Welcome. Thank you for your patience while we got started. Hopefully, you're having a good conference and learning a lot here. I wanted to introduce, though they need no introduction, I'll introduce them anyway. We have Jacob Thaysen, our CEO, Ankur Dhingra, our CFO, and Steven Barnard, who's our Chief Technology Officer and Head of R&D here today. My name is Salli Schwartz, although I think you all know me. I head Investor Relations for Illumina. We're going to manage today's session as entirely Q&A. We want to be able to talk about the things you're interested in talking about. Very excited to mostly talk about technology and the products, as this is that kind of conference, so hopefully we'll focus on those sorts of things.
And we're going to, hopefully, if the technology bears out, take questions both from here in the room as well as on a webcast that we have open right now. So I'll pepper in those questions as they come through to me. If you have a question, I just ask, please raise your hand. Somebody will bring you a microphone. Please talk into the microphone. I will implore you, beg you to limit yourself to one question. We don't have a way to write things down, so if you ask eight-part questions, they're going to answer whatever they remember and ignore the rest.
We're doing that anyway.
Okay. So please try to limit yourself. I know you have a lot of questions, and then we'll just go around as many people as we can get. And I'll just call on people as I see your hands, so just try to be patient with me. Anything else I have to tell you? Oh, we may have members of the media both in the room and on the phone. For anyone that's from the media, I just ask that you direct your questions to our PR team and not ask them in this session, which is geared for the investment community. And I'm going to take the first question because I can. So I wanted to pose this to each of you. We have been talking about so many cool new technologies here over this conference. There's so many things that we've announced.
I don't mean to ask you to pick amongst your children, like Candy Roget said yesterday, but if you had to pick one thing you're really excited about and you wanted this audience to focus on, what would you pick and why? Jacob, I'm sorry.
Oh, I'm allowed to start. So I think there are so many great things being put out there, so it's difficult to choose between your children, for sure. But I still think that constellation is an unbelievably cool technology that completely sets us apart just from a workflow simplicity, but also the insight that constellation is providing in the genome. I think it's going to be the standard going forward for everything in rare diseases, germline specifically, also, of course, sequencing. And it's really creating a very different game in this space where nobody else would be able to actually provide the same insights. And this is the insight you saw yesterday if you were at our session where Dr. Stephen Kingsmore were in and talking about that they could see this Hemophilia A, which has not been possible before. Even other long-read techniques had difficulties to that.
Now they can. So this is exactly information that you want to have if you look for rare diseases and just whole genome sequencing going forward. And this technology is the only one that can provide that. So I'm excited about that. Steve?
Yeah, since he took mine.
They're all unique.
It really is a spatial offering, right? So the impact of that is really this: we have a complete portfolio now across the omics, from proteomics down to genomics, and across multimodal, from bulk to single-cell to spatial now. So the completeness of those technology offerings to get us into the next post-genomic age is now getting completed this year. And that's a huge inflection point for the community and for Illumina going forward.
Well, Seth, so you covered the core and the omics. So one of the ones, just to pick one out, I'm super excited about and have been personally driving a lot is in the Perturb-seq single-cell space. Many of you in the one-on-ones have probably heard me talk about it a little bit, and we've just launched a five billion cell Atlas program that we will build over the next two or three years at the most. And the reason I'm super excited about it is, of course, it unlocks an understanding of biology that hasn't been done before, where we will be able to manage the perturbations of entire cell lines rather than going after a small set of segments. But more also importantly for us, what you're also beginning to see is laying the foundation for a pharma strategy.
If you recall, for the three pieces of growth in our strategy that we've talked about, there was the rightmost column around software and the services strategy. You're beginning to see some of the early foundational work on what that pharma services strategy could begin to look like. This is new pieces of hyperscale technology. We think Perturb-seq can materially improve the speed from a drug discovery perspective. And then, as you layer on multiomics, specifically a combination of genetics and proteomics in that space, there are meaningful services that can be built there. We'll, of course, keep informing as we build that capability out. I'm super excited about that.
Good. Thank you. I'm going to go to Sophie first because she raised her hand even before we started, so...
Thank you for that. Jacob and Steve, if you want to do. On constellation, can it compete with existing long-read players in terms of multiplexing? I know I saw that on your roadmap, but can it actually head-to-head compare when you utilize an entire flow cell?
