QuantumSi at Canaccord Genuity: Strategic Advances in Protein Sequencing

On Tuesday, 12 August 2025, QuantumSi (NASDAQ:QSI) presented at Canaccord Genuity’s 45th Annual Growth Conference, outlining its strategic initiatives and challenges. CEO Jeff Hawkins discussed the company’s innovative protein sequencing technology, emphasizing both progress in the biopharma market and headwinds in the U.S. academic sector.

Key Takeaways

• QuantumSi is advancing its protein sequencing technology with the upcoming Proteus platform launch.
• The company is experiencing significant growth in biopharma opportunities, despite challenges in the academic market.
• New capital acquisition models are being introduced to enhance platform utilization.
• AI integration is pivotal in developing amino acid recognizers and expanding proteome coverage.
• The competitive landscape in protein sequencing presents high barriers to entry, which QuantumSi aims to navigate through expertise and data resources.

Financial Results

• Academic Market Headwinds: The U.S. academic market is facing a slowdown in capital purchases, though consumable sales slightly exceeded expectations.
• Biopharma Traction: Opportunities in the biopharma sector have doubled, focusing on the protein barcoding application.

Operational Updates

• New Capital Acquisition Models: QuantumSi is offering reagent rental and leasing options, with a six-month evaluation period for placed devices, which can be purchased, rented, or removed.
• Sales Cycle: The academic sales cycle is extended or paused, while biopharma sales cycles last 9-12 months due to integration into active programs.
• Utilization: Academic customers show sporadic use, whereas pharma, biotech, and government accounts demonstrate consistent purchasing patterns.

Future Outlook

• Product Pipeline: The company plans to launch a Version 4 sequencing kit this quarter, reducing sample input significantly, and rolling out PTM detection kits compatible with existing platforms.
• Proteus Platform: Set for launch in the second half of 2026, Proteus aims to increase feature density and reduce consumable costs, with a prototype demonstration expected by year-end.
• AI Integration: QuantumSi is leveraging AI to enhance amino acid recognizers and improve the kinetic database, training on over a million binder candidates.

Q&A Highlights

• Proteus Potential: Proteus is anticipated to have more placements per quarter than its predecessor, Platinum, due to enhanced capabilities and a broader application set.
• Competitive Landscape: The protein sequencing industry is noted for its complexity and high entry barriers, with QuantumSi’s success hinging on customer data and pipeline development.

In conclusion, QuantumSi’s strategic focus on innovation and market adaptation positions it well for future growth, despite current challenges. For further details, please refer to the full transcript.

Full transcript - Canaccord Genuity’s 45th Annual Growth Conference:

Kyle Mixon, Analyst, Canaccord Genuity: Hi. Welcome to the Canaccord Genuity Growth Conference. I’m Kyle Mixon. I cover life science tools and diagnostics for Canaccord. Please welcome me to this fireside chat with Quantum SI.

Quantum SI is developing and has commercialized the first of its kind next generation protein sequencer. And from the company, we have Jeff Hawkins, CEO. Thanks, Jeff, joining us today.

Jeff Hawkins, CEO, Quantum SI: Thanks for having

Kyle Mixon, Analyst, Canaccord Genuity: For those less familiar with Quantum SI, why don’t you kind of walk through the company’s technology vision and kind of the long the road map basically as you see this industry kind of playing out.

Jeff Hawkins, CEO, Quantum SI: Sure. So as Kyle mentioned, we’re the first company to commercialize next generation protein sequencing. So what does that mean? So we have a single molecule detection technology that detects individual amino acids. So most measurements in the field of proteomics are sort of saying there’s a protein there, its presence or absence.

They’re not giving you sort of that level of fidelity. Think of it like DNA sequencing and your ability to do a whole genome. That’s the type of approach we’re taking. Today, our technology is leveraged for more targeted applications. The roadmap which I’m sure we’ll get into today helps expand the sequencing output, the coverage of amino acids towards our end state goal which is really de novo sequencing of proteins.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And then you just had earnings, second quarter earnings recently. And you noted really throughout the first half of the year, you noted obviously headwinds on The U. S. Academic side.

