Good afternoon. My name is Swayam Paklaramahant, or known as RK. I'm a senior analyst in the HC Wainwright healthcare team. So this afternoon, we are going to have a conversation with Jeff Hawkins, CEO of One MSI. One MSI is a commercial company developing next generation protein sequencing instruments. The first of which is called platinum, which is on the market, and they're also developing a second-generation system, Proteus, which is actually a platform and that provides differentiated capabilities. So to discuss the development of Proteus and also... Thanks for having us.

So just to get started, Jeff, if you give the audience a brief... uh outline of not only quantum si but also the commercial strategy behind sure the corporate strategy sure yeah so you know at a high level you know quantum si is in the field of proteomics and in that field you have essentially two different types of technologies you have technologies like mass spec or affinity based methods designed to screen for thousands of proteins from a sample but they just give you protein presence or absence um where we fit in is we're in sort of the what's a new bucket, some called next-generation protein sequencing, some called high-resolution proteomics, but essentially what we're doing is sequencing proteins at the amino acid level so that you can detect small changes such as single amino acid variants, post-translational modifications, sort of things that are very difficult to do with existing technology. As you mentioned, we launched a first-generation technology called Platinum in the beginning of 2023. We're the only commercial stage technology for amino acid level resolution sequencing in the market. We've been using that largely to engage key opinion leaders, generate data, learn a lot about just operational and commercial and sort of support of that technology, and then took those learnings from that commercial phase, you know, both here in the U.S., but also through some direct and partners internationally, took all those learnings and said, okay, what's the future need to really look like? What's the capabilities we need? And that led to the Proteus creation.

Perfect. So, you know, for 2026, you know, you deliberately have deprioritized, you know, platinum probe and guiding just for about $10 million in 2026. But because you want to concentrate on Proteus, not only development, but also making sure that you have it commercially ready for the launch. So when Proteus comes to the market, and let's say it's sitting in 2027, what sort of a revenue run would you like to see from Proteus so that internally the team feels that you've made about a decision?

Yeah, so maybe I position what we did with Platinum just slightly differently. We certainly have reduced it as the sole priority of our commercial team. We do have our commercial team splitting their effort around supporting that existing base and helping to drive consumable utilization and publications, but then also really prospecting and building the market to be ready for Proteus. But the other reality of, you know, sort of being a public company is we, you know, we had, we shared the information about this new technology in the launch. So some customers naturally hold back. That's why we introduced programs like our placement program. So people can access the current tech and, you know, learn about it, get used to running it without having to necessarily purchase that machine up front. Because we knew with Proteus coming, that would likely, you know, impact people's sort of timing. You know, do they want to buy the current one and then turn around and buy a new one? That's sort of a natural sort of sort of evolution that can happen. So some of this is also just people waiting. In terms of success, I'd say, you know, we learned a lot from the Platinum launch in terms of, you know, we went pretty broad as sort of a enabling technology with Platinum. Sort of if you want to try protein sequencing, here's a here's here's a technology you can do it with and sort of you can try any application you want. That leads to, you know, some successes and some people having challenges. It leads to a certain sort of support infrastructure you have to build. I think when we look at the launch of Proteus, you know, you really hear us talking about post-translational modifications. You hear us talking about single amino acid variants. You hear us talking about areas where there aren't good references. So you need to work in an unbiased or reference-free way. You're going to see us do that because we think that sort of depth of focus and concentration will lead to, you know, a more successful launch, sort of a smoother trajectory. But we do expect it to build up sort of in a controlled way over, you know, the first few quarters and then really build that evidence base, have the users that can sort of reference other accounts. And then you can really see the inflection point and acceleration, you know, not dissimilar to other companies who have come to space with, you know, space with new technologies over the years.

