Archon's Jamie Lazarovits on Unlocking the Full Power of Antibodies With AI
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The quality of your investors, the quality of the people that you have around you are going to be the critical determinant in you actually being able to execute on this. If you think anything is hard in academia, multiply that by however many fold you want once money is on the table, once the stakes are a lot higher, once you can't just happen to write another grant to keep people working in your company.

Welcome to Founded and Funded. I'm Chris Picardo, a partner at Madrona, and today I have the pleasure of hosting Jamie Lazarevitz, the co-founder and CEO of Archon Bio. Archon is a company Madrona partnered with truly on day one to spin out from David Baker's lab in the Institute for Protein Design at the University of Washington.

They have leveraged cutting edge protein design from the IPD to develop a brand new therapeutic modality with the potential to massively transform how we think about treating many categories of disease. This is no easy task, and today, Jamie and I are going to dive into how he pivoted from bootstrapping deep tech investments to biotech, how he landed at the Institute for Protein Design at the University of Washington, where he worked with David Baker, who just won a Nobel Prize, how to navigate translating an academic project

into a commercial product with a clear business model, picking your co-founder and building your team, and of course, how he's building novel types of drugs that will get more treatments to more patients. This will be a great conversation for those interested in startups, whether biotech or not. And so with that, here's Jamie.

It's really great to be here. It's pretty exciting to finally have the opportunity to talk about who we are. We've been maybe not that great of a kept secret, but it does feel good to finally share who we are. Okay, so you have told me many times that you actually started in the sort of startup and tech world by bootstrapping investments into deep tech companies.

How the heck did that happen? Yeah. So my best friend when I was in my late teens, he started a software company and he happened to do pretty well. And I had some money from my tuition as well as from scholarships and decided to start day trading.

And this was pretty exciting because we had never really played around with something like this before, but we thought, why not just do something more mathematical, actually see if we can figure out trends in the market. And at the time, we were playing with kind of penny stocks in like the rare earth market. And that was...

a lot of fun, we did relatively well. But the problem was is that what we realized is it really was gambling at the end of the day and we weren't actually able to see underneath the hood, did these companies have substance? And what we also realized was that we weren't as excited by just making the money. We actually wanted to understand how these people were thinking, what they were doing.

And because my friend had this software company based out of Waterloo in Canada, which is a very big engineering school, and we started speaking to a lot of early stage founders who had amazing ideas but didn't quite have the right capacity to communicate what they were doing. And because my friend and I were so interested in actually understanding what's going on under the hood, we decided to take...

our tuition money, the money we made from day trading, the money he made from his company to just start investing in these companies. And we ended up doing this in about 10 different companies. Some of them have grown to over 100 employees with multiple tens of millions of dollars a year in revenue. It's kind of fun that you got a little taste of our side of the table.

Totally. And some of those companies are still going. And, you know, I think that's super interesting. Not many people have this sort of accidental venture capitalist interlude between graduation and, you know, going to, you know, get your PhD. But I think, you know, it'd be a little interesting to talk about sort of how you made that transition. You were working with these deep tech companies and then you decided that you're going to go to grad school.

Yeah, so I was working with these deep tech companies. A lot of them were really focused on AI, came from Toronto. So obviously machine learning is very big over there. So big in AI, big in hardware. It was very interesting thinking about how do you translate deep tech products to solve real world problems.

And I was working at Harvard and my roommate, his mom invented this device that profiles maternal blood. So instead of a woman having to go for an amniocentesis, you were able to just profile her blood and then you could actually determine if potentially there was something wrong with her child. And I found this really amazing because it actually

opened my eyes to this opportunity of using engineering to solve really important problems in healthcare. It inspired me to think about how could I actually take this deep tech stuff that I had learned, how do I take this passion that I do have, which is another story we can talk about for biotechnology and medicine and healthcare,

and integrate that together to actually find something that is bigger. And I ended up finding my PhD supervisor, who's a world expert in the delivery of materials and nanomaterials. And I went and did my PhD with him because it just, it felt right. I also know that you have sort of a more personal reason, right, for being super excited about the biotech and healthcare side of the world. And I think it would be great to just sort of share how that put you on the path more towards biotech and then eventually to the IPD. My mom would say that she'd be incredibly upset if I told her that I failed my family.

for doing a PhD, but if I would have become a medical doctor, I would have been the seventh generation in my family. My father was a physician scientist and when I was about seven, he was diagnosed with brain cancer and he was pretty fortunate because he was able to survive two years with that. But if you have a certain type of brain cancer, glioblastoma multiforme, it's pretty much a death sentence. It's like a 99% mortality rate.

