Quantum-Si. Quantum-Si commercializes Platinum, a next-generation protein sequencing device that also includes a protein analysis software. T o discuss the company's strategy for continued commercial and long-term growth in 2024 and beyond, I welcome Jeff to this discussion.
Thanks for having us.
Jeff, so what's unique about Quantum-Si's technology? A lso how is the Platinum device and the software, how does it differentiate itself against what competitors have out there?
Let's start with how, what's the technology do, right? So if you're familiar with DNA sequencing, Quantum-Si is doing something very similar, but we're doing it for proteins, and we're giving people amino acid-level resolution and also able to detect very small changes called post-translational modifications. In terms of the instrument and the software, so the instrument, called Platinum, is a small desktop machine. It has a list price of $85,000, and then the software, which is cloud-based, has a series of workflows and capabilities in it that fully automate the data analysis for customers. I think when you compare that to other technologies in the market, a commonly known technology would be mass spec. Those machines retail on the low end for around $500,000 and go up well over $1 million.
Then in terms of the data analysis, while those technologies are very powerful, it's a very non-standard, non-automated. You typically have bioinformatics people who are doing workflows and customizing that analysis, so really gotta be a very sophisticated core lab to use a technology like mass spec, where with Platinum and with our automation, you can be a core lab and use it, but you could also be a new-to-proteomics lab and leverage this technology.
In terms of your database, can you describe, who these folks are, and in what areas do you expect the product itself, you know, to get adopted into?
Sure. T oday, and in 2023, when we initially launched, most of the first customers are large academic medical centers, places like Northwestern University or Johns Hopkins those preeminent KOLs, that they take on new technologies and begin to explore their capabilities. We're continuing to work with a lot of those, you know, large academic medical centers, both here in the United States, but also, in Western Europe, where we're beginning to build a footprint. But as we've moved into 2024 and moved throughout the year, beginning to get more traction with pharma and biotech customers who are using it, you know, more in the drug development side of the workflows.
One of your recent announcement was a collaboration with Liberate Bio, which is using protein barcoding in order to screen lipid nanoparticles for in vivo delivery of genetic material. C an you please break this describe the application itself and maybe share certain details of potential targets or target tissues that these folks are going after?
Liberate Bio is an early-stage biotechnology company in the Boston area. They originally were working with us and talking about this concept of barcodes. W hat they're trying to do with lipid nanoparticles is engineer these LNPs to target certain tissues. I think historically, LNPs have been very good in liver, but haven't been maybe as applicable to deliver payloads into other tissues. T hat's what they're working on, is: how do we develop new chemistries, new formulations that will target other tissues?
What they're using us for is they're putting a genetic payload in there, let's say an RNA or an mRNA. They're attaching a, a very small, highly sequenceable peptide to the end of that. They're then able to inject in an in vivo model, in a multiplex fashion, different formulations of their LNPs, and then they can see which tissues those LNPs went to and if there are relative changes in the amount that you see of one formulation or another allowing them to multiplex this screening and really get to a formulation in a faster pace.
The other aspect goes back to what I said earlier, which is, you know, the accessibility of the technology. T hey have amazing scientists at Liberate Bio, but they're an early-stage biotech, and early-stage biotechs want to invest as much as they can in the development of their drug. T he concept of acquiring a very high-dollar piece of capital equipment, like a mass spec, just wasn't practical for them. O ur technology had a really attractive price point, and then the automation meant they didn't have to be experts i n doing proteomics analytic tools. They could bring something in like this, get trained in just a couple of days, and be up and running, and now doing multiplex screens of these LNPs.
I'm sure barcoding was not an application that you thought of, you know, when you started Quantum-Si or when the technology was being put together. Do you foresee, you know, similar such applications or that the customers are talking about, wherein you need to innovate your own technology a little bit more to suit for their needs?
