dabble, may do a couple of experiments in single cells, but may not necessarily purchase, I mean, they may go to a core lab. So I mean if you think about -- I think you've got through like the hub-and-spoke sort of model, the sort of way you use things like this one, right? I mean so I guess there's probably more users -- there's probably more users out there than, I would say, but certainly, it's not a one-to-one correlation between the number of investigators and the number of boxes you're going to place, right? There's a bigger universe ecosystem around it.

Well, potentially, right, but we do -- so a couple of things. First of all, just empirically, we do see customers like they can use like the lab [indiscernible] do, for example, with the instrument. But the convenience factor, we have many examples, kind of drives them to get their own. And it depends on how much they run experiments. But as soon as they get over some threshold, that becomes a pretty easy sell. So we do see empirically us going well beyond sort of just the cores or just sort of the centralized labs, where like once an instrument gets placed in a particular place, it does kind of start reeling people in. Now it is kind of a function of how much those people use the system. If it's one experiment, every one in a while, then that doesn't necessarily necessitate getting one. But we do see people kind of ramping up along this curve. And yes, the thing is at this stage, it often seems and especially if you go back a couple of years ago, single cell was kind of a newfangled technology. It's a little kind of intimidating, data analysis [ set where ] you need to get scale. But it has been getting more and more accessible. And part of it is driven by us, part of it's driven by just people getting more used to it and using it. But we've been working through new product configurations by introducing new software tools, by introducing new sample prep tools to kind of keep lowering those barriers to adoption, and ultimately, the pricing and so on. So when I think in terms of like the end state, if you like premise them, taking care of the pricing kind of -- cost issue, taking care of the workflow kind of ergonomics issue, to my mind, the end state is still kind of a slight -- it's hard to imagine it sort of in any other way because if you had the choice -- if you weren't constrained by those other things, if you had the choice, you would be running experiments with single cell resolution.

Yes. Yes. Got it. So you mentioned it. I mean the bulk of your customers right now are in the academic markets. And I think some of the disappointment on the quarter was the fact that the academic markets hadn't yet rebounded as robustly as I think the Street was hoping for. Can you talk about, first of all, where your academic customers are right now? What are some of the still constraints in that market? And then I want to move this to -- like expand it into the biopharma space and the growth opportunity there?

Yes. So I mean there's a certain level of nuance in terms of when we talk about bouncing back and kind of reopening, and it's important to put these things in context. I mean, first of all, just on -- you look at the business, how much it has grown. Going back to Q1 of 2020, yes, we grew close to 50% from that point. And that was a close to normal quarter. The COVID was just taking shape. So everything should be kind of, I think, calibrated to the fact that this is on the background of rapid growth for the business overall over the course of the past year. Now there's headwinds from COVID. But again, in the context of Q3 and Q4, where there was like massive kind of bounce back where people got back in the labs. But since Q4 and going back, we made us sort of on our call -- after the Q4 earnings, people are back in the labs, but they're not operating as efficiently as they were before COVID because they're all these kind of -- all the restrictions around social distancing about when people can actually be in the labs, when can people be together in the labs. And it's been -- if you ballpark it's roughly 90% or so efficiency, although obviously, the number has some [ air buzz ] around that. And what we've seen is that there's a certain sort of asymptotic kind of plateau, right? Eventually, people will get to 100%. But it will take some amount of time because it has to do with regulatory and social inertia. People are back, but just like that efficiency is there. And so that's -- and that's also heterogeneous. Regions, certainly, like when you look at Asia, for example, there's no -- especially in China, there's no effect you're seeing. Europe is fairly negative last quarter, especially. U.S. is pretty heterogeneous. So that's kind of -- that has been sort of the story so far in academic market.

So let's talk about the biopharma opportunity. I mean we did -- I mean we did a couple of calls with biopharma customers, and they certainly raved about the product. I think it was more about whether or not they were going to -- how broadly within their organization, single cell analysis should expand. So are we still in a situation where the academic community is sort of like the fast -- sort of like on the bleeding edge and the pharma people are just now starting to follow and do this? And it's basically where -- can we think -- let's think about the biopharma opportunity because you're clearly underpenetrated there from where you should be if you benchmark it to other technologies that we're familiar with?