And you’ve consistently had like some positive comments and I guess traction on the biopharma side too. So if you just talk about what you saw in each end market, know, year to date especially recently?

Jeff Hawkins, CEO, Quantum SI: Sure. Yeah. I think that The U. S. Academic market probably experiencing what most companies in our space are experiencing, you know, general slowdowns in capital purchasing.

On the consumable side though with our existing installed base continuing to see those customers sort of purchase at their normal pace. We actually said on our call it was a you know a little ahead of our expectations. On the pharma biotech side, you know, people are applying our technology in that space largely around something called protein barcoding. And we had, you know, launched a kit in that area late in 2024. We made that a big priority given what we saw in Q1 with The U.

S. Academic market and really grew that funnel of opportunities during the quarter. We had about 30 or so going into the quarter, exited the quarter with 60 opportunities in that space across both large pharma and smaller biotechs both here in The U. S. And some in Western Europe as well.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And then with the update on the call, you talked about some new capital acquisition like models, I guess, for customers, especially in this academic research market. You know, maybe just provide a little bit of flavor from what those are and how you know are those going to stay around for the long term?

Jeff Hawkins, CEO, Quantum SI: Sure. So you know what Kyle’s alluding to is we began just a couple weeks ago offering other ways for a customer to acquire our platform. So if we take a step back, we think a large user base, know, running this product, the technology routinely, publishing their data, talking with their peers about it is a, you know, sort of a critical part of the long term strategy. We also have seen customers who have had our instrument for let’s say three or four quarters, so about nine to twelve months. When they’ve had that level of experience and utilization, they’re the ones who are starting to come to us and say, hey, talk when am I going to get budgetary information for Proteus, which is our next platform.

So you can tell that they’re thinking about where we’re going and thinking about how to incorporate it. So given the the macro backdrop, know, having a strong balance sheet and an instrument that you know has a pretty modest cost to make, we had sort of two options. Customers were approaching us and saying, hey, we have consumable budgets. Could we send you samples? And many of people in our industry have used sort of service models but our experience is when people use it in their lab, that’s when it’s stickier, that’s when you get that sort of link over time.

So we said let’s give different options so people can reagent rent, they can lease the platform and you know in select accounts that you know maybe are key opinion leaders or maybe a really great application for the tech, we may place the device and capture that consumable revenue that that we would not otherwise you know capture if we were holding out for the capital dollars.

Kyle Mixon, Analyst, Canaccord Genuity: And there’s a decision window for the for these models too? I think six months?

Jeff Hawkins, CEO, Quantum SI: Yeah. So the way we set it up right now is if an instrument, you know, a reagent rental is different if someone signs up for that, those are normally long term commitments. If we’re placing the device and they’re just purchasing consumables, what we’ve told customers and and what sort of agreement says is that we’ll leave the device there for six months and we’ll evaluate sort of their usage over that time. If the usage is really strong at the end of it, know, some of them we hope will purchase the machine, others might move to a rental contract and continue and if somebody really hasn’t purchased sort of to our expectations, we have the ability to pull that instrument and take it to another place. You know, one thing we’ve learned in the early commercial time with the platform is we’ve been able to move it around for the purpose of evaluations and it’s very robust.

We can ship it somewhere, unpack it at the next place and it works. So it’s a fairly low risk and low cost endeavor for us if that instrument doesn’t stick, pull it out, get it to another account, let them use it and generate data. And then and again, you sort of have the options at the end of that six month period. Okay.

Kyle Mixon, Analyst, Canaccord Genuity: And then in terms of so just going back to the end markets, academic versus academic and biopharma. Talk about like sales cycles in each of those. Again, almost like the pre NIH kind of like the headwinds, and let’s also like how biopharma sort of is doing just given the evolution over there.

