Hi, welcome to our next Fireside Chat. I'm John Sarver, one of the UBS Life Sciences analysts. Joining me on stage is my co-coverage, Elizabeth Garcia. We're happy to host Singular Genomics here for our next Fireside Chat. With us today on stage is Drew Spaventa, Founder and CEO, and Dalen Meeter, who's Head of Finance. Thanks for joining us. You maybe kick things off here. Let's start with the G4 launch. You now have 11 commercial units in the field. Maybe can you provide some of the initial feedback from customers, you know, any learnings that you've now had over the last three quarters since the launch? Yeah. Yeah. First of all, thanks for having us. Good to be here. Yeah, the G4 launch is underway at this point. Just to remind everybody, the G4 is a benchtop sequencer, pushing the kind of performance in the key areas, throughput, speed, flexibility, and really from a profile standpoint, is a notch above any other benchtop instrument on those key performance indicators. We've had a ton of learnings this year. I think we've been pretty, you know, candid in our earnings calls, that getting the G4 to a point where we can manufacture and supply it at scale, there's been some challenges there. We're feeling a lot better about where we are now. A lot of the learnings, you know, have come from internal supply chain and manufacturing. You know, understanding, you know, how you can, you know, robustly, build and bring up units, how you can, manage customer expectations to bring up units in their sites, the right way. Then once you have units that are, you know, kind of up and running, you know, frankly, you know, customers find ways to break them that, that you weren't aware of. You have to go through those learnings and figure out, you know, how you, you, you know, get the customers back up and running, and then implement longer term fixes in the instrument design. There's an iterative process that, that just takes time with complex instruments. Long-winded way of saying, the launch is, is now, you know, really getting to a better place where we feel like we have some momentum behind us. Second half this year we should start to see some really nice ramps. We feel good about where we are. Great. I also wanted to mention, we have iPads here on stage, and there's instructions if you'd like to ask a question from the audience, we can take it up here, too. You know, speaking of that second half ramp, and sounds like, you know, 3Q may be on the low end of that two to four units per month that you've talked about shipping. Any just additional color on the outlook for the second half, and can you talk about, you know, funnel and backlog and how that's tracking? Yeah, you know, maybe I'll provide just a little color, and then Dalen can, can, can add on. You know, the funnel that we have right now is well over 200 qualified leads. When we talk about a qualified lead, there's a, you know, set of criteria that, that, qualifies them, so to speak. It's do they have a need for a new sequencer? Are we speaking with the, the right person, the decision maker? Do they have budget, and is it within a timeline that's within the next, you know, several quarters? That, that funnel is really strong. Converting the funnel into, you know, placements, that's still TBD on how quickly we can kind of really ramp that into placements for Q3. We're, we're definitely expecting an increase over the 1st half, and even more so in Q4 into the next half of the year. I, I don't know exactly where on the two to four per month we'll, we'll, we'll land, but definitely ramping into Q4, with more in Q4 than Q3, and then likely more next year than this year. I don't know if you have anything to add. Yeah, maybe just one comment. You know, we've recently launched, you know, our F3 consumable kit, right? That doubles the read count throughput on the F2. Customers have been, you know, waiting for that. I think that that's gonna be a nice catalyst for demand here in the second half. Then in addition to that, we're on track to, you know, launch our Max Read Kit for single-cell sequencing, you know, kind of late this quarter. You know, we'll, we'll get a full quarter of that, you know, hopefully, in the back part of the year, and that, that as well, will be a nice, nice demand catalyst for us. Thanks. Yeah, love to dig into some of those kits here, later on. Maybe just still, I guess, high level on, you know, some of the manufacturing issues. It's not, you know, any continued, I guess, lingering issues there, supply chain? You know, can you just talk about some of the learnings, just maybe from a manufacturing standpoint, on, on getting up to speed where you guys are actually in that, you know, monthly placement? Yeah. One of the biggest challenges was with an instrument that's as complex as a sequencer, you have a number of vendors that are providing complex subcomponents, things like valves, cameras, objectives, flow sensors, stages. Within all of those, you know, components coming in, a lot of times you're not gonna uncover a one in a 100 failure rate until you've, you know, sequenced or, you know, ran those instruments, you know, hundreds of times to thousands of times. A lot of times, if it's a subcomponent-related issue, you have to go back and work through the vendor to identify, you know, what specifically was it that went wrong with that subcomponent, and that can take time. One of the main, you know, things and the reason that, you know, these things don't fix themselves in weeks or months, or typically quarters, is that that cycle takes time to go back to the vendor, have them do a root cause, work with them, and then further, you have to figure out how you do quality control of incoming new parts to make sure that you've addressed it. Again, when you're talking about a system that has, you know, hundreds of components, a failure rate of one in 100 and one in 1,000, it's only a matter of time where you start to discover these things. That's why you still have these iterative learnings over time. If you look at, you know, Illumina and the way they launched systems early on, you know, their their launches had quite a few bumps along the way. In fact, you know, oftentimes you, you hear anecdotes of launches being 12-18 months behind schedule, over budget, and then typically with an Illumina launch, you still have that hardening time where, you know, 12-18 to 24 months, the system's improving in the field. They call it the green banana, where they used to throw it out there and, you know, the banana ripens in the field. The reality is we're not in a market right now that you can do that. Right now, there's an incumbent