This conference call transcript was computer generated and almost certianly contains errors. This transcript is provided for information purposes only.EarningsCall, LLC makes no representation about the accuracy of the aforementioned transcript, and you are cautioned not to place undue reliance on the information provided by the transcript.
spk08: Greetings and welcome to the Singular Genomics Systems Incorporated fourth quarter 2022 earnings conference call. At this time, all participants are in a listen-only mode and a question and answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. Please note this conference is being recorded. I will now turn the conference over to your host, Mr. Philip Taylor. Sir, you may begin.
spk06: Thank you, operator. Presenting today are Singular Genomics founder and chief executive officer, Drew Svobenta, and chief financial officer, Dalen Meter. Earlier today, Singular Genomics released financial results for the three months ended December 31st, 2022. A copy of the press release is available on the company's website. Before we begin, I would like to inform you that comments and responses to your questions during today's call reflects management's views as of today, March 2, 2023 only, and will include forward-looking statements and opinion statements, including predictions, estimates, plans, expectations, and other information related to our financial and operating results, plans, and strategies. Actual results may differ materially from those expressed or implied by these statements as a result of certain risks and uncertainties. These risks and uncertainties are more fully described in our press release issued earlier today and in our filings with the Securities and Exchange Commission, including our most recent Form 10-K or 10-Q and the Form 8-K filed with today's press release. Our SEC filings can be found on our website or on the SEC's website. Investors are cautioned not to place undue reliance on forward-looking statements. We disclaim any obligation to update or revise these forward-looking statements. Please note that this conference call will be available for audio replay on our website at singulargenomics.com on the events page of the news and events section on our investors page. With that, I will turn the call over to CEO Drew Spaventa.
spk07: Good afternoon and welcome to Singular Genomics fourth quarter 2022 earnings call. We are pleased to update you on a very important and productive quarter as well as a milestone year for our company. We will focus on three key areas. First, business highlights and key accomplishments from 2022. Second, new data and product announcements. And third, the 2023 pillars of success. Starting with business highlights from 2022, first and foremost, we delivered our first quarterly revenue as we brought the G4 to market and shipped five instruments to customers, a key company goal and a major milestone achievement. Initial customers spanned a variety of market segments, including academic core labs, a commercial lab, and a hospital research lab. Feedback from customers has been positive, and the value proposition is resonating. Three of our five initial shipments were to academic core labs, including Harvard's Beth Israel Deaconess Medical Center, the Medical College of Wisconsin, and the University of New Mexico. At Harvard, the flexibility and speed of the G4 has been a key in allowing them to utilize a single instrument to run single-cell and spatial experiments with varying sample volumes and output requirements. At the Medical College of Wisconsin, the team has been impressed with the high quality of the sequencing data and single-day turnaround times. At the University of New Mexico, the flexibility of the G4 is ideally suited to address their diversity of applications. It is exciting that our initial customers have been able to demonstrate the G4's industry-leading combination of power, speed, flexibility, and accuracy. To achieve this important commercial milestone in Q4, our team addressed the challenges experienced with scaling manufacturing supply chain we discussed mid last year. The team moved swiftly to qualify alternative suppliers, redesigned certain components that have long lead times, implemented supplemental QC testing to ensure complex sub-components from suppliers and meeting specifications and reliability metrics, and advanced our final assembly, integration, and testing of instruments. The end result ultimately reduced the time required to build and bring up a G4 system by 25%. In addition to achieving our G4 shipment goals, we had several other key accomplishments for the year to note. We continued to build out a North American sales team with nine key territories to continue driving demand and growing the funnel of leads and opportunities. We expanded our marketing presence at 14 industry trade conferences and talks, including ASHG, AGBT, AMP, and PMWC, increasing our brand awareness and communicating the value proposition of the G4. We signed partnerships with 12 library prep and analysis partners, bringing the total as of year end to 18. This is designed to remove barriers to adoption of the G4 and facilitate a seamless integration into existing library prep workflows and data analysis pipelines. In operations, we successfully completed an ISO 9001 audit of our dedicated manufacturing facility and commissioned state-of-the-art clean rooms and lab space for scaling production of enzymes, nucleotides, flow cells, and reagents. We've progressed R&D work on our G4 instrument and consumables roadmap to bring improved flow cell specs and new kits to market. Lastly, we've progressed to