Jeff Hawkins, CEO, Quantum SI: Yeah, sure. So I think you know prior to the NIH funding, would say the typical academic sales cycle was around three to four months. Some people would want to evaluate the technology, some wouldn’t sort of a little bit of a mix depending on just you know specific decision makers. Biopharma was more like six, maybe nine months on the long side. What we’re seeing right now is you know academia is obviously stretched out and in some cases just paused.

Biopharma tends to be with especially with that protein bar coding application I mentioned, you know, about nine to twelve months and the reason for that is they’re implementing the barcode into an active program running it all the way through to the readout which often means through a mouse model or some other animal model to really prove out that it does exactly what they want. They can multiplex, they get the they get the fidelity of the result they need and they can sort of then calculate the savings they’re going to experience by doing it. So running through that process, you know, on one hand you can say, you know, it sort of delays the the revenue opportunity but the flip side is they’re committing that amount of time and energy and when we get that business, it’s going to be a high barrier to entry for the next person who might want to come in and you know try to take that business from us in the future.

Kyle Mixon, Analyst, Canaccord Genuity: Gotcha. Okay. And then when you think about like being like almost entrenched right now, you’re penetrating pretty well in this biopharma market, maybe better than your expectations. How do you expand within the biopharma customer beyond this like barcoding application?

Jeff Hawkins, CEO, Quantum SI: Yeah, think it’s a good question, right? Barcoding was a really good entry point. It offered them a type of result and capability they didn’t have access to. It gives them that multiplexing a lot of, you know, with some of the changes in the rules around the number of animals being used. A lot of the large pharmas have initiatives to reduce the number of animals being used.

Multiplexing is obviously a cost savings if you try to look at eight, you know, payloads at once versus one at a time and like one per mouse, there’s a there’s a cost saving. So it hits, you know, on a lot of the boxes, checks a lot of those boxes of the large pharmas certainly and for the biotechs, you know, it’s those benefits but also, you know, the platform is just much easier to run, know, it’s small and it’s a lot lower cost than say sending out to mass spec or somewhere else for some type of a result. So slightly different models but similar sort of both economic and workflow reasons to do it. The other part you asked was? Just you know, how do you Oh, extending beyond that.

So I think, you know, the next place for us, you know, as we expand the coverage of the technology and you know launch some of the kits we’re working on that will you know create a deeper sort of post translational modification discoveries to move more into discovery. A lot of what we’re in today is what it’s called candidate selection or candidate screening. As we bring out more and more capability of the tech, we can move back upstream and get even into the discovery side, the biomarker discovery side over time. So I think that’s the next place for us to go. In the biologics world, you could conceive maybe not in that pharma but with their contract manufacturing partner being used in more of a QC type of environment for those, you know, for the for the actual biologic on the downstream side.

So I think a couple different ways to go with the tech as it continues to sort of expand in its capability.

Kyle Mixon, Analyst, Canaccord Genuity: Alright. Like thus far, how is utilization the number are a little bit small, but how is utilization sort of you know differ between the academic customers and like the biopharma customers?

Jeff Hawkins, CEO, Quantum SI: Yes, so we see a couple patterns. So in academia, what we tend to see is more episodic use. So they buy a certain number of kits, they run their experiment, their study, then they sort of stop buying, they write up their data, they publish it or they present it at a meeting and then they start up their next study. So you see sort of this lumpiness buying kits then off then buying again. What we see in both pharma and biotech and also in government accounts, have a, you know, a nice footprint in the Department of Defense is a much steadier consistent purchasing pattern.

They purchase at some rate whether that’s monthly or a certain amount every quarter and they’re doing that very consistently and the number of kits is sort of going up over time. So a much more consistent pattern, you know, little longer to get them going, but once going, you know, a more consistent pattern with some level of growth on it.