that, that has a system that works at a certain level. There's not as much tolerance for, you know, that type of strategy. For us, the bar is higher than it's been for Illumina, yet we're a company that is, you know, lower resourced and trying to get out there as quickly as possible. It's, it's really one of those things where the instrument itself is an incredible design, and it works really, really well. When you're talking about, you know, a really high bar, it's, it's something that is gonna take iterative time to get to. You know, that's probably more color than I've, I've given, but that's just the reality of, you know, kind of how these complex instruments work. You know, again, for the last 12 months or so, we were really, you know, rolling up our sleeves in the trenches, kind of, you know, figuring out all these, these different ways to manage the supply chain better, quality control the parts, do more testing. Right now, we feel like we're really at an inflection point, where we're starting to see a lot of those, you know, that work and those changes reflect in, in, in instruments that we can manufacture quicker. They're more reliable. Again, I think we're, we're, we're just in the precipice of a really fun time of growth as we see all that hard work start to transition into instruments that will meet, meet and exceed customer demand. Yeah, you know, that's really great color, they plan there on that Illumina analogy, too. So it sounds like now that a few quarters in, though, you're starting to see some of that, the instrument perform. The, the customers, you know, they have it on hand now for a couple of quarters. Yeah. I mean, we have, you know, a number of customers. I think we have an updated investor deck that, that will be posted very shortly, if it wasn't last night. You know, customers love the performance of the system. We have, you know, anecdotes and quotes from customers on exceeding specs, higher output than, than what's advertised on the spec sheet, more reads per run. The data quality is equivalent to Illumina and in some cases better. The, the system itself is a really, really powerful system for really good data. The issue has just been: How do we get to the point where we can really scale? The customers, you know, they love the, the profile of the system of data. It really hits a need, which is how do you deliver something that fits in a bench, that gives more power, faster turnaround time, they can run it more frequently? That's core labs, small academic labs, small companies, and eventually clinical labs or hospitals, medical centers. It's, it's rightly designed to fit their exact needs. Customer feedback has been very positive. Of course, there's always some learning and hiccups. Some customers are more, you know, amenable to understand that you have new technologies than others. We've made a lot of strides on where we are right now. Great. I think, Drew, maybe, at 4Q, you guys provided some PAM analysis and outlook for the industry. Maybe just can you remind us where you see the, the, you know, the opportunity there for the G4 and, you know, any changes now? I think it's been two quarters or so since you've provided that. Yeah. You know, just where sequencing is today, you know, roughly $6 billion market. If you look at where those dollars are spent, you know, about half of them are gonna be research or research and translational. About $3 billion. Typically, the profile of the customer is gonna be either academics, core labs, service providers, or, you know, small and medium-sized biotech companies. If you think about the TAM that from a application standpoint, a big part of it is gonna be single cell. Probably $600 million-$800 million is estimated in single cell. There's gonna be in the research side, again, an equal size, maybe a little bigger in target panels. There's a long tail of other things like RNA-seq, CRISPR sequencing, Olink. Where we specifically see a beachhead within the academic, which are typically the earlier adopters, we'll get to clinical in a second, is in applications where we have something unique to offer, namely single-cell and Max Read. Our Max Read Kit will do, you know, 800 million to 1 billion reads per flow cell. We're just throwing out numbers, but basically, it's four samples from a 10x kit in a single flow cell. We have 4 flow cells, 16 samples in a single run. That's very unique. It doesn't exist out there unless you go to a NovaSeq to get that scale and that price point. For us, in the academic setting, somebody can buy, you know, a $1 million NovaSeq as a core, but they still have to, you know, fill up, you know, 50 samples to get a certain price point. If they can put a G4 and they can do 16 samples overnight at the same price point, it really hits a, a sweet spot. That's one of our application beachheads, and then, you know, shortly behind that is another Max Read Kit for general RNA-Seq, which should also provide a very kind of unique offering. On the clinical side, that's really not where we're focused today, but it's where we'll be focused next year and beyond that. The clinical side, vast majority is target panels. There's a trend to go higher throughput, meaning more, more targets within the panel, potentially whole exome. There are some clinical applications doing whole genome. Anything with a biopsy is gonna do really, you know, depth of sequencing on, on certain targets. You need your system to be established. You need to have, you know, quality control systems, QMS systems. You need to be at a certain level of maturity of the business before you're gonna go in and do patient, you know, critical samples in a clinical environment. That's something we're largely focused on since we think the G4 fits really well for a lot of those applications, especially if you're thinking about a decentralized environment, like a academic medical center or hospital lab, where they're gonna have varying sample volumes at different points in time. They're gonna wanna run the samples fast and cost-effectively. That's very much something that we would, you know, take step-wise, putting the foundation in place, but it's probably a next year customer segment in the second half that we really start to, to be ready to serve. No, that's, that's helpful color and kind of leads into to my next question. Just on that backlog and sales funnel, it sounds like you're having, you know, the most success early with the academic customers. Maybe just talk a little more that, you know, that near-term opportunity, you know, where you see these academic users, you know, using the G4 in their different research. Yeah. The, the funnel is