PX, our second system in our product development pipeline. This system is developing the capabilities and methods for high-throughput in-situ spatial and single-cell analysis. building several prototype systems during the year, and more recently, signing our first partner for the technology access program. All of these accomplishments play an important role in establishing a foundation for cross-functional success going forward. I want to thank the entire team at Singular for their amazing contributions made in 2022. Turning to new data and product announcements, it was all on display at the AGBT conference in early February. We hosted a successful customer and KOL event with over 60 lab directors and scientific leaders in attendance. The event provided an opportunity to develop relationships, solicit feedback on the value proposition of the G4, generate new leads, and drive opportunities forward. We presented 14 new datasets, 11 with industry-leading genomics partners, collectively showcasing high accuracy of the G4 system across many diverse applications, including single-cell sequencing, whole genome sequencing, and somatic whole exome sequencing. These data sets reinforce the G4's ability to fit into a robust and diverse set of workflows, putting the G4's speed, flexibility, accuracy, and power on display. We launched our MaxRead kits for single-cell sequencing with enthusiastic customer response. The MaxRead single-cell kit will allow users to get up to 800 million reads per flow cell or 3.2 billion reads per run at the low cost of $200 per sample for $1 per million reads. MaxReads provides a novel method to achieve Novaseq-level pricing for single-cell sequencing on a benchtop system. The flexibility of the G-Force for flow cells allows users to scale their run up or down based on sample volume at the same favorable economics. We intend to begin shipments in the second quarter. In addition, we were pleased to announce that Singular joined the 10X Genomics Compatible Partner Program, demonstrating the G-Force compatibility with the 10X Genomics Chromium single cell platform. The flexibility of the G4's four flow cells and four independent lanes matches precisely with the most widely used sample configurations on 10X's Genomics Chromium runs, providing an efficient way to optimize run sizes for single cell experiments. And lastly, we improved the specifications of the G4 F2 and F3 flow cells for both accuracy and read counts. Accuracy was raised to 80% to 90% greater than or equal to Q30. The throughput range of the F2 and F3 flow cells was increased up to 250 million and up to 450 million reads, respectively. All data sets and product specifications are posted on our website, and we encourage you to visit and see for yourself. The third topic I'd like to talk about today is how we are thinking about success this year, the 2023 four pillars of success. First, commercial execution. This means executing on and measuring the following key items, G4 system placements, reagent pull-through, and customer satisfaction. We have a good start with initial G4 placements in the field, customers starting to sequence, and we're receiving positive feedback and beginning to collect the data to set and deliver on each of these metrics. Second, G4 TAM quantification. This means establishing G4 product market fit in specific market segments, applications, and customer types with the goal of credibly framing the G4 TAM and measuring our progress in capturing market share. Third, operational excellence. This encompasses goals in the manufacturing side where we have objectives to improve supply chain, manufacturing efficiency, quality, and system performance and reliability. While challenges were overcome and progress was made on supply chain and manufacturing in 2022, this is a key area of continued focus with scale-up this year. Fourth, innovation and product pipeline. We have an exciting pipeline of innovations, including improvements in performance and specs on the G4 platform, new reagent kits offering higher throughput, higher accuracy, and longer read length. G4 specialty application kits with novel content and workflows for specific applications, and, of course, advancing the PX, the first high-throughput in-situ sequencing platform. We look forward to updating you through the year as these all progress. Before I turn it over to Dalen, we would like to provide some color on the 2023 outlook. We are incredibly encouraged by the magnitude of interest and engagement from AGBT, with a sales funnel well into the triple digits in terms of qualified leads. We are seeing strong interest, especially in academic labs, where longer budgeting and sales cycles typically result in instrument purchases in the second half of the year. Our funnel is strong and growing with real opportunities. Engagement with customers indicates the F3 and Mastery kits will be significant adoption drivers of the G4 as they become available in the coming months. We are currently applying learnings from early placements and taking the necessary time to improve on things such as system deployment, support and service, and instrument reliability to make sure we meet customers' expectations and lay the right foundation for sustainable success. This means a slow and moderated deployment early in 2023, ensuring a consistently positive customer experience during this early launch phase, and equally important, preparing for a scaling phase later this year. We will provide additional color and updates on 2023 in our Q1 earnings call. With that, I'll turn the call over to Dalen to go over the details of our fourth quarter financial results.