Kyle Mixon, Analyst, Canaccord Genuity: Got you. Good. And then like, know, you have a handful of boxes out there that have been deployed, they’ve been installed. How are they being just like broadly, how is utilization going? I know pull through is something that you don’t want to properly quantify right now, but like is this something that’s in line with your expectations or is this like being, again, like impacted by the macro environment?

Jeff Hawkins, CEO, Quantum SI: Yeah. Well, I think we can say one thing on the utilization. We think at scale, so when the when the platform has been implemented, you know, people are running it across multiple sort of research projects, the platform is capable of pulling in about the list price of the machine per year in consumables. So our machine is a $125,000. So you know that 100 to $125,000 range is what we would expect at scale a customer would be pulling through with this platform.

You know, we haven’t given out exactly where we are today. Think to your to your comment Kyle, you know, are tracking you know the way we want. We’re happy with it. I think the adoption has been a little longer sales cycle than we like in pharma biotech, but the ones who are live with the platform, we’ve been really happy with the, you know, the purchase levels. The defense side has been very strong, probably the most ahead of our expectations and I think academic, it’s I would say it’s in line with our expectations.

It’s, you know, it’s lumpy so it’s a little bit harder to say we had an exact number there but people are you know, no one’s going sort of dark with the equipment which is what we measure. We measure sort of, you know, what’s the buying pattern and then we define as a user sort of you know idled versus active and we’re not having people go active and the instrument just sit there which has been you know challenges in this industry for many years, sort of something gets bought, gets used once and doesn’t get used again. So we don’t have any sitting in that category. So we’re pleased with that, but we’re working to continue to raise the level across the different segments.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And you launched the Platinum Pro, which is like the next gen sequencer that you have. You launched that earlier this year. I guess a little bit higher price point and it allows us like pro mode basically. How has that rollout progressed?

You know, has that storyline kind of progressed so far with customers?

Jeff Hawkins, CEO, Quantum SI: Yes. So it offers two things. It offers pro mode which you mentioned Kyle, which is the ability to use our technology sort of in an open mode. So if you break down our tech at the most fundamental level, you know, we’re essentially an exquisitely good technology for single molecule binding kinetics. We’re applying that to sequencing but there’s a lot of other applications where people want to measure binding affinities and our tech is sort of an alternative to some of the other options that are out there to do that.

So we opened up a channel, gave people access to the dyes, opened up the software so that they would be capable of doing that type of work. The other thing the Platinum Pro offers is some customers, especially when you get into pharma biotech or you get into defense, they will not, they’re not able to connect your machine to the cloud and all of our analysis tools sit in the cloud. So the Platinum Pro gives people the ability to do onboard analysis and not need to be connected to the cloud. So that you know helps when you’re trying to implement in one of those environments where someone doesn’t have cloud connectivity or has a you know firewall that doesn’t allow for it. You know, so far it’s gone well.

We you know continue to sell through the last of our platinum units and you know, so we have a mix right now. Some people buying the legacy platinum machine and some buying platinum pro, but we’ll soon here be sort of out of that inventory and it’ll be exclusively Pro’s moving forward.

Kyle Mixon, Analyst, Canaccord Genuity: Got it. And then also on new products or pipeline. So we have, I think you’ve like a V3 library prep kit coming out soon. You also have the V4 sequencing kit coming out soon as well. You keep rolling these like these versions out of these kits.

What’s the kind of the goal, the end game when it comes to like having all these kits roll out? I mean, given you don’t have like a ton of place like placed boxes, it would just seem like maybe you don’t have to do like a new version every several months. But like why is that necessary for this type of technology?

Jeff Hawkins, CEO, Quantum SI: Yes. I think our approach has been continually improving the technology. So the new sequencing kit, the Version four kit which we expect to happen this quarter, you know really does two things. It continues to expand the amino acid coverage and it also allows us to cut through the amino acid called proline. You know for the deep proteomics people you talk to core labs, you know, proline rich proteins, antibodies, membrane proteins, these are very difficult to analyze with mass spec.