But, you know, in line with him dying from brain cancer, at the same time, he was also doing absolutely incredibly impactful science. And he was an immunologist by trade, worked in organ transplantation, and was one of the first people to actually develop antibodies.

And he actually developed an antibody that is now one of the most successful biologics on the market. It's called Intivio. And obviously he was not here to be able to see that go public. But one of the big things that it taught me was that having impact is possible.

I think sometimes in life, you're taught that these things that you want can't happen. But when you actually see something that is tremendously impactful and can help people and improve people's lives happen, it doesn't in a certain perverse way actually show you that it's possible, even though you could have maybe believed you could do it beforehand.

And so since he wasn't there, I took a lot of the responsibility of navigating with these different agencies because obviously it's a pretty big deal if a medicine goes public or gets FDA approved. And it was really exciting for me because it was, again, this like theme of integration brought me into experiencing what it's like to actually see a drug get approved, see what happens when change is real, integrate that with both like my

learnings as a student as well with me bootstrapping this deep tech and one of the big things that it came back to is that uh

I wanted to have impact in a way that people wouldn't have to go through what I went through historically. One of the ways that you can do that is you can work with the individual, but if you're working on engineering or technology solutions, you don't actually have to do that. You can actually have impact beyond it. I think it's an incredibly powerful story and constant source of motivation. I think for me, I just get lucky that I get to work with founders like you who are so driven to solve those problems.

You know, it's vicariously motivating for me, certainly. And, you know, before we get to the Archon story, which obviously we're both super excited to talk about, you made it to the Institute for Protein Design where you met your co-founder. You know, maybe just give us a little bit of insight into both what the IPD is for kind of those of our listeners who don't spend as much time in the world as you and I do. And, you know, how you got there and how you and George met.

Yeah. So the Institute for Protein Design, when I first moved there, it actually felt like the...

physical, mental, psychological manifestation of the Yukon Gold Rush. It just felt that like when people were there six years ago, that they felt that they were a part of something big. And there was just like this substance that you could feel in the air that people really felt that they were going to have impact of the things that we were working on, really had the ability to change how we live. And the Institute for Proteas Design was spun out of

really David's group and where he has this unbelievable superpower is that he is just good at attracting good people. Turns out that's actually not as easy as it sounds. Because of the magnetism of the excitement of the technology, but also people to be enabled to pursue science creatively, it's built this institute where people pursue design, computational protein design to solve problems but

without predisposition of what those problems are. So people can come into the institute with complete and open creativity, and that's encouraged. And what's really cool and interesting about it is that it's very rare to be able to go somewhere where you are completely supported and financed to be creative, imaginative, and be given everything that you need to do in order to get things done.

And maybe do some awesome protein design along the way. Yeah, just for everybody, we're talking about David Baker, who is the founder of the Institute for Protein Design and really invented the modern version of the field. And you and your co-founder, George, were part of that sort of along the way. Do you want to talk just for a second about kind of how you and George met? It's kind of a serendipitous story and why you got working on the Archon technology.

The interesting thing about life is that there's only so much that you can plan. The big part is just being open to opportunities when they present themselves. In this case, this was anything but an opportunity. There was a going away party for someone who had been working at the IPD and this is about five and a bit years ago.