probably two-thirds academic right now. Then a third would be kind of the other category, which actually does have some clinical players, whether it's a, it's a central lab or a small company developing a clinical. On the academic side, I, I think the, the applications are pretty clear. You know, there's. Again, one of the benefits of G4 is you can run all types of sequencing on it. It's compatible with all of the applications and ecosystem, but specifically in academia, we're seeing a lot of single cell. We're starting to see some single cell that's not 10x based. Doing the, the instrument-free single cell. There are companies like Parse and Fluent and others, we're starting to see a little bit of that. We're seeing an increasing amount of CRISPR screening and CRISPR readout sequencing. That's been kind of an area of growth, although still small compared to single cell. We see a good amount of RNA sequencing. There's various types of RNA-Seq kits. The academics, I don't see a ton of it, but there's some, you know, exome and targeted panels. Most of it is gonna be around RNA, single cell, CRISPR, Olink's growing as well. Those are really the application tests that, that we're seeing in the academic segment. That's helpful. Then I guess, you know, when you think about the, the competitive environment, you know, obviously there's a very large incumbent in Illumina, but also you have other some emerging players, new technology coming in. Just, you know, how do you see yourself when you're competing head-to-head versus peers? You know, where are you winning? Where, what are your learnings there in the overall environment? Yeah, the, the academic core lab segment, we feel that there's a, there's a really good win for us. We feel like we're winning there. The speed and the flexibility fits right, right in with how a core wants to run. A lot of times, cores are actually selling individual flow cells or individual lanes. The fact that we have foufour lanes on a flow cell and four flow cells allows the core to go to their PIs or their customers and say, "You can buy a single lane that doesn't get mixed or batched with other samples for as low as $200." The equivalent is on a NextSeq right now, there's no individual lanes, there's 1 flow cell. The smallest bite size that you can sell on a NextSeq is about $1,800. It's just. It's different. I mean, the user has to provide more sequencing to fill up that flow cell, or they're trying to figure out how they can batch samples across multiple experiments to submit a single order, or the lab is frankly just running it at, at, at, you know, not full capacity. That flexibility, specifically for the cores, provides a really nice value proposition that they can then pass on to their customers. The speed, the flexibility, and the throughput, again, those are all just, you know, nice pieces of, of, kind of value within that more flexible format. I don't know if I can. Do you have anything to add, Dalen? Yeah, Drew mentioned the new investor deck. We have some nice customer quotes in there, at least one of them, you know, touches on this. If you think about the core lab's workflow, you know, they have a bunch of different PIs coming in with different experiments, different sample sizes, different deadlines. You know, the ability for them to really customize the, the size of the run and get it back in less than a day, so quick turnarounds, is just very appealing for them. You know, you did talk about that, you know, utilizing the full flow cell, and I guess, you know, how often does pricing come up in these conversations? If you look, you know, any metrics you could share on where that pricing is, maybe with underutilizing flow cell versus some of the pricing coming from, from the emerging competitors or even, you know, where could Illumina go on, on the XLEAP-SBS, on NextSeq? You know, pricing is a really interesting topic because I think we're in a bit of a time right now where the market's a little bit irrational in trying to figure out what's what. What I mean by that is typically, in a rational market, Illumina had their pricing very cleanly segmented based on, you know, kind of the instrument and the level of throughput and amount of data you were getting. Meaning that the NextSeq kind of had a pricing per gigabase that started around $15 per gig and went up to $40 per gig, depending on how big the flow cell was. Then if you looked at the NovaSeq, it was around $6 a gig and went up right to around $18 a gig. There's only a little bit of overlap there on the low end of the NovaSeq and the high end of the NextSeq. What we're seeing. Our strategy from the beginning has been not to use price as the ultimate lever to compete, to use the speed and the flexibility and cost savings through more efficient run of flow cells, cost savings through the fact that we can offer a Max Read flow cell that's tremendously more throughput on a single kit, so therefore, we sell the high kit ASP, but the actual cost per reader, cost per experiment is going down. What we're seeing in the market is price is now something that customers are able to use as leverage if they have a choice of vendor. We are seeing Illumina discount the cost of the instrument. We haven't seen them discount reagents, and we've seen other new entrants get very aggressive on pricing to a point where, where some are just giving away instruments for free, which is, again, a little bit irrational because I don't think there's a sustainable business there. What we come back to is trying to sell on the merits of the system. We have a, a, a system that from a pure KPI standpoint, if you look at buying a NextSeq or our, our system, you're gonna see a lot of value in how much it costs to run it, and how quickly you can get your experiments back. You're also gonna see cost in the fact that you're getting into the low end of the NovaSeq on your throughput for the MaxRead application. There could be a huge cost saving if you're alleviating the need to buy a NovaSeq. For a lot of customers, they don't look at only price. They're looking at what's the complete value of the system, how does it fit with my work? Some customers are using price as a lever, and they'll just drive it down, and they'll make a decision based on whoever is the lowest price. Just being candid, that's kind of where the market is right now. I think unsustainable business practices are exactly that, they're unsustainable. If you're giving away systems, you're not gonna have a business. I think now you've placed a couple leases or reagent rental instruments. Can you just remind us how many placements there, and just kind of what is the