So let me start and then give you the opportunity, Steve, because I think Steve will say yes. But the point is that constellation is not only going after the long-read market. There is a big opportunity there, of course, if we can go into areas where we haven't played before. But I think more importantly is that it creates much deeper insight for our current market and the market we're already playing well in, in rare diseases and others, where we're now creating deep insight that no one else will have done to also a cost level where normally Illumina is going to take things.
Yeah, so let's set the stage and make sure we understand what we're talking about. So when we talk about constellation and delivering this expanded information, in 24 hours, you're going to get 16 samples out. So that gives us a 10B flow cell, eight lanes apiece, so 16 samples in 24 hours of a complete genome with phasing, structural variants, and all the variants that you normally get. Now, there is no technology to match that. PacBio, maybe three genomes, incomplete with two-day library prep instead of 10 minutes and over 24 hours of sequencing time. ONT takes about three days, one sample, and you're not going to get the variants at the levels you need for diagnostics. There is no comparison across the market today, and people forget about that. So right now, 16 samples overnight.
Thank you for that.
Multiplexing.
All right. We'll go to Dan here. There's a microphone there.
Thank you. Just wondering, I know, Jacob, I think you kind of referenced Roche on the stage yesterday, but obviously they're presenting later today, and just kind of wondering, Illumina's kind of high-level thoughts on the specs that Roche initially introduced, and kind of how do you think Roche's introduction into the market will impact both your share and kind of your strategy?
So let me start and then have maybe Steve go more into the scientific part of it. But first and foremost, we've been competing already for a while in this space. This is a competitive space. Illumina continues to build out an ecosystem that is not only about a sequencer, but end-to-end workflows and application that goes on top of that. Informatics is becoming an even more part of the technology stack. So I think it's going to be important for customers are not only buying a product anymore. They're buying into a whole ecosystem. They're buying in. Also, you want to do applications on that. You want to make it simple. You want to make the workflows. So that is the game. By the way, over here, we have the MiSeq, and the Ingenuity that is together is an end-to-end workflow.
You can add samples on that, and you can go directly into the sequencer. So it already exists, the end-to-end. So that mindset is within the company. If you look into the specs itself, first of all, let's say that we have seen a technology overview. We haven't seen a product launch yet. It's very difficult for us to actually speak to many of the details because they're not there. They have not been shared. There are some high-level details, but so I can't speculate on the details. And everybody wants us to speculate. Everyone wants to speculate right now. It's all speculations. Steve?
Yeah, so if we take a step back from this technology reveal, there's two directions. People are asking us how we're thinking about that. So I'm going to talk about the first one. The first one is diagnostic analysis of the whole genome. That goes back to constellation. And why is that important? So one attribute we do know is that the Roche technology is a short-read technology. It may be a little bit longer, but it's still classically short-read. So that's number one. Now, that puts it in the same group of people doing traditional short-read data quality and information. constellation takes us from that pack into a new dimension and a new innovation level where you're getting expanded information with the variants, the phasing, and the structural variants. So we're separating ourselves from those classic short-read capabilities. The answer to clinical is technologies like constellation.
10-minute sample prep and expanded information. They don't have that. No short-read technology has that. That's one pathway. The second pathway they infer is the counting applications. So what are those classically? RNA, single-cell, spatial. Where is the majority of cost in those experiments? It's in library prep. Two-day preparation for spatial, classically. Those kits are extremely expensive. That's why we haven't seen any really big science in spatial. Our spatial product is changing that. Sequencing of those counting applications is typically between 10% and 20% of the total cost of the experiment. You're not impacting science by decreasing counting costs in sequencing. You're thinking about the problem incorrectly. You're focusing on the wrong pareto. It's the library prep in spatial and in single-cell, and that was a major step forward in our multiomics strategy of acquiring Fluent, which is a scalable technology. It requires no instrumentation.
The new release with spatial that allows you to very flexible axes: the surface area of tissues you want and how much sequencing depth you want to answer the science question. When you look at essentially that influence on the marketplace, you can really put it in perspective there. Do they really understand the NGS marketplace and what the customer needs?
OK, I'm going to go to another Dan, Leonard in the middle here in the yellow shirt.
Hey, thank you. I would just love to understand a little bit better the concept of cost for insight, if you could put some numbers around that with any example you want to use. I mean, constellation, for example, 16 samples on a 10B. Does that mean it's $1,000 per genome? A single-cell experiment, what would that cost? Who can just any kind of more granularity you can give me would be helpful. Thank you.