spk04: Thank you, Drew. I'll start by covering the Q4 2022 financials. Then I'll provide directional remarks on key metrics for 2023 and overall cash runway. Revenue for the fourth quarter of 2022 totaled $765,000, made up predominantly of the revenue recognized on three instrument placements during the quarter. Gross margin was approximately flat during the fourth quarter of 2022, driven by consumable and extended warranty credits, as well as higher costs associated with the installation, training, and support of our first system placements. Operating expenses for the fourth quarter of 2022 totaled $22.5 million, compared to $19.7 million for the fourth quarter of 2021. These totals included non-cash stock-based compensation expense of $3.1 million in Q4 2022 and $2.9 million in Q4 2021. The year-over-year increase in total operating expenses was driven primarily by scaling headcount and infrastructure to support our growth, including the G4 launch, product pipeline, and R&D roadmap. Net loss for the fourth quarter of 2022 was $21.1 million, or 29 cents per share, compared to $19.8 million or 27 cents per share in the fourth quarter of 2021. Our weighted average share count for the quarter used to calculate net loss per share was approximately 71.6 million. And in cash, cash equivalents and short-term investments, excluding restricted cash, totaled $244.6 million. Turning to directional comments on 2023, as Drew mentioned, we've been excited by recent customer feedback and we believe our value proposition is resonating more than ever. We believe it will be essential to focus on and support early placements, and we intend to moderate G4 placements in the first year of launch as appropriate. As such, we expect that G4 placements in the first half of the year could be lumpy and trend around the lower end of the ranges previously discussed. One of our highest priorities is to ensure the installation, system bring-up, training, and support experiences are positive, This is foundational to our long-term success because we are still in the early days of establishing credibility as an emerging company in the space. We expect 2023 investment related to our product priorities to increase across commercial, manufacturing, operations, and R&D. However, we are mindful of the macro environment and need for focused capital management. Our intent is to manage existing resources to extend cash runway into the second half of 2025. Thank you, and back to Drew for closing remarks. Thank you, Dalen.
spk07: In closing, I want to reiterate the themes of today's update. First, I'm incredibly proud of the Singular team in 2022. It was a busy and productive year, filled with many milestones for our company. We brought the G4 to market, placed initial systems in customer labs, and generated our first revenues, all while navigating challenges in scaling the supply chain and manufacturing. Second, recent product announcements like the max read kits for single cell sequencing and spec improvements in quality and throughput for the F2 and F3 flow cells have enriched our portfolio, continuing to differentiate the G4 from the competition. Customer interactions and feedback from prospective partners continue to validate product market fit. Simply stated, we built the right system. And third, we're excited about the opportunities in front of us for 2023, a year in which we will largely measure success across four pillars. First, commercial execution in the form of installed based revenue and customer satisfaction. Second, G4 TAM and product market fit, evidenced by customer profiles and growing adoption in our target market segments. Third, operational excellence, measured by our ability to improve manufacturing efficiency, manage supply chains, and deliver high quality products at greater scale. And fourth, innovation pipeline, which in 2023 includes bringing additional G4 kits to market and advancing R&D on the first in-situ sequencing platform, the PX. Now let's open it up to questions. Operator.
spk08: Thank you. At this time, we will be conducting a question and answer session. If you would like to ask a question, please press star 1 on your telephone keypad. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. One moment while we poll for questions. Thank you. Our first question is coming from John Sowerbeer with UBS. Please pose your question.