demand you're seeing for that versus an instrument purchase? Yeah. Yeah, I can take that. I think we talked on the last earnings call, about a third of the opportunities right now that we're looking at are, you know, kind of in that other bucket, you know, not a traditional capital sale model. That's what we've seen. You know, we've got a small end count out there, but, you know, those are the opportunities we're looking at. Just as a reminder on that, you know, every one of these that we, you know, try to structure, a flexible model, it's, it's based around customer need. Ultimately, there's, you know, an economic. ... return to the organization somewhere down the line, whether that's through consumable uplift or, you know, purchase of the instrument straight up, down, you know, down the line at some point. That's really the way we're looking at it. We're giving our sales team the flexibility to do what they need to do for customers based on their needs, and we're seeing about a third. I guess, you know, with that third opportunity, I guess, you know, how are you doing that? You know, could that, you think, help accelerate overall placements if you're just getting more instruments out there, people are using it, word of mouth? I guess, how does that fit into this, maybe the overall strategy you're, you're thinking? Well, I, I think there's. I don't know if the categories four or five, if one of them kind of blend. There's just, you wanna have a menu of how do you get a customer a system that makes sense from a business standpoint. The first one that, of course, you would prefer is a capital purchase. They buy an instrument, and they use it. The second one, we offer a lease option, where a third party will actually, you know, put that company onto a payment plan. They're leasing the instrument, and, you know, we receive the capital upfront, which again, from our standpoint, is almost as good as number one. The third one is the traditional reagent rental model that comes with a set annual minimums of reagents, and the reagents are priced on an uplift so that you recoup the value of the equipment over a three to five year time period. The nice part about the reagent rental for us and for the customer is it's zero money out of pocket, the way we price a lot of our flow cells on the kits where we win, we're still gonna be cheaper or around the same as a NextSeq would be to run just natively. For a customer, if you can go in and say, "Hey, you know, our $8 per gig F3 flow cell on a reagent rental is, you know, $12 or $13 per gig, and it's still, you know, cheaper than the $15 on your NextSeq," that's pretty compelling. Now, for us, we don't receive the capital upfront, but the uplift in reagents over time obviously is, is where we're making the money there. Then the kind of other options that you would have would be, you know, something that's more like a, a strategic placement with a KOL, where there's a conditional PO where they would convert in, but you describe value, that KOL speaking on your behalf or acting as a reference site. Those are kind of the different flavors that we have, although that last bucket we try and use very selectively to make sure that we don't fall into the comment I made a few minutes ago, which is if you just start giving away systems for free, people expect it. It's not sustainable. You have to be very thoughtful about what value you're getting if you're going to make a placement strategically in terms of, you know, all the different, you know, factors that that creates. Just on that last point, maybe one additional clarification. You know, have you noticed any changes on that? Are you getting maybe more aggressive on placing instruments over the last quarter or so, or two quarters or so, maybe even just given some of the budgets or macro environment? Has that changed at all, on like where competitors are, are there? On the academic side, we haven't really seen much of a slowdown in the budget. I, I should go educate myself. I believe the NIH budget is still being reviewed, hasn't been approved, but the submission was around the same $50 or so billion as last year. From what we hear, most academics feel like they, their budgets are in place, and they're still spending on their research. Where we've seen a pretty substantial slowdown is in the private side. You know, we used to have a lot of interest, and the interest is still there, but I would say maybe the conversion of interest or the part on that kind of four factor qualification of, you know, budget and time to buy, on the small, medium-sized biotech companies has, has changed. Just like us and others, I think most companies right now are trying to, you know, hunker down and, you know, minimize expense and cost and kind of improve the, the operating margins of their business, and that makes, you know, spending money on new capital equipment not one of the, you know, the top priorities. If you move into the, the medium or larger sized companies, you know, companies like the Adaptives and the Terras and Invitae, those guys are actually thinking about it the same way as well. Whereas two or three years ago, you know, they were very open to a conversation on how do we start to supplement our sequencing fleet, or how do we start to look to get away from Illumina? That interest is still there, but they'll candidly tell you, "That's, like, the tenth thing on my priority list right now. I'm trying to get, you know, a more profitable business. My ETS is an issue. I'm trying to cut burn. I'm..." The, the state of the market right now is, is just very different than it was a while ago. Thankfully, the academics in place, and it's a very strong segment, and there's a lot of money spent there on sequencing and multiomics, and that's an area where we're seeing traction. It also happens to be the, the right area, where you, you launch a new technology. You don't go to the, the clinical companies right out of the gate, kind of like I, like I mentioned. That's kind of a little bit, I think, what we're, what we're seeing kind of on the, on the macro level, in terms of, of budgeting. I guess just, you know, maybe on, on the sales cycle, any way to quantify just, you know, the lead times and how long the sales process is in place? Just kind of run through on that a little bit. Yeah, I'd say the sales cycles are longer than, than we anticipated. I think part of it has to do with the competition in the market. I think part of it has to do with, you know, customers realizing that if they have a choice, they can kind of negotiate longer. You know, I think we would say a typical sales cycle from something entering