We’ve historically not been very good at those either because we couldn’t cut consistently through that amino acid. This kit will do that. So it’s going to open up some new applications of our technology in an area that is widely, you know, desired to be studied but very, very difficult to do with existing technology. The version three library prep is really about lowering the sample input. So, know, lot of our customers to date have worked with, you know, recombinant proteins, you know, maybe you know, not super complex biological samples, higher concentration sort of proteins.

The new library prep, we expect to lower that input by more than a 100 fold, which is really going to let us get into more complex biological samples, more complex mixtures, know, so things that we think opens up new opportunities. Our general strategy has been this sort of steady cadence of improvement, but the other thing happening in the background that often doesn’t get much attention or credit to the people doing the work is over the last two years, we’ve brought up and in sourced all of the manufacturing capabilities to make these kits and what that is going to allow us to do going forward is really start to look at sequencing kits perhaps as more of just a continuous improvement to the kit rather than having to do these in chunks. So each time we identify a new recognizer for a new amino acid rather than having to sequence it into a kit because of lead times with vendors etcetera, we can flow it in in more of a continuous fashion and we think that could be very beneficial for our customers. You know, we’re in research markets so there’s not some of the complexities there are for clinical customers.

We can turn kits over and people tend to adopt very quickly. So, you know, I think we’ll look to move to a more continuous process on that front and then with the library prep combined get into some of these, know, lower concentration complex biological samples.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And then you also are going to roll out PTM detection kits, know, in the next like in a few quarters, let’s say. You haven’t provided the exact timing. That’s kind of that’s been the PTMs have been viewed as this like killer app on most important sequencing or one of the killer apps. So what is that how does that how would those kits really expand your customer base or product opportunity, let’s say, and also expand like your revenue per customer potentially?

Jeff Hawkins, CEO, Quantum SI: Sure. Yeah. I mean, PTMs and single amino acid variants are sort of what people really want to deal with protein sequencing, especially if you’re in you know a developed market like The US or Western Europe. I think when you get outside of those areas, you know protein identification, quantitation becomes you know more interesting to customers because they don’t have access to other existing technologies. On the PTM front, know we have some customers who have already published either in preprint or peer review on the use of our tech for PTMs, but you know sequencing today doesn’t go 100% of the way all the way through the you know the protein or the peptides and we don’t have a 100% coverage today.

So one of the things we showed at our Analyst Day is the ability to combine modalities, meaning we can do a pre sequencing detection run and probe for PTMs anywhere in the peptides then move into a sequencing run, combine that data and get even deeper sort of profile of those peptides and of those proteins in terms of their PTMs. So what we announced on our call and what we’ll share more data on sort of the exact roadmap and timing at our Investor Day coming up in November is really how do we see those kits rolling out? How broad could this be applicable you know to various PTMs? But you know based on the feedback we’ve had from customers, this is really an area that outside of a small number of people who have sort of the highest in equipment, you know sort of bespoke pipelines on the bioinformatics side, this is not really something that’s reproducible and routinely able to be done in the market. So, we think it represents a really good opportunity both on the translational side in academia, we think it could start to open up some of those discovery opportunities on the pharma side and we’re sort of excited to share some more coming up and then roll out those kits soon after and see how the adoption goes.

Kyle Mixon, Analyst, Canaccord Genuity: Yeah. In the PTM detection, know, basically like reagents, those are going be compatible with Platinum and Platinum Pro or with the Proteus?

Jeff Hawkins, CEO, Quantum SI: With Platinum Pro and then they will also port over onto the Proteus device.

Kyle Mixon, Analyst, Canaccord Genuity: All right. So the Proteus device that’s going to be launched in the 2026, different architecture. It’s an optics based architecture compared to what the kinetic space that the platinum devices are based on basically. So with the fluorophores and so forth, so maybe talk about like the development of Proteus so far, how that’s gone? Because you announced it like late twenty twenty four and you’ve given almost a two year kind of like roadmap.

So how is that progressing?