spk03: Hi. Thanks for taking the question. You know, maybe just digging into a little bit of the manufacturing headwinds that you had there. You know, do you see these now, you know, behind you and resolved? And just, I guess, on that to clarify, it sounds like you're going to be at the lower end of that two to four per month. initially for the first half of the year is what your thinking is for instrument placements?
spk07: Hey, John. Thanks for the question. I guess I'll take it in two parts. On the manufacturing side, we made tremendous progress. We talked about it in the prepared remarks. Significant progress, but still work to be done. Anytime you're developing, deploying a complex instrument, you're going to learn things in the field when you have instruments in your first few customers' hands you know, running repeatedly that you didn't see internally. They break things new ways. So there's obviously going to be ongoing improvements there, also improvements on how long it takes us to manufacture, which we build an instrument and then bring up, which is kind of testing and handoff to either internal customer or external. There's definitely going to be improvement on how quickly we can do that. It's measured in, you know, weeks, and we have internal goals to get the current time down even further. We mentioned 25% improvement from where we were at the end of last year to where we are now. On the instrument side, yeah, we'll be on the lower side in the first half of the year. We took a little bit of a pause to apply learnings from the first five shipments for the first part of Q1. And we expect kind of Q1 and Q2 to kind of be on the lower side with much more kind of steeper ramp in deployments moving into the second half of the year.
spk03: Thanks. And, you know, that kind of leads my next question. Just, you know, any additional color on learning, maybe across, you know, software, installation, or feedback from those initial five customers out there that you can share with us?
spk07: Yeah. Yeah. I mean, overall, everyone's really happy. And the sequencers are up and running producing data. And we have, you know, five happy customers that will serve as five reference sites. And I think that's an important point. We want every early placement, every placement for the foreseeable future to be a reference site. The learnings really are across-the-board shipping. How do you make sure you ship an instrument and you don't have to spend extra time once it shows up making sure its calibrator wasn't damaged in shipping? Installation learnings, learnings on customer bring-up, and then ongoing support. And then there's also learnings, obviously, on the instrument side, certain areas of robustness and reliability, a lot having to do with customer training, packaging and kits. I mean, it's really across the board. Overall, we're exactly where we want to be. and they're working very well in producing high-quality data, but there's also learnings that you want to apply before you put more units out there and make sure that you have that consistency of customer experience before you really go pedal to the metal on putting units out there. So we're just working through that as kind of we expected and feel really good about where we are, and that's kind of the learnings are really across the board.
spk03: Thanks, and then last one here maybe for Dalen. Just appreciate the color on the cash runway to the second half of 2025. Just any additional, you know, puts and takes you can give us on just the cadence this year and how we should think about that burn.
spk04: Yeah, hey, John. Thanks for the question. Yeah, Q4 OPEX and burn was a little bit lower. There was some seasonality in there, you know, related to some payroll and labor-related items. In addition to that, you know, we were going through our, you know, 2023 annual budgeting process. you know, looking through the prioritization of activities and investment. I think just natural course of that slowed pace of spend a little bit. You know, if you look historically, our quarterly, you know, kind of burn in expense, you know, run rate has been about $25 million. And I think that's a good baseline to think about, you know, starting, you know, Q1 here in 2023, adjust it a little bit for, you know, kind of annual just salary merit increases for the employee base. But I think that's probably a pretty good baseline to start the year.
spk03: Got it. Thanks for the questions, and congrats on the revenue milestone.
spk08: Thanks. Thank you. Our next question is coming from Julia Quinn with J.P. Morgan. Please pose your question.
spk00: Hello. Thanks for taking the question. This is Martin Nazarovic on for Julia. I just wanted to ask about the customer mix. You previously mentioned it's mostly academics. but you hope to see a shift towards a bioforma as well. So what's your expected customer breakdown for 23 based on your current funnel? Any color you can share there?