And with Proteus, you know, you actually have a master plan in the sense, you know, you not only want to start with Proteus, but then you want to go away from, you know, 80 million wells to the Proteus Plus, which will be about 320 million wells, and then Proteus 2.0, you know, which could be a 2.10 million. So this is actually a multi-generation hardware cycle that, you know, you're starting off from here. So for investors and also for people who would be using these machines, you know, what's the cadence that you are targeting as you grow this from Proteus all the way to Proteus 2.0? And, you know, would people just wait, saying, like, let's wait for Proteus 2.0?

Yeah, I mean, there's always that question of you've given a glimpse into the long term. So will people wait? I think that maybe a good way to divide it is so the move to Proteus was to get on to a core architecture in terms of the optics being in the instrument and the automation that's there and then the consumable being the passive nanowell array. So getting to that architecture was required so that we could have sort of now a two-step sort of evolution. A lot of the improvements you talked about, you know, more throughput, a lot of these will actually come through a mix of chemistry improvements. Some will come through software. So things like faster sequencing. Our standard sequencing time is 10 hours. I can double the throughput of the machine if I lower that to five over time or further. We've shown data in the past around sequencing time, sort of sub two hours, are feasible with improvements to the chemistry. We can improve the output by improving the number of single molecule reactions. Something called sort of superpoisson loading, sort of a techie term, just means getting a higher number of those wells in the array, delivering a quality sequencing result. So we can do most of what you're describing there for that, you know, platinum or sorry, Proteus 2.0. through a mix of chemistry, some software, um, you know, perhaps another embodiment of the consumable, um, but it doesn't require any new piece of hardware. So anybody buying Proteus is going to get that whole roadmap, um, you know, accessible through these other changes to get to the sort of the billion scale. That's where the technology we shared last fall controlled cleavage comes in. And what that means is we're able to control the sequencing reaction in such a way that you can then scan a much larger consumable. So when, you know, at some point that platform comes out, that is a new platform, but we may also target perhaps a very different throughput in that machine. We're not sure yet. So I think that's certainly a longer term roadmap item. I think anybody, any customer buying it now on Proteus is going to have, you know, a pretty attractive multi-year sort of evolution coming through chemistry software and, you know, maybe other consumable or reagent sort of approaches we might use that will be compatible in that machine.

So the next couple minutes, let's talk through Proteus and also the strength that Proteus In your latest call, you were talking about how Proteus has already delivered roughly twice, two times the read length that platinum currently delivers. and also seeing higher detection of amino acids and also the frequency. So, so far today, you know, what's the longest contiguous read length, you know, that has been achieved with Proteus? And, and also, you know, how does that translate to the PDMs detection, you know, that you'll be flagging as, as the hallmark of this mission?

Sure. So maybe we'll start technology and then work down to why does it matter for a customer? So technologically, when you think about protein sequencing, we sort of use the phrase coverage. And coverage sort of embodies a lot of things. It embodies, do you have the ability to detect an amino acid when it's there? then there's a component of how frequently when it's there do you see it because there's a lot of complexity here to sort of the context of the sequence and then there's how far into the peptide do you do you read sort of you mentioned the read length so we've really been focused on all three of those attributes over the last you know sort of two years as part of this program you mentioned we're now sequencing in our development lab at 17 amino acid detection again there's 20 total um part of that is we've also improved some of the existing recognizers that are in uh commercial kits so the detection frequency is going up and then the read length is a mix of you know just improvements to the chemistry but also some fundamental advantages in terms of detection capability signal noise um how how short of a pulse you can see with the proteus technology that leads to that longer read um you know i think read length we like to think about it in terms of average read length because there are scenarios where you have very short peptides and you read all the way through it before sequencing's over and you have other examples where a protein may be digested into some really long pieces so the sequencing could be longer so we try to have sort of quality control standards that we use so every time we're improving the kit we're measuring that and can see how the average coverage is changing or how the average read length is changing but to your point apples to apples on a controlled set of samples the read length on platinum today tends to average around 8 to 10 and we're seeing you know closer to sort of an average of about 15 right now why is that number important now let's get to why it matters so you you digest this protein into a bunch of small pieces called peptides the enzyme we pick makes on average a 20 amino acid long peptide. So perfect would be average 20. So if we're already out at about, say that about 15, about double the platinum, we're getting a lot more information. Why do we care about coverage? Why do we care about read length? Because at the end of the day, if people want to see a PTM, it doesn't mean that one's in the first position could be in the eighth, could be in the 12th, could be in the 20th. People want to see a variant same sort of logic applies people want to sequence something that doesn't have a good reference they they don't expect to get 100 coverage but they're going to want to maximize the coverage they can see so anything we do on either of these three sort of pillars improves the number of scenarios the number of cases that that customers can use it for the the breadth of the coverage they get or the percentage of the ptms they might be able to see so people doing biomarker discovery doing translational work, trying to profile PTM patterns, these things will all lead to more complete sort of context of their analysis.