Yeah, so on constellation, right now, as we say, we are right now one genome per lane. We are still in early access, so we have not provided all insights on the pricing yet. We also said it is in the hundreds of dollars. It is not in the thousands of dollars. That calculation is, of course, changing when we are also coming out with our multiplexing of that, where we can add multiple genomes on the same lane. That is what we are working on. That will come out. We felt it was important to showcase the technology to get people working on it, just get one genome on the lane. Rest assured, we will make this much higher plex going forward also. That will drive, of course, the cost. We will, of course, think about and we will be clear about application-specific pricing also.
We think that there is value in that in the constellation that will allow us to price it at a premium. But I don't think you should expect that you can take a cost of a 10B flow cell right now and divide it by eight and then say that's the pricing. That's not the idea. We want to make this competitive. We want to open up markets with it. If you think about, so that's in constellation. If you think about single-cell, as Steve was mentioning, in single-cell and spatial and others, the cost, if you want to run the big programs that Ankur is also talking about, the conversation is cost per cell. When you make a small project, it's really the cost per experiment. But you're looking at the cost per cell because you want to run as many cells as possible.
That's where we have, if you look at the end-to-end workflow and what we can do, where we both have the sample prep, the sequencing, and the informatics technology stack, we can actually drive a cost per cell that is at least two times less than anybody else out there. So that is one way of looking at it. And spatially, it's the same logic. We saw yesterday that we will price it very differently. And we're just getting started. Because we think if you look at spatial today, the examples, first of all, it's very, very small tissue you can put on our competitors on their surface. We can now allow for whole slides that we can sequence. So we can really run really full slides.
I can tell you for pathologists, which is the world I came from also, they want to look at bigger parts of the tissue. If you look into human tissue, you cannot look at, if you look at lung tissue, you need actually more than just a few millimeters. You need centimeters of insights. We will price that. You can go from one or five experiments up to hundreds of experiments or thousands of experiments going forward. That's the idea going forward.
Thank you.
Can you hand the mic to Puneet next to you? Thanks.
Thanks. Thanks for hosting this. So my question is, again, on Roche, if I could. When you look at their presence in the market, obviously it's strong in terms of diagnostics. They're building this platform to reach diagnostics. I think that assumption should be solid. But diagnostic market, you're well entrenched into diagnostic market after all these years. So can you talk a little bit about how you see that competition, those guys coming into the market, especially when some of the products that Roche themselves offer are competing with some of your customers? So I would love to understand that. And I think you had competed, correct me if I'm wrong, back in the dark days against Roche. So I would love to get that for you. And then just one question, if I could ask. I saw in the spatial slides, there was some Nanopore data.
Yeah.
Could you elaborate when that's coming out?
So that was your one question? OK. Yeah, so you're absolutely right. I mean, back in my prior life, I came from cancer diagnostic, a company called Dako, where we were fighting against Ventana Roche also. So I know that very well. I was both in the commercial part. I ended up also running R&D to really build the solutions, the workflow solutions to go out there and compete with Roche VENTANA. We're very successful, actually, coming back, for those of you who know that background. So I know who Roche is. I know how to compete with them. And I know what it takes to be in IVD space. This is pretty much where I grew up also. I also know that many companies, when you are in the diagnostic space, and especially here, you need also companion diagnostics, right?
So you need to work with the pharma companies to develop the companion diagnostic that goes together with the drug. That was a business I built up in the Dako and VENTANA days also. Most pharma companies would like to work with an independent. So I think building also, because in the end, in diagnostics, it's all about the assays, the applications where you can make decisions on. So the ones that have most companion diagnostic is also the one that is going to be successful and the ones that the physicians want to use. We're already out with our TSO 500 that is now an FDA-approved kit with companion diagnostic. And we're building more and more companion diagnostic into the labeling. So that is going to be very important going forward. Secondly, in the diagnostic space, IVD players or customers do not care about technology. They care about insight.
Having a new technology and putting it into an IVD market, this is not something you do over two or three years. This takes a long time to establish the technology, make sure that you can do something fast or you can do it cheap. It's about the actual applications that you can actually measure what you need to measure again and again, not one time, not in the hands of a KOL, but actually in the decentralized laboratory. This is a game that requires the highest quality of insight, but also where you're in a production environment, because that's how clinical works. This is what we do every day in all our laboratories today, and that's what we serve. This is what will require in the clinical market also. That's more in the decentralized also. It requires also full workflow, sample in, and result out.