spk07: Yeah, I think we expect the current funnel to be fairly representative of what we think the install base will look like. Right now, it's majority academic, either core labs or investigator labs. It's probably... I would think around 60% academic and 40% others. So it's not a huge skew in one direction. We think it'll even out more over time. I think we're learning that the academics in a lot of ways are kind of early adopters. Some private companies as well, but when you talk about biopharma or CROs or other central labs or people that are doing clinical testing, those are probably going to be what we call qualified leads in the funnel further out, and we think that that mix will change over time as we kind of get the system out there and establish the market.
spk00: Great, thank you. And then the second question, how has the sales cycle changed in 4Q, and how is it trending so far in 23?
spk07: Yeah, so sales cycles for these types of instruments, they're a little bit longer. You know, we expect a six to nine month sales cycle. Similarly, we expect it to take a rep that's hired six to nine months to really get fully up to speed and be able to, you know, hit quotas. You know, I don't know if there's much change from last year into this year. On the academic side, you know, we certainly haven't really seen much change, although understanding budgeting cycles better is giving us more visibility into when those purchases and when this demand will convert into placements. And that's really looking more into the second half. a lot of the academic budgeting cycles, they'll look at different options for the first half of the year, put their request in mid-year, and then they'll be looking to take delivery and pay on the second half and mostly Q4. On the private side, I think we are seeing people a little more hesitant to adopt new technology or spend money in the current macro environment. So I think that will change at some point. So maybe longer sales cycle with private companies, academic unchanged.
spk00: Great. Thank you for taking the question.
spk08: Thank you. Our next question is from Matt Sykes with Goldman Sachs. Please pose your question.
spk01: Hey, good afternoon. Thanks for taking my questions. Drew, maybe the first one for you. You mentioned that TAM analysis that you guys have done. We'd love to get a little bit more additional color on sort of the output of that analysis if you're willing to share and just kind of where you feel like the realistic TAM is and where you think the sort of differentiation with G4 is resonating and what that does to the sort of addressable portion of the TAM sort of this year and into the future.
spk07: Yeah, absolutely. We're happy to share kind of our models and our numbers separately. I guess at a high-level summary, if you think about the current market of NGS, and again, there's all different TAM analysis of how big it's going to be in five or ten years and where the growth is, but start with the $6 billion current market. About half of that is academics. And if you look at the breakdown, the majority of the academic are going to be doing targeted panels, RNA-seq, and single-cell. So when we think about early adopters and where those things converge, RNA in the academic environment and single-cell RNA are real sweet spots for us, especially with max-read coming. We think that'll be a real driver of adoption since it's such a differentiated solution for that really popular academic application. When we look at the clinical side of things, the majority is targeted panels. And that's something that we're very interested in addressing and demonstrating. We think the G4's kind of specs, throughput, speed are really well suited for your academic medical center or your hospital lab or even a centralized clinical lab due to the fact that you can run individual samples very quickly at a really good price point. But as we mentioned earlier, we think those are probably further on the adoption curve. The early adopters likely aren't putting patient-critical samples onto a new technology, and that's just the reality of how new technologies go. So we can definitely spend more time with you on those TAMs, but the point is sitting here a year from now, if we say we're going to win in the academic single-cell market, well, we want to be able to show you proof points of that, have real customers, understand the use case of those customers, and have metrics. And if we're telling you we're going to play in you know, academic medical centers and start doing targeted panels, well, where are the early proof points in that and where are we getting traction and how do we think about what part of that market we can win in? So that's what we mean and we'll share more on it.
spk01: Got it. And maybe just following up on that comment about Max Reed, just kind of leading to my second question, which is just based on the feedback you've gotten and if we focus on sort of academic where you've had some success, products like Max Reed and other products you might have in the pipeline, has it shifted your priorities in terms of where you want to spend some of the R&D to develop products to maybe focus specifically on those applications you mentioned, but on the academic channel and where their kind of interests lie? I mean, has it shifted any of your priorities in terms of spend and focus for product development?