Yes. Yes. So I mean we definitely are. That is true. And it has always been biopharma follows academia, like we're talking about this news regarding leading-edge technology that goes into initially parts like [indiscernible] development of the pharma. And we are like where every pharma kind of within those groups is using 10x. And then like within the pharma, there's sort of this progression along the chain, where I think we're used quite a bit in discovery, especially sort of the target discovery, where a lot of that kind of work is similar to the academic work where you're trying to kind of find the genes responsible for like -- responsible for different disease conditions or the expression networks that are perturbed in different ways in healthy and disease tissue. And you have things like CRISPR screens that are also being used. But again, and that's -- we definitely kind of -- that part has been gearing up. And then -- I mean, we're also seeing examples, but I think it's still kind of early in the initial examples, kind of further down the chain where you start getting into kind of -- once you start getting your lead optimization preclinical studies, animal models, and then also some initial examples of actually clinical studies where people are doing correlative, these are not the endpoints, but correlative biomarkers to existing clinical studies. So like we're seeing us kind of penetrating through the whole chain of biopharma, but more so on the early stuff that's more analogous to where academia is and over time kind of progressing further down that workflow as you think about the progression of drug development.

Got it. Yes. And I mean also certainly having more translational types of products on the back end with Visium and then some of the [indiscernible] spatial will certainly help drive as well, right? I mean that's -- that is driving the pharma market.

Sure. I mean some of the other things that we've been introducing around products like sample prep-oriented things like RNA profiling is coming, fixed RNA profiling is coming, later is going to help there and as well as expression like CellPlexing and such that help people run more samples together kind of in a single batch. So there's more of that coming that's going to -- that's meant to accelerate that adoption as well.

Got it. I mean you sort of alluded to the fact that you have a very aggressive new product portfolio. I mean you rolled out a ton of stuff this year, you had your symposia, I mean, your -- what was the [ 10x ] Xperience, I believe, is what you called it in March, which once again, feels like an age ago. Can you sort of talk about some of the new products that you called out? Things like I think you've got the CytAssist. You've got the -- some of the other -- the Chromium X, the Visium HD. Can you sort of talk about the new product portfolio? And kind of sort of what you're thinking in this year for numbers and new products there? And the question I've gotten though from investors -- from some investors is like, is there any chance that some of these newer products are going to cannibalize some of the older products?

Yes. So kind of putting them all maybe on a sort of temporal progression here. So the products that we have actually launched sort of earlier this year, there's the LT kit, lower through-put kit for Chromium. That's meant to kind of reduce the barriers for the initial adoption, either for new users or for existing users trying new types of experiments. And the idea there, the goal is kind of long-term expansion of adoption for chromium for single cell. There is CellPlex, which is the idea of like pooling multiple samples together into a single 10x channel. And the idea there is lowering cost per sample if you have lots of samples to run. And this is a way for us to get a larger share of the wallet for existing customers, and again, kind of lower the barrier for adoption broadly. And 10x Cloud is another -- like this is the streamline informatics for people. All 3 of these are meant to drive -- over the medium, long term, drive kind of the adoption of the single cell of Chromium and general adoption of single cell. We bought to -- kind of staying, I guess, on the Chromium side, we're going to be releasing Chromium X in the second half of the year. This is a new instrument that's going to support high-throughput experiments for running large numbers of cells and enabling new kinds of applications. So it's the potential -- some amount of risk in terms of that cannibalizing sort of existing because you drop price per cell. But of course, you're running large experiments in principle that can have something -- cannibalizing effect. I think that's going to be pretty minor because I think it's going to be more about just like new experiments that could be going to be now enabled that were just too expensive previously on a per cell basis. CellPlex is another one that has the potential to cannibalize in a kind of immediate and near term, because, in principle, it is dropping the cost per sample and so people gear back up. I think that's going to be fairly -- we think about this, there's going to be some other effect that's baked into our kind of expectations in the near term. But in the long term, they should definitely expand the usage and ultimately drive more adoption. Onto -- on the Visium side, I mean the big one is Visium FFPE that we're launching this year. So we're definitely excited by that, lots of interest. We're now starting to gear up sort of the commercial organization, started taking preorders. I think that's pretty complementary to our existing sort of customer base and revenues. As we think to next year, CytAssist is going to be coming in the first half of the year, and that's going to -- I think that's going to be a further accelerant to sort of like on top of sitting on top of the FFPE capabilities to now give us access to all these sort of archived, premounted tissues that are premounted on slides. And then Visium HD, I think, is going to be a further kind of -- that will really kind of bring the platform into its kind of full realization with the single cell resolution. I don't think that's having much of an effect at this stage. It's something that customers are, for sure, excited by. But it's far enough away that it's not yet having effects on existing products.