And I just so happened to sit next to George at a dinner table and we were both drinking a beer and he had made some comments about being half Japanese. And I'm like, oh, I just came back from Japan. And really, we just started talking about, you know, our passions and the things that we were interested in. And it really had nothing to do with any professional overlap. But we got along really well and decided to, I don't know, chat the next day at the Institute. And what we realized is that he was actually working on some pretty cool technology. He...

architected the technology with members at the IPD. And the problems that he was speaking about were very familiar to the types of problems that I saw in my PhD. And because he was such an interesting person and easy guy to chat to, I just started to pursue it and just

you know, posit is there, you know, cool opportunity to maybe do something together here. Yeah, I know we'll get to this in a little bit because we can talk about how you and I met, which is somewhat similar, actually. But I think it's interesting that, you know, there wasn't pre-planning involved. You didn't go to the IPD with the idea of, hey, I'm going to start a company. You didn't go search out a co-founder at the IPD with the sort of baked in idea. Like, yeah, we have to find a company to start just to, you know, spin this thing out. Like,

You guys met at dinner and started working on really cool technology.

So part of that is true. The other part that is not is that when I did leave my PhD, it was a really hard process for me to figure out what I wanted to do with my life. When you have lots of opportunity, you know how to make a decision that means actually you aren't gonna be doing anything. And my friend Carl, who's a co-founder of a local company here in Neoleucin, told me that I need to come here, told me that protein science is the most amazing thing that I need to be aware of. And this was seven years ago.

And when I spoke with David and Lance Stewart, who is the ex-Chief Strategic and Operations Officer at the IPD, I told him that I had this really strong desire to be able to build a technology that has impact.

But the amazing part of being able to use computation was that you could explore space in ways that you could not have done with other types of technologies. So I did come to the IPD with a feeling and a notion that I actually wanted to have impact, I wanted to translate, but it wasn't at the expense of doing something that had quality. So, uh,

I guess like 50-50 there. I remember visiting you guys in that tiny office where you sat like six inches apart from each other and it was boiling hot and being like, how do they get any work done? Yeah, when you do that for four years, you get pretty used to it. Yeah, well, I know we've talked about your background a lot and gotten here and I think that's important, but now we...

get to the really exciting part, which is that for the first time, you were going to talk about Archon publicly. And we've announced the company, we've announced the fundraising. I think there's a huge amount of tailwinds behind what you're doing. And so let's dive into what you're actually doing. What's the revolutionary technology? I'm going to give you the space to sort of describe out loud what you're up to and why we're so excited about it. But

We have to talk about the fact that David Baker just won the Nobel Prize, which I think is a phenomenal achievement and honor for David and the IPD and Seattle and

and everybody that has worked with him along the journey to get there, which I know is not over. So maybe start with the work that George and David, you know, George being your co-founder, were doing at the IPD for, what is it, the 11 years that George was there before Archon? I think the most interesting thing about what protein design was is that it wasn't designed with...

the intention of application. It was more from this like mathematical, almost artistic pursuit of can we do this? Can we make structures that have never existed in nature before? Can we represent, you know, beautiful shapes out of amino acids that give rise to proteins? And the really interesting thing is, you know, back in the day, just even being able to put little pieces, little Lego blocks of proteins together was incredibly difficult to do. And

where the field was about seven, eight, nine years ago was that. And then as complexity began to increase, it was like, okay, well, can we add on to the complexity of the types of structures that we can make? And then

It took a lot of insight from people like my co-founder George and other really spectacular members of the IPD to start asking the question, "Okay, well, if we can make these shapes, is there a chance that these shapes can do something?" There's this really fascinating transition where George invented vaccines that are in the clinic right now. He was one of the first people to be able to show that you can use a design protein to tune the way a cell behaves and communicates.

And now we're at this completely whole other side of the coin where we now have this like public affirmation and confirmation that protein design is big. It's impactful from a scientific and technical standpoint. But now the next step is, okay, what can we as a community do with it? What are the real problems that we can solve? And that's where companies like Archon fit in. I think that's a perfect transition. And so, you know, on the theme of design proteins that can do something,

Maybe give a description of what Archon is, what are ABCs, what's sort of the underlying innovative technology that you guys have built? So Archon is a biotechnology company that has created a new class of protein-based biologic to solve significant problems in the medical space that other technologies cannot.