That requires, of course, sample prep, automated sequencing, but also the full technology stack in informatics. We have all that. We're working on all that. So we will definitely have a very strong position there. And in fact, I don't think just because you have a brand name in that new technology it takes a long time to establish that. So information to be seen. So we have certainly had a very strong presence in that space. And then you're right. I mean, there's been a lot of conversation about vertical integration, as you know, also for Illumina's perspective. Now you might have a vertically integrated company. What does that mean for all our customers and the market space?
I think that could be seen as, I think, many customers that could be also customers to Roche might consider twice before they will sign up with them, because they now have the full vertical integration of Foundation Medicine and Roche and so on and the sequencing. So I think that there will be a lot of customers out there that still want to, as I mentioned, pharma wants to work with independent. Many of our customers today will want to work with an independent. So I think we will be in a very strong position going forward. On the Nanopore, Steve.
Yeah. Thank you for actually not eating your lunch and looking at the slides. I think you're one of the few people that caught that. If you've been following Illumina's IP portfolio, we've been establishing a very nice IP portfolio in nanopores, right? But that is just one research direction. The R&D direction of Illumina is to provide total solutions. Is that optically based sensing? Is it electronic based sensing? Each of these modalities will have its place in the markets. So we will choose the correct modality in the correct chemistry to satisfy the customer's needs. And we won't release a product unless it's meeting the future quality expectations of a technology, which is essentially Q30 now, right? And just a little bit more on that.
If a technology launches a Q20, it has to make up the Q30 or Q40 in library prep and sort of exotic, time-consuming library prep. You're going to see this in the Roche offering. It's three boxes. They didn't take much time to talk about that, unlike constellation, which the C- level can actually perform.
I've done it. Yeah.
So that's one point. The point of launching at the Q30 is the quality expectations. By the time these products hit the marketplace two, three, four, five years from now in the clinical market, those expectations are going to be above Q50. The reason is you're going to have to have the ability to go after these needle-in-a-haystack applications, such as MRD. That's what enables. So if your starting point is too low, there's very little you can do to make up for it using the library prep. So you have to start at the industry standards now, which is Q30, and then use library preps to get up to 40, 50, and possibly Q60 in the future. So I don't think that's much appreciated by the announcement and this positioning of, oh, yes, we're a clinical company. So that's a big question mark out there.
Yeah, and also the fact that when you are using duplex technology, you actually have to sequence substantially more, so it comes with a penalty, and it comes with many other penalties that haven't been really talked about in detail, so I think, as Steve was saying, for us, the Q-score has to be above. The native Q-score has to be above at least Q30 before you have actually a relevant product. Now, as Steve was saying, we're working on many different directions. Remember also the MiSeq i100 has a CMOS readout, right, and we can do sequencing in four hours on the MiSeq i100 today. That's another direction we can take. If we want to say if speed is important, we can use the CMOS readout for that, and we can, of course. It's a chip. I mean, we know how to make chips.
So we can make that bigger. We can make that the more powerful. If you want to go another direction, then we have SBS chemistry is fantastic. There's so many more things we can do. We have many dimensions that we can operate on and optimize depending on what the applications are. What we have always done in Illumina is to build solutions that can cover many different applications. Imagine if we want to say, let's build something that is unique for different applications. We can truly optimize that to a completely different level that we haven't really talked about. But that has not been the direction we've taken it because we wanted to make tools that could serve many different customer types out there.
I'm going to go back in the corner to Doug here.
Thank you. Good morning. I want to ask you about tactical levers you have to pull relative to emerging competition. So a few years ago, I think you could make an argument, and it's an oversimplification, but the solution, if you had a hammer for every nail, it was lowering the price per gig. That's what Illumina did more than anything. Today, there's new products like constellation, single-cell, spatial, proteomics and I think a lot of these have been viewed, including by folks like me, as ways to generate more revenue.
I'm wondering if what we've been overlooking is these give you the levers to price these new products in a way where you can protect the amount of spend per assay on sequencing by pricing aggressively with the adjacencies, where you essentially enable customers to do things at a lower total cost than anybody else, even if the others have lower sequencing. Am I thinking about it right? And beyond that, are there other.
Spot on. That's the whole thinking about whole workflow is that you, and that's why I'm continuing to say highest quality insight for the lowest end to end, and you want to provide that to the customer so they can optimize their experiments based on what it truly costs to run the experiment and not just what it costs to run one piece of the experiment, but of course, historically, the piece of the experiment that had the highest cost was the sequencing, so it was natural to work on that part of it, but as you said, if you go into these new technologies, especially single-cell, spatial, proteomics, and others, sequencing is a smaller part of it, so if you lower the price of sequencing, you're not really lowering the price for the overall experiment. Having the ability to own that whole thing, we can now drive optimize that.