I think you're right. We weren't sitting around in a room thinking like, "Hey, let's build a next-gen protein sequencing to do peptide barcodes." I think we are obviously thinking about the big picture, the big vision of de novo sequencing and all the various proteoforms that are out there, things like the PTMs and the variants, all these like very difficult things to analyze today. Well, I think this is a good example of you get your commercial team in place, you get out, and you start talking about the technology. W hen you have a broadly capable technology like this, the customers will, once they're familiar, begin to surface these ideas. They'll surface the concept of, "Let's use a barcode.
C ould I do that? How could I do it? How multiplex could I be?" I think there's bound to be other applications. W e've seen people work in PTMs, which we expected, but we've seen people look at isoforms. T hey're doing it complementary to mass spec. I think if you would have gone back 18, 24 months, you know, we weren't sure how many of our instruments would really fit in a mass spec core lab. Would it really be a tool that would add value there, or would people see it as a purely competitive situation? I think those customers have really helped us see, "Hey, I can do this set of things with my current tech.
Here's a new technology that helps me do these other things I can't, I haven't been able to do historically," so I think they'll continue to probably open up ideas, applications. Sometimes it's just as simple as us optimizing with them. Other times it might turn into a kit or a product or a software, like what we're doing with barcoding, where it'll be a dedicated kit to really optimize that workflow for them.
Quantum-Si, you know, seems to be continuously upgrading the products and innovating your technology. So an example of that is, you know, you just released your Version 3 sequencing kit. H ow does this process work, in the sense , do you do this on the demand of your customers, or is this something that, hey, you know, you got to make a better kit or a better device from where it is now? Is that self-driven? H ow, as I said, how much of this is customer, you know, feedback, and how much of this is internal?
I think it's a mix of both. I on one hand, we have, you know, an amazing R&D team, you know, I think a really great, like, vision of this technology roadmap from things we want in the near term to things we want to, you know, do, you know, in the long term in the most highest order, you know, path to getting to de novo sequencing. So some of this is just our own innovation programs and the capabilities we believe that as we bring out, customers will benefit, whether they're, you know, doing protein identification, whether it turns into barcoding. They're almost ideas we have about just lifting the technology capability independent of the application.
I think where the customer piece becomes more and more integral with our product development is as we start to identify these applications. So specific things that the customer wants to do, where maybe the technology does it, barcoding is a good example, but knowing their workflow and their requirements, we're able to optimize a very specific kit that makes that workflow even simpler, gives them the characteristics they're looking for, and really makes that a plug-and-play solution for them. So I think you'll continue to see a bit of both as we see that, and sometimes it might just be software too. There could be things that we could just optimize a workflow for, maybe variant detection or PTMs. Maybe that's an idea where there's a specialized workflow.
I think these are the types of things we're always listening to, to be additive to what we're doing on our own.
The other piece that you have been doing regularly is also upgrading your library prep kit, which is very, very important for this process. So what's a library prep kit? And, you know, how does it really improve the workflow, you know, that you're just talking about?
The library prep kit is what you use to go from your proteins of interest into peptides that then can be loaded onto our cartridge. T hat kit has a big influence over the complexity of the sample that you could be working with, the concentration of that sample, and then just how efficient are you in getting those peptides delivered onto the chip. W e have a version of that kit today. We have been working on an innovation roadmap to improve upon those parameters I laid out. C an you process a more complex sample, more complex mixture of multiple proteins? Can you improve the and reduce for the customer, especially the input quantity that's needed? T hen there's always little opportunities to just improve the packaging, the workflows, remove some pipetting steps.
I think the second version of library prep is largely around really just making more and more applications available, but there's also always an underlying, "Can we make it easier for the customer to use?" I think that thought process is baked into everything we do. Can we really simplify that workflow for customers, always looking for little things on top of the technology capability?
At this point, how many of the amino acids can you recognize? D o you need to improve that technology more to recognize additional amino acids?