into the funnel, if we don't think it has a chance to close within 12 months, it's an unqualified lead. There have been a few that have come through much quicker, and I think as we get the system established and we really, you know, get the thing to the point where people know it's, it's, it's out there, and it works really well, we're still very early in that. I think we'll, we'll start to see quicker and accelerated kind of lead time in the funnel. I think the big question for a lot of customers in our funnel is still: How do I make sure I'm buying something that's a good purchase? You know, a company like us that, you know, is early into a launch, and has been delayed, I think people are gonna wanna make sure that, that the system is where it needs to be. You know, we're making a ton of progress there, and it's trending in the right direction, but I think that's, you know, that's really the big, the big thing that people are waiting for. You have your early adopters, and then when you want mass adoption, there are a certain set of criteria that need to, you know, boxes that need to be checked before somebody's gonna spend $300,000 on a piece of equipment. That's really what we're working on: How do we gain the trust of the customers? How do we get it established? How do we get natural word of mouth to start permeating the industry and the space? You know, the systems work, they're solid. We got them out there. They're performing as intended. That's the big, you know, effort right now, is how we kind of get our reputation to a point where people are ready to step in and buy quickly. Maybe last question before I turn it to Liza. Just on, on that, you know, say, 12 months sales process, you know, just to look at last quarter or so or two quarters with macro environment, you know, any way to quantify maybe that's been elongated a little bit or how that's been tracking? I mean, I think in, in general, it has been elongated. I think it's macro environment. I think it, it, it's also kind of again, the, the, the current state of the market. People are trying to figure out what's, what's what. I will say we've seen the, the funnel drastically increase over the last six months. At the end of last year, we had less than 50 qualified leads in our sales funnel. Now we have over 200, and we, we, we added more the last quarter than, you know, than where we were at the end of Q1 combined. It, it's been a, a really nice leading indicator on getting quality people in the funnel, starting to have real conversations, solution selling with them. You know, most of these customers, if you understand how a sequencing cell works and an expensive piece of capital equipment, you have to really engage with these customers. You have to understand, well, how do you plan to use the instrument? What type of kits do you need to run? What's your-- what are your current costs? How frequently are you running? Then, you know, we have to paint a picture back to them of, "Well, if you adopt the G4, here's how we're going to save you money, or here's how we're going to save you turnaround time, or here's what it's going to do for your lab." That takes time. It's an iteration. The next step beyond that is testing samples. Not all customers want samples tested, but some say, "We want to send you samples and test it." Some ask for references. That's the next stage. Once you get to the bottom, typically you get to a point where people have made a decision, and then it has to go through whatever, you know, processes there, whether it's academic or a private company, which is a kind of another set of gates that takes, you know, days to weeks to get through the, the proper channel to actually get the CO issued and then take the system. That's kind of the way the process works, but the leading indicator is just the one that's trending really in the, in the right direction with the, top to mid-size. This funnel never have been as full as it is right now, so we're, we're really kind of excited for the next couple quarters. Thanks, John. I appreciate that this is pretty early stage, but, I do believe you have made some placements in critical clinical customers. It would be great to kind of dive in there a little bit to kind of get a sense of, you know, what maybe some of the clinical customers are starting to do, what applications they're thinking about, and how they're kind of they're utilizing your instrument. you know, how you think about the opportunity. You mentioned liquid biopsy, how big that could be for you and, you know, maybe that's a five-year kind of target, but it would be great to kind of dive into that. Yeah, I think we, we, we have one clinical customer, but I think. Let me provide a little color around, you know, these clinical customers. Some well-funded clinical labs, they have a research group, and they have sequencing that's done with patient samples. They have sequencing that they're doing, that they're doing research to supplement the, kind of the patient work that they're doing. That's where one of our, our clinical customers fit. It's in the research arm of a, a large and well-funded, well-known, leading cancer research lab and clinical diagnostics lab in the US. For them, they want to bring this G4 into routine clinical use. They're working with us largely as a, as a partnership of sorts, to work through the system, to understand how it works, to understand the error profiles. They would love to put it into their clinical fleet as soon as it's ready. We're working with them with kind of really open communication to figure out, you know, when's the right time to do that. I, like I said, it's probably sometime in the second half of next year. There are other labs that are clinical labs that have similar research groups. The types of applications that this lab happens to be doing is targeted panels, small, medium, and large targeted panels, and that's exactly what they want to use the system for. I think there's also a clinical fit for NICU testing. Now, NICU testing is done largely centralized at Rady Children's Hospital. I think they're serving 30-40 hospitals around the country, but there's also maybe 12 to 24 hospitals that are bringing NICU in-house. What, what does it mean to bring NICU in-house? The hardest part of NICU is the interpretation and making a diagnosis, that's where Stephen Kingsmore and his lab have really, you know, kind of created a unique offering there. In terms of the speed of sequencing and in terms of the requirements, typically, you're sequencing a baby, the mother, and the father, and there might be a control. Our system is perfectly suited for that. It's literally an F3 