Spatial, the sample prep is so expensive that it's prohibitive for actually making big experiments. We can now, with the end-to-end, drive down the sample prep to a level where you now are spending more time on sequencing, but you're optimizing for the customers so they can do significantly bigger experiments to the benefit of us also because they will sequence more. That is the way we think, and that is the fundamental logic in the strategy of seeing moving from cost per gigabase end-to-end workflows. I think this is going to be the game for the future, and very few companies in this space will be able to do so because it requires investment on all parameters in those workflows. Just coming out with a sequencer is not going to be the success criteria that customers are looking for for the future.
All right. We'll come up front to Tycho here, just in the middle, the blue sweater.
On the competitive front, just curious on your latest thoughts on ULTIMA. They've put up some interesting wins here between Chan Zuckerberg and UK Biobank. They're adamant they're making good margin on those. So they're not giving away boxes. So how do you kind of respond and counter to that? Second, I guess, are you assuming Roche goes reagent rental? I mean, that's what they do with chemistry, immunoassay. So does that have potential to kind of disrupt the market further? And then lastly, on spatial, how do you manage your customer relationship or your partner relationships, 10x, others that have kind of benefited from having you in the market now that you're directly competing?
Yeah. So under reagent rental , first of all, our instrument contribution to our revenue today is relatively small if you look at the whole. So we have reagent rental today already. And there's no problem for us to go in. Reagent rental, reagent rental doesn't really work in academic where it's more grant-based and so on. But if you go into the clinic, for sure, and you know the volume, then a reagent rental or price per test or whatever phrase you want to use is, in many cases, the right conversation to have. Because the reason that customers like that is when you're in the R&D space is that they can be reimbursed. So there's a 100% correlation with the price they pay to the vendor and the reimbursement level. That's the game we played back in days. We know how to play that.
We will go there also in the clinical market. But academic is not really interested in that. But that's, again, why we want to own the whole workflow. So we can make business model pricing conversation that is relevant for the customer. And if they have more money in one bank, if they have a CapEx budget, let's go and help them there. If they have an OpEx budget, let's go and a consumables budget, we can also use that. So we can build it up as we want to. And remember, again, when you buy a sequencer, you have a pull-through. NovaSeq, it's $1.3 million per year, right? And we know they are at least sequencing for the following five, six years. So we can look at the lifetime value of a customer and build the right model for that.
So the other one was how are we going to compete with our customers? I don't think that we're not competing with our customers. We are a life science tools company that have workflows that we want to put out there. We cannot put our workflows out there. But so we want to continue to collaborate with partners. It doesn't really matter whether we have overlapping technologies. And that's my commitment to all the partners is that we will always make sure that they're successful on our platform. We will do our utmost to help them. But as these companies are also working with some of our competitors, I think that's fine. I mean, we want to make sure that we optimize for the customer. And we want to make sure that our customer feels that they can trust that Illumina will help them no matter what.
We're not trying to lock them into anything. We want them to be successful. So that is a commitment. That's how I believe that the ecosystem has to evolve. Yeah. Everybody, there are some companies that like to compete in press releases. But you need to double-click on what's really real. We're coming out with a 5 billion cell project now with Broad. That's real. We will do that over the next three years. And we will also do more than 5 billion cells. So that's what we commit to. When we come out with and announce things, that's because we are actually delivering on it.
I'll start this way. We'll go to Patrick.
Jacob, you know this conference is a lot about technology, but also customer conversations. I'm sure you've had a bunch of them. I guess on the academic side, it's notable. Even I think one of the AGBT Chairs got their travel canceled because of the NIH stuff. So can you just talk about, I guess, the customer conversations? It feels like budgets are tight. And again, particularly on the instrument side, just a lot of scrutiny on all these purchases in the labs. Can you just talk about what you're hearing down here, what your expectations are on that front, and how we should think about when this loosens up and what could drive that?
Yeah. First of all.
Especially on the indirect side.
Yeah. No. And first of all, it's great to be here. And I think all of us and everyone, this is a very great conference to talk to customers and really spend time with them. So I really enjoy being here. And it's great that it's back in Marco Island. Our conversations with customers, I think this meeting has been very positive. Clearly, everyone right now, especially in the academic environment and especially in the U.S., are concerned about the situation with NIH. I think a lot of customers are still seeing that the budgets are there, that they can spend money. But there's, of course, a concern out there. As you know, many of our customers are seeing a lot of volume still going through in their core labs.