Antibody cages or ABCs are at this intersection of generative protein design and molecular engineering. They help resolve a long-standing problem in science with this unique engineering solution. And this long-standing problem in science is how do you make a drug that gets to where it needs to go, doesn't go to where it shouldn't, when it's where it needs to be, it stays there,

and it does its activity properly yeah it turns out that's like actually an incredibly difficult problem to solve you've reduced drug development into the simplified form but that is that's the game right exactly and if you study over you know decades and decades and decades in the pharmaceutical industry what we've learned is that it's the shape it's the size it's the

diameter, the flexibility of a drug influences the way it travels inside of the body. Okay, so it's super interesting. You can, by just changing the shape of the ABC, change the efficacy profile, the delivery profile, you can get these antibodies to where we want them to go and engage with the target totally differently. And then what? What effect does that have, the ability to do that on sort of the underlying disease or pathway that you're trying to modulate?

Well, fundamentally comes down to what we call the therapeutic window. It's a balance of on target versus off target effects. What does that mean? So if you've, you know, you look at people that have taken chemo and they lose their hair, that's a consequence of how the drug works. And the reality is, is that the drug just distributes to many, many different places. And

And so you have this balance of how much drug can I add that gets me the profile that I want and how little must I have in order to not have all of these like super negative effects. And by changing the geometry, by changing these unique properties of our structures, we have this finer ability to tune either going up into our desired site or

or away from those sensitive sites that are actually going to cause some of those worse side effects. And so it's this bio-distribution enabled, what we say is a modulation of therapeutic window, which is a huge opportunity in a variety of different therapeutic areas that either get

too much or too little efficacy. Because if you have too much of something, you can get a lot of toxicity and too little of something, you're the safest drug in phase one. And just to clarify for everyone, because I've gotten to see all the visuals and it kind of helps, what you're really talking about here is sort of the underlying cage that you've built out of proteins, which can take any number of shapes. It could be a pyramid, it could be a cube, it could be a

icosahedron, right? Sort of, you know, classic geometric structures that you're able to sort of

linked antibodies into naturally, so therefore they're fixed in, you know, kind of geometric position. Exactly. Yeah. Thanks for bringing that up. So the antibody cage system is you have your antibody of interest, you have your design protein of interest, and you just mix them together. And they spontaneously form this rather beautiful, geometrically defined structure. And it's the geometry of this structure that dictates how it travels in the body, how it interacts with its tissue, how it

elicits its behavior. And turns out making that is actually very difficult, if not impossible without the advent of these computational protein design methods. And now you can make a lot of them. We make a lot of them. So the core innovation that we've done is not only on the back end AI, but it's also on the manufacturing.

And sometimes when you make a technological solution, sometimes you overthink of actually how it can be integrated. And one of the core things that we tried to do when we were making this technology is how can this be as easily insertable into downstream manufacturing of antibodies as possible? Antibodies are the largest class of therapeutic in the biologics market. And often when you change an antibody, you lose all the features that made it great in the first place. So we tried to ask a pretty simple question. How do we not do that?

And that's where design, that's where our unique manufacturing has come in is because we now can do that. We can make

any number of these, but fundamentally it's using AI to solve a very defined problem that not only allows us to tune biology, but it allows us to tune biology without compromising manufacturing and production of the therapeutic in the first place. We'll get into this tuning topic because I think it's particularly interesting and it's a theme that has started to come up with a lot of AI plus biotech companies. But one of the ways that I think about Archon is essentially,

unleashing the full power of antibodies.

that might not be our actual marketing tagline, but it's... Antibodies transform. Antibodies transform. That's our tagline. But can you give a couple maybe non-technical examples of sort of why this cage structure with antibodies just elicits a totally different type of behavior or what you can achieve that you can't with an antibody alone? So I can give like an ultra colloquial example. Sure. If I yell at you and tell you to do something, you're probably not going to be that

enticed to do it, but I have to ask you nicely, you'll maybe be more interested. So it's the structure and the composition of how I ask you to do something really matters, even if it's the same words. And what we found on the cellular level is that it's structural. It's explicitly how you ask the question, how you interact and engage with the cell that determines its proclivity to actually do something for you. So you're saying, you know, hey, if you have one antibody that

that is just, that's the drug and it goes to a target of interest on its own. It may be safe, but it might not have any effect. Exactly. If you stick it in your cage,

and you bring several antibodies in a very geometrically specific confirmation to that target of interest, you might be able to elicit a massively different effect even from the same underlying antibody. Exactly. The most interesting thing is because we can control the structure, we actually have the ability to tune across the entire plane of behavior. If you want something that's super strong, if you want something that's super weak, if you want something that's in the middle, you actually have the ability to do that. That's actually because of the power of this geometric control and tunability.

that I'm talking about. This is one of the things I get so excited about and you and I have talked about forever. But if you think about the old paradigm of, hey, if you want to try to figure out the range of what antibodies are going to do, you have to, you know, maybe mutate them one by one, do this in parallel.