flow cell, 120 gigs. That's a whole human genome at 30X coverage. You could do both parents and the baby on three flow cells, and if there's a control, you have the fourth, and it's overnight. It's a perfect solution for the G4, and we've had interest in that. That's, again, not something you run to. Just talking about clinical applications where, again, there are time dependency to the results, you want to keep it on site, not lose time. That is an area that we're interested in, but you have to find places that are well funded enough to take on the analytics and tertiary analysis part to make a natural diagnosis. That's an area where, again, we have limited resources. It's really partnering with the establishment, and it's a, it's a bigger lift, so it's something that's probably longer term for us, but an area that we think is really interesting from an application perspective. From the decentralized clinical applications, I don't know if I really answered your question. Targeted panels are, are obviously one. NICU would be a little bit further out, and then there's a few other places that we see a time dependency where you would want to do sequencing in the hospital, lab, or the academic medical center, if you could. One would be if you're doing tissue dissection and you want to go ahead and sequence kind of, you know, cancer-relevant information. When you have the tissue open in the patient in the lab, that would be a time-critical type of sequencing. Another would be if you're doing an organ transplant and you want to do HLA typing. That would be another time-critical type of sequencing that you wouldn't want to send out, and there are a few others as well. If you're doing treatment selection and you want to quickly pivot or understand the way the treatment's working on an oncology patient, you don't want to wait, you know, weeks if there's a treatment that's not working. You want to be able to understand that quickly, make the decision. Pivot to a different line of treatment. There are a ton of applications, but these are, these are very nuanced, you know, specific applications that is not something an early company is gonna go after. This is something we'll start to partner and understand it, and really next year, we'll start to try and think about how we, we penetrate that market. Great. Super helpful. It sounds like probably when you're thinking about this, this would be something, you know, clinical is more in the five year, to have like a strong clinical customer base. Any thoughts around kind of where that could go eventually for, for Singular? Well, I think we, we look at Ion Torrent and Thermo Fisher as a good example of somebody that's been successful in the clinical sequencing almost exclusively so. If you look at, you know, that solution, they've basically taken what is a, a, admittedly, a handicapped sequencer in the fact that it's very low throughput, and there's an accuracy profile issue. They have wrapped around a complete workflow that's easy to use, that's fast. It does, you know, 28 genes. They have three reimbursable targets in that panel. They get $1,900 for each one of those targets. They have gone after three of the largest, you know, cancer opportunities through a targeted panel and complete workflow, and they have a, a really profitable business that people don't really realize. I think for us, we look at that and we say: You know, we have a very similar profile system. The Ion Torrent is four lanes, and it's a one chip. We have four lanes with four flow cells, so it's kind of a higher throughput, more accurate solution. How do you wrap in a workflow around that, make it easy to use, and then the informatics and reimbursement part is a whole another story. I think that's a really good example of how you can win in the clinic, and it's a $600 million-$700 million business that's growing faster than Illumina's business, and people don't talk about it because they, you know, it's not in the academic and the KOLs. It's a real business that's operating quietly in hospital labs. Cost, ease of use, complete end-to-end solution. Those three things are how you get sticky in the hospital lab longer term. Really great color. I'll ask one more, and then I'm sure John will wanna go to PX. You did mention the F3, F3 and Max Read flow cell kits. It would be great to just kind of get customer feedback on the kits and kind of what you're seeing there. Maybe add a little to that. Yeah. I mean, the F3 is, it doubles the throughput. It's pretty straightforward. You get double the amount of reads. The cost per gigabase, cost per read goes down. You open up a different application set. Yeah, that's kind of your, your bread and butter, higher throughput. It kind of would compete with the P3 flow cell on the NextSeq. We have four of them, it's, you know, about four times more powerful than the NextSeq, four times more throughput. If you think about the MaxRead, that's a specific kit that's built and designed for an application. It requires us to do that. The first one is single cell. Single cell actually is, you know, four or five different kits within the 10x lineup. You have a couple different Chromium and a couple different Visium kits. You know, that is gonna be a large market and a big beachhead for us because the academic community is doing a ton of single cell. That one should, should really push us to, you know, push adoption within that kind of core market segment. That, that's really the color on the two kits. Beyond the Max Read Kit for single cell, we haven't publicly announced where we would go next with that kit, but it's amenable to any type of sequencing that's short read, less than 100 bases. Some of the ideas out there that, that we're considering on the product roadmap would be kind of Olink. If you're doing a, a sequencing readout, and you're only doing 50 or 60 bases from a, a protein tag, that could be a, a nice high throughput way on a benchtop instrument. There's also increasing, you know, work being done there in, in these target customer segments, although it's not a huge market yet. It's probably $30 million in sequencing, $40 million, maybe something like that, at the most. Another application kit would be general RNA-Seq. That's, you know, there's probably 24 different RNA, you know, kit providers out there, but there's a way we could offer a conversion kit and make that amenable to MaxReads, and that serves a, a large market. There's a few other, you know, kind of applications. One clinical application that we're really interested in, that we would love to advance through partnership, would be something like looking at NIPS, non-invasive