Others are more concerned about the future grants and less about the current grants. Yeah, I think we are just in a period of time where there are a little more concerns. There are more risks out there. But everyone sees that what we do in sequencing, what we do in multiomics is the future of where grant money will go also when things are starting to operate normally again. They will.
Yeah. Just one more comment there, Jacob, in the conversations I've had. With these NIH headwinds, the conversations I've had is people want reliability, and they want to be dealing with vendors and companies that have a long history of supporting them, delivering products on time and of quality, where they are afraid of taking risks now because of this sort of potential budget reductions. So they still want to do good science, but they want to make sure they can be guaranteed to do that good science. So that's a side of the equation that people aren't really talking about is the reality, right? As more things get constrained, you need reliability, and you can't take risks, which you may do in sort of times when funds are flowing.
So those conversations have been very good, especially with the emerging technologies and our history of developing and working with our partners to go forward. So that side of the equation has been really an aspect of developing these relationships even deeper that we had in the past with the core labs, with big customers, institutes, major KOLs across the country. So that's a side we're seeing also.
Yeah. I think you all know the corporate truth or corporate saying about no CEOs ever get fired by hiring McKinsey, right? I think there's a little bit of that here right now. Nobody is going to be blamed with going with Illumina. They know that's a safe choice. And that's also the most innovative company out there right now. So I think that is something you will see.
Let me add a small data point. And this is current quarter, mid-quarter. Of all the Xs that we've placed so far in the quarter, half of them have gone to research. Just as a data point, right? People are still buying. People are still taking deliveries of their Xs. And at least until the mid-quarter so far, roughly half of the Xs have gone into the research community.
Good. Thomas, Dan, I'd go to them next. We got to do the trifecta of Dan.
I've been waiting for that three in a row for a long time. Hopefully, one day that happens.
OK.
Jacob, one of the things, or Steve, for that matter, one of the things that was on the slide yesterday was Q55 accuracy in the future. Is that something that you think comes with puts and takes depending on what instrument you're using or what the bells and the whistles are on the genome? Or are you comfortable with your development path in a way that says these various metrics that other competitors are being looked at upon will be matched by Illumina, regardless of which one you're talking about, in a way that's sort of standardized such that there really is no room for discussion on whether you have the most accurate genome or the most complete genome?
Do you envision in a year or two being able to deliver a genome that is on all facets better? Therefore, the $8 billion that you've spent in R&D over the last 10 years are sort of future-proofing the business?
Yeah. Good question. No, first of all, I agree. And I think we talked about constellation is a part of that. Q55 and beyond is a part of that. But maybe you want to talk to what we'll be doing on high-quality scores.
Yeah. I mean, first of all, let's start from the beginning here. So the constellation is offering expanded information to medically relevant genes and sequences that no one could unlock before. And the Kingsmore story is a perfect example of that. That's just not coming from Illumina. So that's happening now. On top of that, we're going to be layering Q55. And the reason we're doing that is to get into applications that require the needle in a haystack, right? And the better that Q-score is, the more confidence you have of calling something above the background. So that's coming in the R&D pipeline. And that's really being driven by applications like MRD that is gaining acceptance in the medical world, right, in the diagnostic world. So we will have that in the future. So the third part of the question was, this is the danger of.
One second.
I really didn't mean for that to be one. It was just like the comprehensiveness of what you bring to the table in 2026 or 2027.
Yeah, so to take two steps back, what we're doing is redefining what genome quality is, and there's three aspects of that or four. First of it, it's cost throughput, so those are the basics that people have to be concerned about, but it's quality and clinical interpretation, so it's very interesting. We get into this debate over the last two decades. Is it Q-scores or callability? If you ask a physician, he could care less about the Q-scores. Can I call a variant for interpretation in either drug selection or understanding the disease? That's where the dialogue has to go, and there's a lot of noise about Q-scores right now.
But when you get to the end point of diagnostics and understanding and interpreting genomic data, it's callability of the genes of interest or the variants of interest. That's where we should be talking.
And that's what we are driving for. And I think also the technologies, some of the technologies that is mentioned that is out there today, they cannot call these things. You might be able to call 95% of the genome. But if you can't call those 5% where you have a lot of relevant variants in, it doesn't matter. If you can't call, if you want to do a clinical insights and you can't measure BRCA, it doesn't matter. See what the clinic wants to look for, that you have comprehensiveness. So we have to walk away a little bit and move on from just the standard terminology and really look for what the customer truly is looking for. Yeah.