So, you know, since we've been talking about PTMs, and one of the key differentiator for Proteus against mass spec has been the detection of PTM. That's what we're expecting to be done. What specific PTMs, you know, can Proteus detect at large versus, you know, what a mass spec can do at this point. And, you know, what are the plans to expand, you know, the PDM universe?

Sure. Maybe let's start mass spec. So, you know, phosphorylation, so phosphoproteomics is probably the most well-studied area. There are a lot of, you know sort of third-party software tools people can use to to take the data off their mass spec and analyze and ultimately resolve down to sort of site-specific meaning i know there's phosphorylation at this amino acid once you leave phosphorylation the availability of tools gets to be much more sparse so then you start to be more where what's the lab and do they have those in-house tools or not if we look at platinum so we haven't said exactly what we'll launch with on Proteus, but I want to maybe make a sort of a contrast. With Platinum, we have had people publish or present data on phosphorylation. We've had people present on methylation, deanimation, so sort of people playing with a range, citrullination. But on Platinum, some of that is automated through the machine. In other cases, people have taken the data and come up with custom analysis tools. Our goal on Proteus is this is all baked into workflows with automated analysis tools. What we're excited about with Proteus is we've historically kept sort of three different ways of detecting PTMs moving forward until we were confident in which track we wanted to take for the long term. Two of the approaches require a lot of protein engineering, which are feasible, but they tend to be longer sort of R&D timelines with more R&D expense. What we've just talked about on our recent call was we're really feeling good about the ability to detect these PTMs through the rich kinetic data that's there from the baseline sequencing reaction. More than just the amount of time the recognizer is there, the time in between binding events, the time in between cutting events, and just leveraging all of that with sort of modern AI tools you can detect these small changes that come from ptms the value of that is if you're a customer and you buy proteus the next ptm let's say we launch proteus and it has i don't know two or three ptms on the fourth is a software update it's not a new chemistry i think the key thing is doing it through kinetic signatures makes the sequencing universal which means the extension of it comes through the data collection, the training of the database, and ultimately a software. We push a new software module into the cloud. The customer now gets the fourth or the fifth or the sixth. So it's a much more extensible sort of path to add the capability. And being universal also prevents us from some of the challenges you see with affinity methods where they need special probes for certain proteins. So we feel good about that. I think we'll have a little more quantitative data to share soon in that regard, but we're sort of going all in at this point on the kinetic signature approach to doing the detection.