prenatal screening or testing. The reason that one would, would be really nice is, you only need 50, 60, 70 bases, depending on the counting application library prep you're using. It would allow us to go after a, a clinical application that doesn't have really the time dependence or the critical nature of a, of a patient, the same way you would in a hospital sensor, center with cancer diagnosis, but gives us kind of a large market that we could differentiate in from Illumina. There also may or may not be a royalty issue, that some customers that do NIPS right now still have to pay to Illumina if they're using an Illumina sequencer to do NIPS. There's, again, maybe an incentive above and beyond just a better, faster, cheaper sequencer if you could alleviate a, a royalty that, that, that is meaningful. That's again, a, a medium to longer term application, but one that you would ideally advance your partnership with somebody that has a large volume of NIPS testing, has their own library prep and workflow, and you can create a value proposition that says, "Hey, very clearly, I'm gonna save you X amount of dollars and cents, and there's no risk on, on the tax," since it's a very easy counting application, and you just swap them in over time. That's something we're excited about. Great. A little bit building on that, we have a question in the audience, and you talked about some of the content that... You know, with content being a major driver in the purchasing decision for end users, you know, what is Singular doing to bring unique and purposeful content to the G4? I guess, you know, where do you really see, you know, separating yourselves from some of the competition out there? You know, it's a great question, and maybe I'll start at the 40,000-foot and then go down to the practical reality of where, where we are and where the market is. At the 40,000-foot level, I think content is gonna be critical to win in sequencing longer term. Content and the complete workflow, because it, it provides a barrier of moat where you're not competing on cost per read or cost per gigabase. You're offering a complete end-to-end solution that does something content specific, that's unique. You kind of take pricing out of the, out of the equation. You're also vertically integrating, so you're not having two or three people taking, you know, dollars in profit out of the customer wallet. You're optimizing the entire spend based on a single vendor, if you're able to, you know, integrate the content up front on the bioinformatics. There's, there's all types of reasons why at 40,000 feet, it makes a ton of sense. We've talked about two or three different kits that have very unique content over the years, and I can go into each one in as much detail as, as, as we want, if we have time. One with HD-Seq, which we think is very unique in, in cell-free DNA applications. It's the way that you actually link together dual-stranded DNA at the very beginning before you denature it and start your library prep. The idea behind it is, if you sequence and figure out how you can sequence through dual-stranded DNA, you have a built-in error check. Instead of going ahead and reading single fragments at the end, realigning them and trying to pick out error through depth of coverage or UMIs, you can actually look at both strands and say, "Did you see a, a variant on both strands, or was it an error or DNA damage or something else that happened?" We think that has a ton of clinical utility in all applications where you need super rare variant detection, a part in 10 million, especially if you're looking at fragmented DNA, like cell-free DNA in, for liquid biopsy. Now, what does it take to practically move something like that forward? It takes a team of X amount of people to really do the work, clinically validate it, get patient samples. It's a big lift. You don't just develop kits like this with, with a two or three-person team as a side project when you're a lean company with 250 people. It's something that we've put on the shelf that we're trying to go ahead and find someone to partner with. Again, this environment right now, partnerships and getting dollars out of big companies is not on the top five things in their priority list. I think we'll be able to advance it at some point. We haven't yet. another example is Ring- Seq, which is a poster that we've, you know, put online, which is a fusion detection library prep kit. It's the, the same thing I just mentioned. Showing a proof of concept, showing a paper, showing it can work once is very different than developing a full kit and product and bringing that to market, and these are the types of things that right now we would need to advance through partnerships, since we've gone lean. We've reduced headcount, and we're ultimately focused on getting the product robust, getting the F3 out, getting the Max Read Kit out. That's where I come back to the one application we did decide was warranted to put resources on, a Max Read Kit for single cell, right within our target market. It's not a clinical application. Researchers use it. Single cell is a big market segment for us, and that is a specific application that's not maybe the same way you would think of content as HD-Seq but it's a specific kit that gives us a unique advantage to, to offer single-cell sequencing on the G4. A long-winded way of saying we're thinking day in and day out about the content, and we've also thought about acquiring content inorganically. It's just, you know, it's a challenge when, you know, your, your, your, your company feels like you, you still need to go establish yourself. We need to get our market cap back up. We need to get some momentum going. Once we're in a place of strength, I think there'll be opportunities that we can act on, both through partnership and through, through M&A. Right now, it's just focus, focus, focus. Get the G4 out, get the F3 out, get the Max Read Kit out, get it reliable, build the customer base, and then grow from there. No, it's, it's a great overview on the content. I guess just maybe wrapping up here on, on the G4, you know, any color? I know it's early days, but how you can see pull through there, you know, how is that translating into, you know, users actually having the instrument? Yeah. Most of the customers, you know, in, in the 11 that we have out there are academic in nature, right? I think what we're finding is it just takes time for them to, you know, coordinate, you know, samples, experiments, projects, and so it's taking a little bit longer to ramp up the pull-through. It's still, you know, really early. I think, you know, you know, quarter to or