Constellation map paves the path for a most medically relevant genome going forward.
Hey, Jess.
Thanks for doing this, guys. So a couple of questions for you, Steve. Could we see FFPE compatibility on spatial by the time you're ready for commercial launch at some point next year? And then second, given what you're doing on the protein prep side of things, is there any pathway of leveraging that to add protein detection to the spatial readout?
Very good. He's paying attention to the presentation. The first answer to the first question, it's in the roadmap. We're starting to work on that now. It'll be released in probably 2026 sometime, probably second half or someplace. But it's on the roadmap. But it's in research. Probably we'll reveal more of that progress at the next big conference, right? That's the first part. The second part is absolutely. So the next step in both single-cell and spatial is to layer in the protein level. So that's in research also. So now we're building the roadmaps, as you can see, layering protein, layering the epigenetic state with the methylation, a 5-base genome. That technology can be applied to all the other modalities, as we say, both single-cell or spatial. So the puzzle pieces are all coming together in those individual technology elements, as we've talked about.
Keep going across to Jack.
Thank you. I had one other competition-related question around the China region. I was wondering if there were any updates you could share around the unreliable entity list and just competing in that market.
Yeah. So first and foremost, we're still operating completely in China. We're serving our customers. Both we are selling instruments. We're selling consumables. We're serving them every day. We have a great team in China that helps our customers. We have had a lot of dialogue both with Chinese customers that have reached out and truly want to make sure that Illumina stays in China. We are very important for them, both from a clinical studies perspective, but also in the clinic and other applications.
They see us in China also as a main innovative leader there. So there's a lot of desire for them. Now, at the same time, last time you checked in on this, we had only known this for 48 hours. Since then, there have been multiple conversations with the right parties in China also. And we continue that dialogue. So for the time being, we're operating completely as we have done. And no change actually from that perspective.
Go to Kyle here. He's right here.
Thanks. Yeah, if you want to look spatial. So hey, for Steve. On the FFPE note, it's Poly-A. Is there any difficulty or challenges getting to FFPE or maybe the protein side, just given that kind of chemistry and structure? And then further, there are other Poly-A technologies and tools out there. Is there any IP concerns or alarming things at all? And then on the Connected Multi-omics software, how much of a differentiator is that given connecting all this that you're talking about?
Yeah. You hit on the sort of why it's in research right now from your first question. So there's two areas we're focusing on. Coming up with a unique chemistry to get through that. And then us certainly going through the freedom to operate. So that's just standard operation that we do in research. So that's what we're attacking. But you hit on sort of why it's in research right now. But we're making progress there. That's the first question. And then the.
Software.
Software.
Software. Absolutely. So I'll give you an example. Do a single-cell experiment; maybe take you three days to do. Now you're spending three weeks trying to analyze that data and a whole bunch of compute power and cost to do that. The ICM, the Illumina Connected Multi-omics software, is going to take those three weeks into hours. And it's going to give you state-of-the-art biological visualization across those different data types. And that's being driven by our Partek purchase, which was and still is sort of the leading visualization software in the market today. So it's extremely powerful. So when we think about the total cost of workflow and what we're offering is we want customers to be doing and focusing on biology questions, not developing the technology.
Because typically, in the end, those solutions aren't as good as professionally written software that is developed by a huge core competency of Illumina. It's going to be a major differentiator in the future as these products get accepted as the de facto standards.
I think this is hitting. We spend way too little time talking about our informatics stack, software stack, which is very powerful. It's really resonating with our customers. We have many customers now in the research setting also that is using our pipelines because we continue to innovate in it. This is also important from what Steve was saying from a workflow perspective. Customers don't want to go out and have to choose one product over here and another here and then stitch it all together and realize that it didn't really work from an informatics perspective and how do I actually visualize things, and now I need an Excel sheet to change my format so I can move it into another tool. They want the end-to-end.
But they also want to have the flexibility and the ability for researchers to really look at the different parts of the omics, so to say, with the highest quality. And that's why we actually it's not just a simple thing. That's why we acquired Partek because they were the leader. And we're now expanding that. So this is, again, going to be a very, very differentiated point. When you start to use those tools, you're not going to move over and make your own homebrew anymore. You're going to stay in that. And we will continue to innovate and drive this going forward. And I think this will be very something that customers want to come back to again and again and use. And that's also one of the reasons they're going to stay with us for a long time.