So I just had a client Bloomberg chat hit me. The client is asking, could you talk a little bit more about the Chromium competitive landscape? And sort of -- and how that sort of looks right now? I mean you're obviously the market leader in single cell, and you've got almost near first-mover advantage on this one. But what sort of is the competition coming up to like on the -- on your deals?

Yes. I mean, look, that has been a constant. There's some amount of competition on the single cell from -- back from 2016, 2017 when we first launched it. There was -- there was big companies in our space, they still to some extent operate, like Becton, Dickinson. Biolumina had a product. And there's been sort of a constant theme over the last several years, it's just new entrants, new company start-ups, that come in with new kind of oftentimes approaches from academia that get sort of -- trying to be commercialized. And there's definitely a lot of sort of small companies kind of just like there has been before. Now we're watching them. I mean part of the reason why we keep introducing new products and innovating is to keep pushing us for the performance side and the capability side. The other thing also, we work hard to have good strong relationships with our customers so that we listen to them. They tell us what they want. And they've now gone used to seeing those things materialize as we release new products. The other thing, too, is like this market -- life science market in general is pretty sticky. We've got [ pseudo-rational ] customers like Supersmart. But biology is just inherently unpredictable. And so once you have something that works, changing that -- now introducing that variable is something that people just are aversed to, right? And that's -- this is where we gain a benefit from being an established kind of company now in the space.

Great. Can you talk a little bit about the pull-through metrics on some of your equipment? And where they are right now? And where you're set to go? I mean you've got a lot of new products coming in. I mean you're lowering the cost of samples. You got to spread these new -- you've got to spread the consumables over these different things. I'm just sort of thinking it's like, is where -- how much more upside is there to the consumable pull-through metric?

Serge, I can take that one. So the consumable metric is -- it's a metric that we definitely watch and track closely, but not necessarily optimized for. Our primary goal is to place as many instruments as we can and drive overall consumable usage in total. The pull-through metric is really a function of just the gross utilization of the instruments, including instruments placed in that quarter, divide into the overall consumable revenue. Theoretically, really high ceiling since [ on ] the Chromium controller, it's really only about 20 to 30 minutes as far as run time on the instrument. So you can get into a multimillion-dollar ceiling using really conservative assumptions. The number that we've given to think about for a near-term pull-through is $150,000 annual plus, maybe slightly above that. I think it's interesting when you look at our -- Serge mentioned the 50% overall revenue growth year-over-year, Q1 of '21 compared to Q1 of '20. When you look back at Q1 of '20, we had an installed base of roughly 1,800 plus instruments. At the end of this last quarter, we had an installed base of, if you take the 2,412 that we ended the year with and tack on roughly 200, 2,600 plus. So we grew the instrument installed base over 40% year-over-year. And then if you do the math on the pull-through metric, it increased slightly year-over-year. And if you look at the quarterly run rate, it's right around that $150,000 that we've talked about. So we're going to continue to focus on placing more and more instruments each quarter. We haven't necessarily given a number for this year. But we said that we will place more than we did last year. Last year, we placed 746. And so you figure somewhere in the 800s, maybe high 800s. And so you do the math on that. And you can get to the lower end of our guidance. And then as you mentioned, too, there's some new products coming out, new instrument coming out in the second half of the year. And so we do expect some lift from those. But as the overall revenue base continues to grow against the point where it's at, those incremental new products have less of an impact on the quarter than just the base business does.

Yes. Yes. So one of the other questions I've gotten from investors and -- this reminds me, I have one of these sitting in my inbox, that I have not responded to yet is, I still think there's some confusion on what exactly in situ is and sort of like how it fits in. It's like -- I mean, it's -- a lot of companies are talking about it, but I don't know if anyone has. I get the sense there's just a general investor confusion about what that means and how it relates to Visium. So what's the nickel sketch on what in situ is? And sort of like what your product offering are, what that offers science, the scientists?