So the next couple of questions are just on the market itself, you know, adoption. So I think the last year you presented a customer survey data where you said 65% of study proposals are requiring to detect at least two PDMs. And then about 50% of them are requiring to do three PDMs or more. So with that in mind, when Proteus comes out at the end of this year, where do you think it's going to land in terms of which pool of these potential customers would you satisfy immediately and you know the the increase in terms of the detection you know is that i think you kind of answered it is that going to be mostly on on kids and things like that or is it real platform expansion yeah so i think so we we do have the data we've shared we've also as i mentioned have had our sales force out since essentially late january after we we brought them

all together and trained them on Proteus, doing the awareness and sort of gathering of what customers want to do with Proteus. And I can tell you, we've got now hundreds of data points from different users around the world on what they want to do in terms of PTMs. I would tell you that PTMs is sort of, we're learning, it's really interesting. It splits sort of along two lines. Are you working more in, and often a researcher, but they could be inside pharma, but if you're working in research, you're doing biomarker discovery, you're doing, you know, sort of translational research, there tends to be, you know, a set of PTMs that you would like to profile on every sample. Today, what happens in mass spec is most people do the phosphorylation, sort of the most commonly looked at, and then they may or may not continue that down to the other ones. If you look, people really want to do phosphorylation with methylation and acetylation. They want to do those three together and you'll once in a while see a paper where a top tier institute spent you know a month just analyzing one sample to profile all these different ptms so you know if you're in that research space there's that sort of combination of three that that seem to really matter the other ones are there in what they're looking for but it gets a little more sparse if you go over into the other side more in a manufacturing environment um you know phosphorylation is still very common but other ones um are are important as well but you tend to see more of a singular focus i'm looking for a byproduct in manufacturing i'm looking for something i would expect or not expect at a certain rate so you see a little more focused ptm work rather than you know more broad profiling work that's one of the things we see in the in the data but in general no one wants to buy you know an instrument to do one thing you know you don't want to buy a 400 000 or a million dollar platform to do one thing. So, and I think that goes back to the second part of your question, again, just to reiterate that with, with us using kinetic signatures, the, now the improvements to the chemistry or the improvements to the algorithms are, are simple upgrades to consumables and software, not a new piece of hardware. So, you know, customers investing with us, they'll have whatever capabilities we have on day one, but that'll, there'll be a roadmap to continue to expand that and um they're not going to need to buy a new piece of hardware you know or a new you know go find some software from some third party to do the analysis like they might in mass spec they'll be able to do that you know sort of through the tools we're providing or or you know an upgraded reagent kit you know that might come out in the future so another interesting thing get the folks that were at the price point, we're ahead of time. We did.

$420,000 as the list price, and you stated that there's not been much of a pushback yet from anybody, and also at the same time you have been doing sort of roadshows, you know, not only in the United States, but in Europe, in different cities in Europe. so um one what do you think with not having any pushback you know there is a flexibility on that price going forward you know a couple you know maybe not immediately but you know down the line and number two when you do all these road shows you know what sort of uh um what sort of leads are you generating um so that you know when you launch at the end of this year

there could be a bolus effect or what should investors expect yeah so maybe start with we released the price $425,000 we did that for two reasons one was we had some customers who are on platinum who have been using the technology for a couple years they're going to want to move they wanted to know to just get working in their budget cycle I also like that data point out there because if I have sales reps out prospecting and I'm telling you about this great new thing I developed, but I don't tell you what it costs, it's probably pretty easy to get you excited because you don't yet know what I'm going to ask you to pay. So it's more valid to have a price point. That said, we're not getting pushback, which means we probably didn't set it too high. It doesn't necessarily mean we didn't maybe set it a little low. We'll find out. But my experience in the industry says if you're low, you can always over time step up the price to get to where you think it needs to be the bigger problem you have is you go up too high you don't have enough capability for for that price point and then the customer is like no thank you so but i think the weeding out of how right it is won't really come until people start to move into that next step and that sort of speaks to what's going to happen i think again i've been in the industry for over 25 years you get sort of above 250 000 people are going to want to see some data off the platform, probably send you a couple of samples to analyze. They're going to have to run through a budget cycle. That could be a grant. That could be an internal capital expenditure. It could be a tender in an international location. Those are going to range from six to 12 months. So I don't think you're going to get necessarily a bolus effect. What we're trying to do is use this awareness bill now to turn into who's got samples that they want to have evaluated so that we can open that access up over the next couple of months. then people will have data to start feeding into their budget cycles so that we have you know some number not every budget request gets approved but we want to have sort of a consistent flow of those so when we look out the 27 we say okay we want to try to sell a certain number of instruments this quarter do we do we have enough budgets that are going to have a decision made in this quarter so we're thinking about it very methodically like that i still think you'll see it you know transpire in a more logical and controlled way than a bolus but um the price point definitely gives you more