Today, the Version 3 kit, if you go on our website and look at the data, we're covering about 70% of the amino acids in the proteome. T he one thing I would tell you is there are an enormous number of applications where that level of coverage or even, you know, somewhat less coverage would be more than enough, right? If you're doing protein identification, you don't need anywhere near, you know, 100% coverage, right? You need a certain number of amino acids, a certain number of unique peptides to do protein identification. E ven our Version 1 kit, which had much lower coverage, was capable of doing a really nice job with protein identification.
I think the reason to keep expanding that is, as we get this into the hands of customers, and they want to do more and more complex things, they want to look for very rare, you know, perhaps variants, the more coverage you have, the better it will be. C ertainly, our coverage today is not limiting us in any ways in terms of our commercial applications or customer adoption. It's really us trying to continue to advance the tech and stay ahead of where we think the market and the customers, and certainly competitors are.
I have one more question on applications. W hen I think about disease diagnostics, you know, is there a place for Platinum to be used there? And then what might, you know, if it is possible to use it, what applications, you know, would that be useful for?
I see clinical, I think, in three pieces, right? There's the discovery of novel biomarkers. There's more of what we would call translational studies, so I've got a biomarker of interest, and I want to scale that work and look at a lot of highly characterized patient samples, and then you have the routine clinical testing. You know, I think today we're playing in the middle, and over time, we'll play more in that first part from discovery all the way through translation.
Okay.
We're not yet being applied in the clinical setting. I think the question on the clinical side will be: what will those biomarker panels of the future be, right? Today, they are largely, you know, a single. I want to look at phosphatase as an example in Alzheimer's, right? So I want to look at one PTM on one protein. You know, so in that, you know, regard, not an overly complex analysis, therefore, a lot of technology is capable. I think as we learn more and more about the proteome, you see some of the studies coming out from some of the big national biobanks.
There's lots of panels that appear to be falling more in that five to 20 protein level, and if you start to get to more complex panels, you start to get into multiple proteins and multiple PTMs, then I think a technology like ours is going to be ideally suited to go the full range, from discovery all the way through into the clinical space. Then, on the adoption of the Platinum right now, you initially started commercializing this to some of the academic centers. W hat's the feedback that you're getting from them at this point?
I think we've talked about this a little on some of our earnings calls at and at other conferences. G etting people interested is easy. When you have something like this that's so ground breaking, so novel, some folks even just wanting to wrap their head around the art of possible. How did this... You know, how do you even do this? It's easy to get that first dialogue going. I think where we are refining our commercial strategies and such, is really how do you identify that person who's not just interested, but really has an application that we can really help solve, that application by solving that, we're solving a real meaningful problem, and therefore, you know, they're going to, you know, gain value from having the technology.
I think the consistent feedback we get, you know, from the people running it, is just how easy it is to do. I think we, when we go in and train, we have application specialists who train the customer on the workflow, that wet lab workflow. T hen when we get to data analysis, if they're in a core lab and they've been around mass spec or other tech, there's always that like aha! moment as they sit in front of a screen, and it's much more of a point-and-click drill-down, very intuitive, workflow on the analysis side.
That always gets that wow s omeone really listened and brought us the type of ease that we're used to in our personal life on our phones and other applications. I think that's the one thing you get that I think is always fun to see with the custome light up about the workflow.
it's not just people saying, "Well," they've actually started putting out data now. y ou have in scientific conferences, we are seeing some data presentations out there. C an you highlight to us, you know, a couple of them, and where do you think these folks could go from here, you know, in terms of, you know, data presentations? Like, what other data presentations should we expect?
Sure. T he first couple that have come out, Dr. Schenkman, who's at University of Virginia, working with peptide isomers. S he had identified a couple of proteins around calcium absorption and osteoporosis. Those proteins have peptide isomers, which means they have the same weight, but they have a different sequence. T he difference in sequence is a different outcome, but you can't see that with mass spec. W hat our technology did was she took. Again, this is a good example of the complementary nature. She had identified some proteins of interest, now she wanted to study that more deeply and study that across more samples. She's using our technology to do that type of work. I think very similarly, Dr. Kelleher at Northwestern, in this case, though, looking at a PTM, looking at phosphorylation, neurodegenerative disease in this case.