Yes. So the thing is it's -- makes it challenging, I think that's where a lot of confusion comes from, like it's very early on. And in terms of the technology development, there's not really anything on the market as far as products are concerned, and there's sort of this shadow boxing around [ recent ] specs that's still some amount of time away. And putting together this kind of technology is just one thing that everyone should appreciate is it's quite challenging because the technology is meant to be a sequencer that works on human tissue, not just any tissue, on a range of human tissues consistently. So it is -- like it fundamentally requires bringing together a lot of different sort of competencies and advancements. So that's important to collaborate. We're still kind of looking -- when we talk about in situ, we're talking about the future, right? And specifically for us, we've been -- I mean, we've been pretty consistent. Like it's not yes -- we don't -- we haven't yet talked about the time line for when these products are going to be coming out, it's going to be a third platform with many products. But it is a future-looking sort of series of products in the platform. I think where it kind of -- if we put it in context, especially with Visium, which is out there right now, is getting really significant additions this year or next year, we see Visium as like perfect discovery and translational research platform for spatial. And it's actually -- it's really hard to imagine anything better because it can really give you really high throughput and arbitrary kind of accuracy of reading individual molecules. And the thing that we are expecting, anticipating is like as people run more and more experiments with Visium or with Chromium, and they're learning -- like they're learning what defines different cell types, what define different tissues, what defines different expression cells, that tells you what you should be looking for then deeper for any particular tissue or disease type. And so then following up on that, like once you know what you're looking for, the tissue becomes the most natural format for actually running more samples, validating them for characterization of your samples in a targeted fashion, in a targeted and integrated fashion. And that's kind of -- that's the key thing. It's an integrated platform that does targeted assets, particularly well, which means it's better for validation, it's better for ultimately clinical use cases, whereas Visium in contrast is great for discovery and translational use cases.

Great. That is helpful. So I think when people think about the Chromium portfolio and sort of think of this, I mean, there's a lot of focus on there's -- you've got gene expression, obviously, being the biggest application, but there's also epigenetics. There's also the [ annual ] repertoire. How do you sort of play in the proteomics market? I mean you've got -- there's clear applications for doing protein analysis with the platform. You've got some products out there. But how should we think about 10x as a proteomics play?

Yes. Well, that's interesting. That's something we've been kind of anticipating and thinking about for a while. There's a capability that we rolled out some number of years ago called Feature Barcoding that allows you to measure proteins in a single cell along with gene expression or along with immune profiling products by oligo-tagging antibodies and measuring them. And it actually has become quite a significant use case. Like, if not the majority, but at least the large traction of all single cell experiments now from 10x actually run with measured proteins [ in cells ] one fashion or another. We've -- the way we approach the market is by enabling partners to create their sort of panels of antibodies with the oligos conjugated to them. And that's been -- it's been reasonably successful, but we're also working just kind of rationalizing for our customers and creating this ecosystem of partners to bring more of this content to the customers. And we see that as being a huge value-add to the customers, like huge growth area because, a, this is -- it's the first order analytics of proteins, and you can reach through this approach -- by oligo-tagging, you can reach very, very high plex levels. And so it's a matter of kind of putting those content -- the content together. But I think in terms of value creation, potential is huge.

So one -- we're in the last minute here, but I've got one incoming from a client. Can you ask about the Bio-Rad IP outcome? Basically, are we done with the legal stuff now? Is this something we can sort of ignore? Or is -- do we get more of these press releases at some point?

Well, I mean, look, there's going to be a -- there's still actions that are in play. We are well past sort of what the big battles that we had back in days before certainly around the time of the IPO, when things looked or felt potential existential, we're not in that kind of world anymore. There's -- yes, there's still actions going on, and they're going to keep going for some amount of time. But that's just -- that is kind of a fact of our industry. There's litigation, there's IP litigation.

Yes. And one final question since I have the ability to run over if I want. What do you think is underappreciated about 10x? What's misunderstood?

That's a good question. I think fundamentally, the company is about capabilities. It's certainly not about the market we have right now this quarter or given this year, it's the fact that we can develop innovative breakthrough technologies that deliver like -- I mean, deliver -- push the boundaries of biology and deliver breakthrough value to our customers. And it's not about any particular technology. It's not about any particular market right now, but we've built a company that's meant to kind of bring the future forward. And the scope of the ability and the scope the ambition, I don't think people appreciate.

And with that, that's perfect. Serge, Justin, thanks for being here. Investors, thank you for listening. We appreciate your support [indiscernible]. Everybody, have a great day, and talk to you soon. Thank you.

Thank you.

Thanks, Serge, Justin.