valid information than being price agnostic when everyone's excited hey that's cool that's great but it's you know it's not going to be free so so the other exciting thing or the other thing that you're doing in terms of getting ready for the launch is the is a summer program where you're bringing in a handful of sites, you know, you know, a part of it is trying to get some publications from some of the KOLs. So what's the grand plan with that, you know, in terms of like, there's a very short time within you know summer and obviously some of these publications will not make it in time sure but how do you use that knowledge internally and also how much of that knowledge can be used externally in terms of detailing the product itself yeah i think it will come in two steps i think before we you know even before we place the machines in the end user environment the ability for customers to send us samples and get sequencing processed by us and and delivered back to them is the first step.

I think that obviously placing instruments in the end customer is because at the end of the day, customers want to know somebody else ran it without you involved in it and it worked. Our approach there will be to mix who we work with based on some being more academic in nature, such that they will publish and share their data. What I would say, it won't be exclusively that. We may put some into more commercial environments where they might not publish their data, but they might be willing to speak about it. In terms of how the data gets out, I think we have multiple ways to do that. We could certainly sponsor a workshop at an industry conference or do that through an analyst or investor day so that it can be presented even before it's able to be published. They could do posters or presentations at meetings. We've seen a lot of that with our Platinum machine. So we think there's multiple ways to get data out sort of in advance of the launch and then still have the flow through to the full peer review on the backside of that. Somewhat similar to what we've done with Platinum. And that's why we still have sort of a steady flow of those coming out on the Platinum device. So I think that's how we think about it. And then, you know, do we keep expanding that, you know, program a little bit all the way through the end of the year? You know, we haven't really decided, you know, how big to make that program yet, but we want to do it. There's always a chance you learn something. that would maybe cause you to do something different before you launched. But hopefully by the time you get to that stage, you're not really learning something that's major. You're learning maybe something about like a software feature or workflow or screen or something more minor that could be tweaked before you get to the market.

I know we've crossed our timeline. But just in closing, of your financial strength at this point, and the launch coming up and obviously the expenses are going to be up until the launch. How do you explain this more about how to use cash? How are you thinking through this whole process with the current cash in the bank?

Sure. So today we have a little over $190 million, which gives us cash into Q2 of 2028. So we've been very fortunate to have access to capital over the last couple of years. We've taken advantage of that and sort of always erred on the side of being well capitalized. Equally as much, we've been very stringent on cost controls. It's not inexpensive to develop a new tech like this, but we've held back in other areas to ensure we invest correctly in R&D. I think moving forward, we view two things. One is we'll continue to be, you know, sort of proactive and optimistic about capitalizing the company. I just don't know a different way to do it. It's at the end of the day, you want to be well capitalized to execute on your plans and shoulder any sort of, you know, twist and turns in the road that you might encounter. But also we've talked about on the R&D front, you know, we have leveraged for Proteus several external partners in hardware and software, in consumables. So that when we launch the platform, we have an ability to start to take out some of the R&D costs that are today being paid to partners. But when the development's over, that can come out. So that gives us, you know, an envelope, you know, for some reduction, some redeployment into commercial. But, you know, we feel good about where we are. We'll continue to be optimistic, opportunistic if it arises. But, you know, with cash into Q2 of 28, that's essentially a year and a half from launch. and there'll obviously be a lot of value creation in that time frame and we'll sort of assess what's the best sort of approach at that point.

Thank you. Thanks for having us.