Again, this more translational setting. They have an idea, they have a concept. They're really looking to dig into that more. They're looking to expand that on the number of samples they have. I think that trend, if I look at what other people are working on and think about who's the next one or two or three academics that will stand up at a meeting and describe data, I think in the academic setting, especially, this concept of, you know, a variant or a PTM in a translational setting is really what is likely to be some of that, you know, additional data that will come out.
We're hoping that, obviously, partners like Liberate, who have been, you know, able to come out and talk with us publicly about it, what they're working on, they'll be able to start sharing data on how that's affecting their drug development process. W e're hopeful that them and some of the other folks using the tech will bring some of those other applications that maybe our academic partners aren't working on, but are equally exciting with the technology.
On the commercial side, you know, you recently added some sales folks both within the United States and also in Europe. How are you thinking regarding not only market penetration, but also geographic expansion from here?
Sure. W e started the year with a pretty lean and mean team. We had been in a controlled launch in 2023, so we were always very mindful of not over-investing too early. As we moved, you know, into the Version 2 kit launch, and now the Version 3, really understanding, you know, how to sell the product to customers, how to support it. We have been expanding that. W e talked about at the end of Q2, we had, you know, just under 30 people across sales, marketing, service, and support. W e intend to grow that by about another 10 this year. There's obviously concentrated in the U.S., but growing that presence in Western Europe. We have channel partners, as well, that we work with in areas of, you know, Eastern Europe.
We also have a distributor in Japan, and we intend to grow that, too. I think we've really gotten confident in our ability to train those channel partners, those distributors, to really go out and sell, service, and support the customer. We've seen some early success from that, so we're gonna expand that as well, but we'll stay direct mainly in those Western European and US markets for now.
Okay. And then, since as you said, since you started your controlled launch of Platinum in the fourth quarter of 2023, and then the commercial launch was initiated in the first quarter of 2024. Your revenues have grown to about $600,000 per quarter, but you also have a full-year guidance of, you know, $3.7 million-$4.2 million. What's the confidence that, you know, you have, that you could get to that guidance by the end of the year?
When we put that guidance together, right, we told yourself and Wall Street, really, what went into that, right? We were thinking about that full commercial launch starting up at the end of the quarter, the first quarter. We were thinking about that expansion of our folks in terms of direct reps, and we were, you know, expecting some of that peer-to-peer selling and various things to happen. I think we're right on track with what we thought. We had always said it would be, you know, more back-end loaded as those reps came online and customers got, out using the technology and talking about it, so I think those things are happening the way we want. You know, I think everyone in our space is talking about the capital cycle.
Certainly, a little longer than we would like. We're not seeing it disappear like some of the really high-dollar equipment is, but it's certainly taking a little longer than we want. But we're still, you know, feeling good that we're in the, you know, in the place we want to be, to get, you know, into that guidance range before the end of the year.
Perfect, and then the last question is, what cash position do you have? And based on what you need to achieve, and not only in 2024, but, you know, in the next couple of years, what a runway you have, from that cash position?
We ended the second quarter with $218 million in cash and marketable securities, cash equivalents. And I'm sure CFO can go into that in more detail for you. But that, as we've said, gives us cash out into 2026. W e feel very good about you know where we are right now in terms of cash and our ability to invest in the business. I think we've had a lot of focus on you know very high fiscal discipline. We've been able to really build out our commercial force from scratch and keep our operating expenses essentially flat year over year, and they're even down from what they were in 2022.
Like, the trend has been a very high fiscal discipline, despite, you know, significant investments in R&D and building out a sales force. I think that discipline will continue. T he continued adoption of the technology obviously helps to provide some gross margin and offset some of those expenses.
Thank you, Jeff.
You're welcome.
Thank you very much, and good luck for 2024 and the rest.
Thanks a lot.