And it takes a long time and you might not get great data. You might not even get any of the results that you want. And what Archon has said is, hey, just take those same antibodies and let's try the entire spectrum of geometry. And we can show that just based on the shape, we can get very different types of behavior out of it. Like, I think that's an incredible fundamentalism.

fundamental approach to how you're thinking about building products. Totally. We like to say that we're trying to turn drug discovery into an engineering problem in the sense that if you decrease the probability of failure, but actually even being able to generate one of these structures, you can actually just ask the pretty basic

science or clinical questions. How do these pathways work? What did failure and success look like in the clinic? And is there a way that you can generate a molecule to be able to hit specific metrics that you actually want to get? So it totally redefines this whole notion of a TPP because classically or target product profile, excuse me. So often what happens is you have a molecule and it has its behavior. And

The question is, is like how how much can you modify it in order to get a desirable profile that you want? And every time you modify it, something else probably goes wrong or at least changes in a way you didn't expect. Exactly. Yeah. And so from our case, we actually take it from a slightly different perspective. We can start

To begin with, we're not going to be talking about our programs today, but for our lead programs, we're starting with very well characterized and understood biological pathways where we've actually seen how these types of molecules behave in the clinic. And by starting from first principles of how does this biology transform or translate into

a clinical setting, we can actually recursively go backwards and actually ask how do we change structure in order to move towards or away from that specific behavior. And so then ultimately what you were creating are drugs that are fully owned and developed by Archon to treat diseases or to go after targets that were otherwise, you know, not other modalities weren't able to hit.

Exactly. The nice thing here is that antibodies are increasingly commoditized. And from our standpoint, what is wholly unique is that we actually own this design and manufacturing process to generate the ABCs. So it gives us the opportunity to choose which program areas do we want to own, which ones do we want to go into, and which ones are we going to be open to potentially co-develop with if that's of interest. Yeah. But ultimately, you know, we'll have sort of

a pipeline of our own internal drug candidates that are Archon and maybe a couple things that we decide there are really natural partnerships out there with larger pharma or people with great disease insight or biology insight that we can work with. Exactly. We have an internal pipeline right now, just not talking about it today. So I think this is kind of a great way to talk about where AI plays into the story. I mean, at the IPD, you guys have built processes

pretty much all of the fundamental generative protein design tools that are out there, certainly the IPD and DeepMind are the leaders in the space. So you have your hands on kind of everything or both hands on them and have built them yourselves right while you were there. And so how does AI fit into the story? AI fits into the story because it is the crux of how we solve the problems that we do.

But AI also isn't the be all and end all. I think that there's this misnomer in, let's say, more of like the information sciences space that we can just like throw these models at biology problems and they're going to be inherently useful. But the thing is, it's a highly multivariate, multifactorial space that you don't even know the implications of what you're doing.

doing has on an even more complex and chaotic system like the human body. We've been incredibly fortunate to be surrounded by like the best and brightest minds in the protein design space, but not even protein design. It's also all these people from all these different unique backgrounds that just

aggregate at the IPD. But the big thing that George and I were focused on were, how do you change and control structure? How do you change the control distribution? And how do you do that by not compromising these desirable manufacturing features that we like in the first place? So AI has massive power. It's hugely enabling, but it also has to be constrained at first in order to know how to use it and for what problems.

Yeah, I think one of the concepts that you and I talk about a lot is sort of the product-led platform. AI is deeply embedded into everything you do, and it's not the product of Archon. And for the non-biotech part of our audience,

We've talked about this a lot. There's a lot of AI and software and compute sophistication going on under the hood here. Yeah. So we've been very fortunate again to come from the IPD. And in particular, I think what really differentiates us is this extreme focus on these particular problems, especially in these target classes that have

There's well-characterized biology, but again, we view that we're leveraging these models in a wholly unique and differentiated way. I know that everybody can now check out the new fancy website that's up and live if you want to see some good examples and animations of what this looks like in practice. Switching gears a little bit, I think for the rest of our conversation, we can talk a little bit about the company building side of this.