spk07: Yeah, it has. You know, I think we talked about Max Read being a technology that can serve other types of short read applications. You know, internally, we have kind of reprioritized our roadmap on kit development. You know, single-cell RNA will be the first max-read application, and beyond that, we're looking at a traditional RNA-seq application to develop, and then we have a list beyond that that we haven't really, you know, decided on, but there's another couple applications that are used in the academic environment that lend themselves to short-reads. And then I think, you know, to the point you're getting at, yeah, the reception specifically at AGBT and the nature of how our funnel has grown from, you know, say Q4 to now, we've seen our funnel in terms of a qualified lead more than double in the last three to four months. And a lot of that, those additions to the funnel are academics who look at the max read kits and say that solves a unique solution for me. And that's really, you know, a motivator or a driver to adopt.
spk01: Got it. And just maybe one last one, just sort of on the, On the ramp this year, thanks for the color on the cadence in the beginning of the year. As you prepare for ramping in the back half of this year, what's the initial install base that you look to have to get the comfort that things are in line, performing well, you've taken care of a lot of the clear issues, and on the manufacturing side, you're ready to scale up? Is there a target number that you're looking for that you want to get to, or is it more just about the collection of feedback you're getting?
spk07: You know, it's a good question. I think, you know, if you go back to, you know, the comments and the color we provided, I think it was almost six months ago now, on being able to do two to four units per month moving into this year. We don't think it's going to be necessarily two to four units per month every month, especially in the first half. We think it's going to be lumpy. Like I said, we took some time to implement changes in the first half of this quarter. But if you think about that two to four as an average over the whole year, you know, I think we expect to be somewhere in that range just back-end loaded. So, again, I think we feel really good about where we are, but it's definitely going to be one of those situations where, you know, we monitor and learn as we, you know, put the next wave of instruments out and, you know, gauge appropriately. You know, so I think, you know, hopefully that gives you an idea, you know, on the low end, you know, two to four, you're in the low 20s, and the high end, you're up into the low 40s, mid 40s. So I think somewhere in the middle of there is ideally where we would be, but it's hard to articulate where that will be just given the fact that we're going to make sure we pace our deployments with making sure every customer has success and the instruments are performing as we like.
spk01: Got it. Thanks very much, and congrats on the revenue milestone in Q4. Thanks.
spk08: Thank you. Once again, if there are any remaining questions or comments, please press star one on your phone at this time. Thank you. Our next question is coming from Don Brennan with Cowan. Please pose your question.
spk05: Great. Thanks, guys. Maybe the first one, Drew, Daylon. So just, I know you've given a lot of color so far, but what is it that is specifically pointing you to the lower end? It doesn't sound like it's demand. You say you want to delight your customers. Is there something about what's going on with the first products in the field and the training and it's taking longer or are there issues? Just kind of what is pointing to the lower end?
spk07: Yeah, I think it's exactly what we said. I mean, we put the first five out really at the very end of Q4. So there was a tremendous amount of learnings as we got back from the holidays to process. And then there were improvements that we wanted to make across the board. So it was kind of slowing down for the first part of the quarter and implementing some of those improvements. And as we think about kind of, you know, the ongoing nature of those continued learnings and putting additional systems out, it's just going to be a slower, you know, moderated deployment for the first half of the year and, you know, then really putting the gas down in the second half. You know, there's nothing more to it. It's really just taking learnings, applying them, and improving the entirety of the experience of, you know, building an instrument, deploying it, and getting customers up and running.
spk05: And is it more on the building or is it more like when you place a box in the customer's hands, is it like they're taking longer to ramp it and they need to be instructed on how to use it? Or just like any specific examples about like what it is these learnings are focused on?
spk07: I don't think we want to get into specifics. It really is broadly kind of everything. You know, there's different parts to, you know, bringing a complex instrument up internally. There's still improvements we want there. There's improvements on the installation and customer bring-up. And then there's also improvements on the system itself. We have F3 in early access right now that's more broadly becoming available in the quarter. We have system upgrades and software upgrades in process. So there's upgrades across the board that we're, you know, applying and rolling in and thinking about how we want to time different improvements or upgrades in processes or systems with the next wave of systems.
spk05: Got it. Okay. Now that's helpful. So the ASP, should we be using something in the 250 range or below versus we're using something higher? Like what's the right way to think about the ASP going forward for the G4?