Jeff Hawkins, CEO, Quantum SI: Yeah. So I think maybe just on the technology side. So our existing system, the consumables, you know, sort of basically like think of it like a digital camera, a CMOS chip with nano wells over the top and then it’s placed into a device that because the sort of the optics of the device are in the chip, the instrument itself is a pretty, you know, simple device, has a laser, has the electronics, the collection, the processing of data. When we go to Proteus, the consumable becomes a very simple sort of you know fused silica substrate with nano wells patterned over the top and then the optics go into the machine. So a couple reasons to do this.

One is we can get to a significantly higher density of features of these of these nano wells and that’s important as you think about getting into more and more complex samples and wanting to see more and more proteins per sample. You can also do that at a significantly lower cost to make that chip than it cost to make our current chip, which gives us a lot of pricing sort of leverage whether that’s to get business in certain accounts, whether that’s for future, you know, competitive sort of defensive reasons, we sort of have optionality with that type of price point on that on that side. You’re right, we announced the program at our Investor Day in November. It’s really probably one of the faster programs I’ve seen in the industry, which is something we started in sort of in the 2024 and we’re saying we’re going to launch it in the second half of next year. We feel comfortable with that expectation.

So that you know about a two and a half year long program for a complete architecture change. But the reason we believe that’s feasible is a lot of the parts we think are even harder to do in our field. The surface chemistries, the recognizers development, the enzymes, the manufacturing infrastructure, all those things are in place with Platinum and Platinum Pro and they poured over into the Proteus program. So really what we’re changing is the consumable engineering architecture, but a lot of the other aspects of the technology are directly portable into that. We’ve been giving milestones throughout the year.

The the big one before the end of the year is to demonstrate sequencing on a prototype platform. So we’ve said we’ll do that by the end of the year. We, you know, feel very good about that milestone. And you know, assuming we hit that milestone then being, you know, in good shape to be able to get the platform out, you know, before the 2026.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And just as we think about like projecting that product, let’s say, why would Proteus be shipped more, placed more per quarter than Platinum would?

Jeff Hawkins, CEO, Quantum SI: Yes. I think Proteus is maybe backing up one step, I think Platinum, was brand new tech into a brand new market. I think, you know, you’re doing a combination of market development and learning about your tech. You’re evolving it and improving it over time. I think we get all that learning as we go into Proteus.

We know more complex samples and more proteins per sample is things customers want to do. That’s something that will only be unlocked when we get to Proteus. And I think the other piece of it is we know sort of that menu of applications we want to have, know, the capabilities around PTMs, the capabilities for those more complex biological samples, know, even higher flexing barcoding. So we feel like we can come to market with a really robust set of applications. We think we can get the you know the pricing right for each of those markets in terms of the consumable side and you know we feel we feel good about it.

Obviously, we’ve got to do the work to build into that. We’re going to want to pull customers into the development process throughout next year so that you know, people have used it and run it and have data before we even launch. But you know, think it’s it’s a project and we just have to keep plugging away at it and and you know, launch it on time with that customer engagement all the way.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. And then you’ve also discussed the use of AI models to develop like amino acid recognizers that will help you expand your coverage of the proteome. I guess what is that? How do you kind of commercialize that? What’s the kind of roadmap to do that and how important is that going to be?

You know, in a in a industry where there is no reference proteome, why how important is like AI going to be?

Jeff Hawkins, CEO, Quantum SI: Yeah. I well, I think AI we use AI in two ways. One is in the development of the recognizers that bind to amino acids and that’s what we talked about and I’ll expand on that in just a second. The other is we use it in the development of the kinetic database and that’s sort of what you expect to see in when you see the sequencing reaction happening. So that allows us to sort of evolve the detection algorithms and improve that over time.