And as we sort of hit on before, I mean, these companies don't really they don't come from nowhere, right? Like there is a lot of building and process that goes into it. You and I knew each other for two years before, you know, we started the company, right? Effectively, you started the company and we provided the capital to help you do it. But we spent a lot of time talking about this beforehand. And so.

I think to start, how do you think about translating the academia and what work you and George were doing at the IPD to the commercial world? What have been the major learnings and insights that you've had now on this journey for two years post-IPD?

So the first thing that I learned when I was doing my, you know, deep tech investing bootstrapping days was the importance of framing a problem, understanding the problem that you're solving and knowing when to ask for help. And I think the third part was really big is that academia, you know,

David at the IPD will talk about this communal brain and everybody benefits from this communal brain, but fundamentally in the academic setting, it's very individualistic. So you are almost devalued from working with many people because your currency is your first authorship. And so it's very difficult to know how and when to ask for help.

if the system itself is almost pressured to de-incentivize that. So one of the biggest parts is that there is this ego associated with being exceptional, being able to build things yourself. And when you're trying to translate a really sophisticated technology, it's just not possible. You cannot develop it yourself. So one of the first things that you kind of have to switch is

You mean you need enough of an ego to think you can do something that nobody else has done, but not so much of an ego that you don't know how to ask for help. And so you have to find people that can really benefit you and transform your perspective in a way to solve problems that you may not have had the predisposition of solving before that. What's a good example of asking for help?

I know, you know, for the people who are still in academia or still thinking about starting a company or making this transition, you know, do you have an example from sort of your own process here where like asking for help might have been hard, but was totally the right thing to do?

Well, I think probably the biggest thing is that I spoke to George and I said, "George, I am not the best protein designer, but you're really freaking good." But I'm able to conceptualize and focus the problems in completely different ways based on my technical background. And so instead of me trying to

can find him, what I actually did was try and find a way to enable him and enable myself where we could solve different types of problems together that actually allowed us to do better faster. And so a big thing for me was that, you know, I'd been working in design for a while, but finding someone that was able to compliment me in a way that really enabled me to be better

allowed me or forced me to look at, you know, what was I good at? What is he good at? And is there a way that we can actually benefit each other? Yeah, I think that's a kind of a very powerful message about sort of putting together the complementary founding teams and playing off your co-founder really well. The other thing you guys did that was, I think,

unique was you weren't ready to start the company for a while. Yeah. Like I said, we met each other two years before, I think you technically really started the company. I think I swung by that small office a lot and we'd have a chat and an update and I'd be like, "Hey, are you guys ready yet?" You're like, "No, not yet." Then finally you were. So what gave you the confidence to say, "Hey, we are ready." We made that go, no-go decision and now it's time.

We viewed that decision matrix and this lens that they're

Maybe some engineers will take offense to this, but it's fine. I'm an engineer. So there are science problems and there are engineering problems. And a science problem is something that we view as having a nonlinear relationship between input and output. You can put tons of effort in, but you don't actually know if you're going to be able to solve it. Or if you are, you don't know how long it's going to take. We view engineering problems as those that you've actually confined and constrained the space, and you know how much effort it requires. It's just a matter of the input

In our case, we didn't want to be entrepreneurs and build out this technology for the sake of it. We understood what we needed to overcome. We understood the problems that we needed to solve. And for ourselves, there is this integrity piece where we said, if we can show to ourselves that we can

you know, resolve and implement these unique features of the technology to solve these types of problems, that we would have the conviction to stand behind it. And we were given a really hard time during the COVID bull markets. You're like, you're crazy, you're working in protein design. How could it ever get hotter than it is now? Turns out it got a lot hotter. It got a lot hotter. And what we did is we really followed the data. And by doing that, we felt that we really presented ourselves as

people that could be trusted. And then obviously the story had to follow suit with that. But once we really hit those key data points, that was when we were like, all right, like we're ready to go. And what we didn't realize is actually how quickly it was all going to come together. Yeah, we did kind of move from our regular check-ins to, hey, there's a company now pretty dang quickly. It was really quick. Yeah.