spk04: Yeah. Hey, Dan, this is Dalen. ASPs were actually in line with kind of where we were expecting them to be. I think from a revenue standpoint, you have a couple of things happening. You know, for the first three systems here that got accepted, you know, we, we gave some consumable credits and extended warranty and, And from a revenue recognition perspective, the value of those kind of credits gets carved off, deferred, and will be recognized in a subsequent period. So ASPs were about in line with where we thought they'd be. There was some discounting kind of for, I guess, the early part of the launch here. We'd expect that to change and become a little bit more favorable for us here as just the system gets more established in the market. But, you know, really it's kind of those two, you know, things impacting, you know, kind of the revenue side of things. From a COG standpoint, you know, if you look at margin, you know, there was a little bit of higher cost, you know, associated with kind of that, you know, white glove, shipment, installation, and additional training service. So, you know, kind of all combined, you know, those are kind of things impacting ASP and margin.
spk05: Great. And then... Um, the funnel well into the triple digits, any, any color on again, like what constitutes a funnel? And I mean, it's a big number, just again, you're not going to give it a specifics on all the details, but just how do we think about that funnel?
spk07: Yeah. I mean, those are qualified leads. And when we think about a qualified lead, we're thinking about a criteria that means it's a real opportunity. There's four things that we think about, you know, does the customer have a need? Do they have the budget? Are we speaking with the right person that has authority to make a purchase? And then what does the timing look like? So, I mean, you can, you know, throw a funnel of numbers around and, you know, but unless they're qualified and you understand the likeliness or how real those opportunities are, we haven't been willing to talk to them yet. So that well into the hundreds is meeting all four of those criteria, meaning we think it's a real opportunity and we have a chance to convert it this year.
spk05: All right. And then... Sorry, Dillon, or Drew, you talked about maybe slower demand trends at private labs or private customers, I think you said. So, you know, we've heard this throughout 2022. Agilent talked about it a little bit earlier this week. But this is just so I'm clear, like this is clinical labs that are kind of just, you know, dealing with maybe tighter capital constraints. So they're being more cautious or just maybe a little clarity there.
spk07: This is more private companies. So, I mean, we're not really selling into clinical labs yet. We're starting to have conversations with them. But like we talked about on the prior question, you know, really, you know, having our sequencer and a clinical workflow doing patient samples, that's probably something that, you know, we'll be ready for, you know, at the end of this year and the next year. With the new technology, the early adopters are really more on the academic side or private companies that want to try a new technology. In general, private companies, similar to ourselves, you know, people are belt tightening. They're thinking about extension of runway or getting to profitability. And it's just a little bit different of a buying environment than, you know, say it was, you know, 12 or 18 months ago. So that's all.
spk05: And on the PX, you said you saw in the first tech assessment, just wondering, like, what, like, does that mean a box is at a customer or that customer is sending you samples? And then any more color just about timings? for the PX and just kind of remind us. I mean, the PX, the main differential is like, I mean, there's probably a lot, but much, much better throughput than what's on the market today. So maybe you can give us a little more color on the PX.
spk07: Yeah. So to answer the first part of the question, it's a technology access program. And the agreement that was signed essentially outlines the scope of work. And we will physically receive samples and conduct experiments with those samples on the PX and provide them back to that academic partner. We plan to do a few of those this year. So that's not an external placement of the system. That's samples coming in. I would say just the very high level, the PX is taking a lot of the technology we already developed in the G4, the optical system and all of the chemistry, and then supplying it to sequencing inside of cells and in tissue. So we're actually using sequencing in situ as the readout. And there's two really powerful things about that. One, you're using sequencing as the readout, so you have the ability to multiplex or determine a lot of information due to the sequencing nature of the readout. And the second is the throughput. We're working in 96 and 384 well plates, so the sample plexing is just very high, 96 samples or 384 samples at a time.
spk05: Got it. And then maybe a final one would just be pricing. So like, um, just remind us, where are you today in the market? Like on a price per gig gig, since I guess, I mean, I know, um, it's coming down, you know, elements, obviously stepping on the gas. I don't know what aluminum is doing, just kind of what, where's pricing that.