On the internal front, you know, I think people talk a lot about using AI and AI tools are obviously out there in the public domain, but even more important than the tool is the underlying training data and what we talked about on our call is, you know, the last eight years, the company’s screened over a million different binder candidates. So we have all this data about when you insert mutations into a protein, it behaves in the following way. It binds to this amino acid, it doesn’t bind to this one, it has this stability profile, it has this manufacturing sort of success. What we’ve done most recently is taken that data and trained AI on that to generate an AI designed binder and we did that and saw a significant improvement in our first candidate of a binder that sort of isn’t even in the ballpark of what you see when you try to develop them using more classic techniques. So what we think that’s going to do is allow us to really go from where we are to complete proteome coverage in a much faster period of time.

You know, we’ve got some case studies in the works that we’re going to put out to try to elucidate this a little bit more and then at our Investor Day in November really try to help quantitate that for investors of what’s that mean, when exactly do you think you can get to that whole coverage, but you know, we think it radically reduces the number of cycles we need to go through to develop coverage for, you know, to get from where we are to complete coverage of the proteome.

Kyle Mixon, Analyst, Canaccord Genuity: Can you use something like AlphaFill to like help, I guess, or

Jeff Hawkins, CEO, Quantum SI: is it You can use these tools. And again, we’ve been using AI tools, like we have a computational biology team, we’ve been using these tools but I think the big breakthrough is training these tools on this very rich set of data that we have that, you know, these tools coming off the shelf don’t have access to this data. This is all proprietary. This is our internal data generated through, you know, years of empirical work in the laboratory across many different orthogonal methods. So the tools are there, but the the real lift we saw was when we trained it on our internal data and generated candidates with that and then tested those candidates in sequencing.

Kyle Mixon, Analyst, Canaccord Genuity: And the rich data comes it’s just because like you’re, you know, you’re just sequencing We’ve

Jeff Hawkins, CEO, Quantum SI: been doing we’ve been doing binder development for almost eight years. So we have we have sequencing data, we have other, you know, we have data from our directed evolution program, we have data from other orthogonal methods to look at binding kinetics on off rates. We have data on any of these that have ever gone into manufacturing, what is stable, what’s not, what’s, what’s easy to express or not. You have an amazing amount of data when you’ve been doing this for this long and if you give all of that to AI, it’s able to take that into consideration when it’s designing the next the next binder.

Kyle Mixon, Analyst, Canaccord Genuity: Is like half a million samples have been

Jeff Hawkins, CEO, Quantum SI: Over a million, over a million sort of candidate binders have been screened in the history of the company.

Kyle Mixon, Analyst, Canaccord Genuity: Okay. Interesting.

Jeff Hawkins, CEO, Quantum SI: So it’s a big body of data that’s available for us to to tap into. Alright, awesome. Finally, what

Kyle Mixon, Analyst, Canaccord Genuity: are investors and maybe even academics or customers underappreciating about Quantum SI in this whole protein sequencing industry that definitely is early stages but could be super promising?

Jeff Hawkins, CEO, Quantum SI: Yeah. I think I think people are probably, you know, underestimating, you know, really what the true potential could be. I think they’re some of that’s tied to I don’t think we’ve yet really helped people understand how different Proteus is going to be in terms of its output and its capabilities when combined with the level of sequencing improvement we’re making in parallel to that. So I think that’s something we have to help bring to light in the market over the coming year. The other side is I think it’s a much more difficult problem to solve than people think and I think because of that, the barrier to entry for others is very high.

This is a extraordinarily difficult problem. You have to have talent density across so many different areas on the scientific side to pull this off. So I think some people might be under calling, you know, the risk of sort of like how quick people will get here. I think it’s very difficult to do, you know, sort of competitive fears might be overstated by some in that regard. And then I think, it’s also a market development and we’re doing it.

I think the data is coming out, the pipeline of data from customers looks good and I think that’ll come out over the next few quarters and help as well.

Kyle Mixon, Analyst, Canaccord Genuity: Okay, that’s great. Let’s leave it there. Thanks, Jeff. Appreciate the time.

Jeff Hawkins, CEO, Quantum SI: Yep, thank you. Thanks.

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