One more point there that maybe a nuance is the software solution, the total solution that Illumina brings to our customers is driven by three durable differentiators that very few companies have. First is the DRAGEN, FPGA and CPU acceleration. That is huge for saving money and decreasing analysis costs. The second is our artificial intelligence and machine learning team. We have more access to data than anyone in the world right now. All of that data is going to be driven back into ICM to help that analysis, right? You layer on top that the multiomics. Now you're getting a complete picture of biology and the tools to interpret it. That's extremely important.
Yeah. One thing we haven't talked too much about also in Steve's team, we have actually a quite large AI capability and AI team that is really powerful in analyzing the big cohorts of data that is now being created. So helping pharma companies, helping academia to really create that insight. And also start to build these foundational models that can help actually interpret biology much more. Very few companies have this in the world. I think there might be a few pharma companies that have this. But we are also one of those companies. And I think that's what Ankur was talking about with the Perturb-seq and other things. It's going to be super powerful for the future of analyzing the data set and help pharma find the right targets and accelerate drug discovery going forward.
We're going to go to Mike here.
Thanks for taking the question, guys. I mean, Roche has come up a lot. I think when you've discussed it, you sort of framed it a lot from the clinical perspective. But I want to focus more on the R&D side. And it's not going to be a Roche-specific question. If I just sort of take a step back, over a number of years, I think what we've seen is that R&D budgets, as it applies to genomics, as it applies to transcriptomics and multiomics and all these fields, they just haven't grown the way they have in the past. And so what I think you've seen is that as new entrants enter, whether it's Element versus mid-throughput, Ultima versus high-throughput, or as new technologies enter, whether it's spatial versus single-cell, you're just seeing buckets of money just move from one bucket to another.
There has been a lot more cannibalization in the last couple of years than there has been before. So you're talking about a lot of spatial multiomics capabilities. You're talking about long-read sequencing. But especially as you layer Roche into this conversation, are you not worried that this is just going to be a continuation of that theme of just the same R&D dollars moving from basket to basket where, yeah, you might see strong pickup there, but it might hurt you more of what used to be traditional bulk sequencing space? Just talk about that overall, what you've seen in terms of R&D spent from pharma and academia.
Yeah. No. So I think actually there is a huge opportunity in front of us. I think some of the barriers for success and really drive much bigger programs is exactly that the whole industry has been focusing on the one thing, just drive down one parameter in the equation and not looking for the end-to-end. Customers, both in research, need to have where they focus on how do you drive down and make it much more simple to do these much more complex projects like spatial, single-cell, and other things. That's why we committed to that because we have seen that. And when I talk to academic customers, Broad and others, the issue is in spatial that you're doing 10, maybe five, 10 samples because it's cost-prohibitive to do hundreds. So science has not been established in these areas.
It's because that there's been so many small companies trying to do one piece at a time, in fits and starts in the workflow. We're providing the whole thing. We can now drive it to a level where it can be much bigger programs. I think that's where you will see, when we start to unlock that insight and some of that you saw yesterday, you will start to see much more money flowing into this. Pharma is going to be all over this. This is going to be extremely important. If you see the actual number of pharma companies that was also here and in the meeting because they can see that this is something that would unlock that better understanding on biology and thereby, of course, accelerate drug discovery.
So I think that the pharma area, not just for sequencing itself, but the insight we're creating here is going to open up a completely both different business model for us, but also a big market. So I don't agree with the notion that we're just shifting around money. I think we're unlocking a complete new capabilities here. And so, yeah, I mean, if you want to just have a sequencer and you want to compete with us in that, you're going to be unsuccessful because it's going to be an end-to-end game.
Yeah. Just want to kind of be here. If you look at the history of Illumina going back to 1998, we did this a number of times. And we're continuing with this strategy under Jacob. And around 2000, we offered an end-to-end workflow and array technology for the HapMap project that was global. And we took over about 70% of that project at that time. Then NGS came on board in the preeminent large sequencing initiatives around the world using Illumina technology. So the GEL project is another beautiful example of end-to-end total solutions at large big science projects. We're using that philosophy in proteomics and in spatial in single-cell now.
The announcements with Broad to fund this $5 billion is just one more example of that. We have a history of doing this. We have a history of executing on this. And Illumina being the de facto standard in these major markets. So more to come there. But that's what you're seeing right now to put it in sort of historical perspective.
All right. Well, that seems to me a very good note to end this session on. Thank you all for coming.
Thanks.
I hope you have a good rest of the conference.
Yeah. Thank you.