spk07: And is that a topic of discussion with customers or no, you know, pricing is always part of the equation, but I think the important thing is to sell on the, on the actual performance and the attributes of the system. And the differentiation, the G four has is going to be throughput on a bench top instrument. It's going to be speed. and it's going to be flexibility given the four flow cells, and each flow cell has different configurations. You can scale up or scale down, and then each flow cell has four lanes, which is really nice for customers that don't want to mix or barcode samples. So those differentiating factors are really the basis of what's getting customers interested. On the pricing side, if you look at a NexSeq, which is still the predominant choice out there for a benchtop sequencer and really what we're selling or selling against, you know, 99% of the time. You know, it's a $335,000 box, and it ranges from about $15 a gig up to maybe $40 to $50, depending on, you know, the specifics. And we're pricing, you know, quite favorably compared to that. The box is about the same at $350 list, but again, it's almost the equivalent to, you know, three nexus in a single box, given the power output and the four flow cells. And then our cost per gig standpoint, we're ranging from about $8 on the low end, if you're you're really going to see massive cost savings versus a NextSeq, and you're going to see faster run times, more flexibility. And then with MaxReads, that's where it really becomes competitive for single-cell applications. And the average customer, I think, right now for a single-cell application is probably spending $600 to $800 on sequencing costs to read out a single 10x experiment. And with MaxReads, we're going to get down to $200 or so. So that's going to be a huge driver for us. So again, I think when When we think about selling, it's selling on the actual competitive advantage of the system. And then when people turn to price, they're usually very, very pleasantly surprised based on where it prices versus the next week.
spk05: Great. Okay. Thanks, guys.
spk08: Thank you. Our next question is from Michael Ricekin with Bank of America. Please pose your question.
spk02: Good afternoon. This is Peter on for Mike. Thanks for taking the question. Definitely understand again here it's early days, but I mean, assuming supply chain doesn't, you know, flare back up, do you have like a rough idea of maybe the production scaling process, you know, when that would be reaching more of an equilibrium with demand?
spk07: You know, it's hard to say. I think, again, if we look at the year in totality and we put those error bars, cut out average systems per month, we're definitely expecting to be able to achieve that this year. I think it's just important that we make sure we get the system in the customer's hands and meeting expectations. And I don't think we're looking to rush systems out for near-term numbers if we're not 100% sure that it's going to meet expectations. One of those areas is the F3 flow cell. We want to get the F3 flow cell broadly available And a lot of customers, you know, are interested in having that. And that's something that's coming available beyond early access very shortly. So, you know, I don't think we have, you know, much more color to provide other than, you know, we're learning, you know, applying those improvements. And, you know, we're kind of right where we want to be looking at the funnel and looking at our ability to kind of scale up through the first half this year and really hit in stride in the second half.
spk02: All right. Thank you for that. And then just. Back to the PX quickly. Any incremental color updates? I mean, you can give on key milestones or kind of like the timeline of what we should be looking out for updates regarding that. Thank you.
spk07: Yeah, so like we answered the question with Dan, we've signed our first technology access partner. We plan to do one or two more of those this year and to kind of have different types of experiments demonstrated with each. We still don't have a product release date. It will take additional resources to develop that product. And we're still really focused on the G4. We have additional kits coming out in the G4 later this year. We have upgrades throughout the year planned. So I think at this point, we don't have much more color. We are building a large fleet of betas. We've talked about that. We should have close to a dozen betas by the end of this year up and running. So we really have throughput to evaluate external samples, potentially place a beta next year or two if we want to. So I think we'll probably have more color on that towards the second half of this year as we you know, kind of get the G4 scaled and successful in market and start to shift a little bit to product development and timing for the PX.
spk02: Okay. That's so helpful. Thank you.
spk08: Thank you. As there are no further questions in queue, this does conclude today's conference call. You may disconnect your lines at this time and have a wonderful day. And we thank you for your participation.
Disclaimer