year to date here, we have, roughly about $100,000 in consumable revenue. You know, we expect that to ramp in the second half, especially with the F3 and the Max Read kits that, that, that'll be out. It's gonna take a little bit of time to kind of ramp up to really that, you know, more, you know, kind of at-scale, annualized pull-through. Just as a reminder, you know, Drew mentioned this, but, you know, one G4 from a throughput perspective can do anywhere from, you know, 2x-4x what a NextSeq can do. Pull-through potential is really good. It's gonna take us some time to get there, and we should, you know, kind of see that profile change as, as customers move from kind of more academic into, you know, kind of the commercial, commercial side of the house as well. Thanks. You know, I think you recently made some sales hires in the U.K. Maybe just any color on just, you know, where you see the ex-U.S., maybe EU, U.K. opportunity for the G4? Yeah, we, we've, you know, we go to a number of major trade shows, and conferences, and we've had a ton of inbound, unsolicited interest from kind of the European market. That market by nature is gonna be more decentralized than, than the market here. Fewer NovaSeq and fewer power users, a lot more mid-throughput sequencers, mid-size labs, just much more decentralized in general. The G4 fits perfectly with that market, and that's the, the feedback we've heard, and there's been kind of a pull for us to go to Europe. When you think about setting up, you know, you know, EU or, or other, you know, non-US areas, it does take investment, and it takes time. You know, getting, you know, a, a general manager of Europe, that was the first step to put a foundation in place to hopefully be, you know, ready to serve that market in about six months. Getting your, your field application scientists hired locally, your service engineers hired locally, getting them trained, making sure that if you do enter the market, you're prepared to support your customers, and you have the infrastructure. It's, it's, it's vital, because you can't enter a market if you're not fully, you know, committed to, to investing in it. We're making that investment now, early, in a modest way. We'll build it out over the next six months, and we expect Europe to be a, a really nice market for the G4, given kind of the, the nature of that market. That's kind of where we are there. I wanted to touch here on the PX a little bit near the end. You know, can you just give us a overview of the PX platform and maybe even just touch some on the IP there? You know, there's been a lot of discussion on IP in the spatial industry, given some of the ongoing litigation there, but it'd be great to hear about, you know, patents in place and, and, and that piece, too. Yeah, the, the, the PX is something that we are really excited about because it's, it's just very unique. Just as a reminder, the PX is a system where we are doing spatial sequencing. Nobody else does spatial sequencing. People use fluorescent probes, they use antibodies, they use dyes to go ahead and do spatial analysis, spatial profiling. They're not natively sequencing inside of the cell. That's our big differentiator with the PX. Why is that important? It's important for a few reasons. The first is you're able to unlock a different type of information. If you're actually able to go in and find RNA, transcribe it to DNA and amplify it and sequence 50, 60 or 70 bases in the cell, you're providing information that, that doesn't exist. You're not just looking at a binary transcript that's there. It's not there. You're able to look at SNPs, insertions, deletions, and actually look at genes inside the cell in a different way than you are with the probes. The second reason it's important is if you think about using that DNA, as a barcode on an antibody, to then provide protein information in addition to your sequencing information, you have very fast cycle times with sequencing. If you're looking at hybridizing and washing and repeating, and you're limited by five or six dyes as in other methods, you know, that's why you see, you know, other companies that have two-day to seven-day workflows to do two samples and a few hundred to 1,000 targets. It just takes a lot of time to cycle. Sequencing is very fast, around five to eight-minute cycle time versus 30 minutes to, to hours. Then the last reason the PX is unique is, you know, our imaging system is very, very high powered. It's down to, you know, submicron resolution and images that are over 1 billion pixels per second. If you just look at the raw imaging power of speed and resolution, it's a notch above or two than anything else out there in the spatial field, given that combination. Why is that important? Well, it translates to throughput. Other systems will offer one or two samples. One of the biggest pain points we hear in the spatial side is that it costs too much, and the throughput's very low. The PX should be able to do 10-30 samples in a single run. Part of what we're trying to figure out is, again, being lean, how do we advance this to a product? We've made really hard decisions and decided where we don't invest in other areas. The PX is one where we think it is so high value and there's so much synergy between the optical system and the chemistry, that there is a continued dedicated effort on it that we are advancing internally, and we plan to share more about that in the first half of next year. That, that's kind of what we're going to... We don't have We don't have much time. Yeah, may-maybe just, you know, at the very end, asking you, so next year, early half next year, get more updates. I think there's also a TAP program, an early access program, happening second half this year. Just anyway, what's the color? Happening right now, yes. The two, two leading academic KOLs that are using, you know, spatial sequencing to do something that they're not able to do with other platforms, and we're working with them, bringing their samples in, collaborating on the nature of the assays. We hope to have data and, and, and papers to share on that at the beginning of next year. Those are, you know, two, two examples of, of your audience. We had, you know, over a dozen people that wanted to be part of the TAP. It takes resources, so we had to kind of down select to a couple. We might extend it to a third, but, you know, those are ongoing, and we should have some exciting stuff to share about that in the next few months. Great. Well, with that, we're right at time. Drew and Damon, thank you very much for being here today, and thank you, everyone, for listening in. Thanks for having us. Thank you.