That was a fun time sort of over the holidays and going into the new year of a lot of work, but I'm glad we did it. It's a really exciting process when you get investors that actually want to put money behind your idea because sometimes it feels like almost you're playing in the sandbox until people are like, no, I'm willing to put real money forward.

And there's this massive aspect of flattery where it's like, wow, okay, finally someone or actually somebody is interested in what I'm doing. But there's this other side to it where again, going back to this whole relationship piece,

is that the quality of your investors, the quality of the people that you have around you are going to be the critical determinant in you actually being able to execute on this. If you think anything is hard in academia, multiply that by however many fold you want once money is on the table, once the stakes are a lot higher, once you can't just happen to write another grant to keep people working in your company.

So I think the big thing is, is when you're looking for an investor and why we're really happy with you guys is that when somebody tells you who they are, you should trust it. And you are...

incredibly honest with who you were as people, what you were going to do for us. In fact, you've done more for us than I would have expected. And I think that's what you actually want to look for when you're looking at an investor is that it's not whether or not they're high profile, but whether or not you legitimately trust that they're going to support you and be honest enough with you to actually overcome problems when they will inevitably be in your face. Well, it,

A, I think, you know, I really appreciate that. So does everybody at Madrona. I mean, one of the things we focus on the most is just helping our portfolio companies and founders as much as we can. And B, I think it's an important lesson for lots of other founders. I mean, the fit is important between you and your visions and what you want to do and the alignment with the investor base and capital. And not everybody fits with everybody else. You know, the...

As you've been in the CEO seat now for a while, I think you've developed and probably already had, but you certainly have stronger views on team building and how you've chosen to recruit and who you're hiring and really what you look for. And I think it's a little bit different in how you kind of frame it than maybe lots of other companies. So I'd love you to just talk for a second about what's your, you know, the

thesis on talent and how do you think about adding people to the team and specifically to your culture? If you acknowledge the importance of yourself individually, that's very important because we need accountability. But the other part of it is knowing that in order to be your best self, you actually need great people around you. Matt McElwain said a really good pithy thing which he's very good at is you want to find people that are cross-functionally useful and cross-functionally curious.

And what I found really interesting is when you build teams and everybody talks about what their corporate values are, what they look for in individuals, it's interesting because sometimes one can say something and believe it, and other times you can say something and not believe it. So for example, you could tell me that you wanna wear multiple hats. You can tell me that you're curious.

but are you actually? And so that's something that we have heavily prioritized for, are people that value relationships that can take a longer term perspective. We look for people that actually want to have impact. And that sounds insanely cliche, but the reality is that if you're an intuitive and emotionally intelligent person, you start actually having conversations with people

the biggest thing that you can hear is like what they get excited by. And for us, we're constantly just looking for people that are good people. They're great at what they do. And they're curious and excited about learning multiple things and doing multiple things. Yeah, I think about that. The bar is quite high to get a job at Archon, which is great. I mean, I think every company talks a lot about always raising the bar on who they recruit, but it's a challenge.

it's an extra high bar, I think, on cultural fit and how you guys just really spend a lot of time thinking about what is the culture of this team and what does that mean when we add new people onto it? Are there certain types of people that you found like you really are out there looking for or you know, hey, these are really great when they join the Archon team? So honestly, it's been just completely organic. And I kind of goes back to this point of

you treat people how you want to be treated yourself. And what we've actually found is that by enabling and supporting and advocating for people on our team, that's unfortunately a little bit more of a rarity than we would like to believe. And then the other side of it is that if you're incredibly supported and you're working on amazing technology, then all of a sudden it becomes a highly desirable place to work. And so what we found is that all of our intake has been completely organic.

You have people that hear what it's like to work with us and that we're actually people that back up what we say with action. And it's been nice because everybody that's come forward has been through an organic

connection with someone on our team. And the really interesting thing is that we have teammates that are telling people how much they like to work with us. And then you have other people coming up and asking, being like, is there even an opening? And these are for job positions that we don't even have, like they don't even exist yet. This is why you're the worst best kept secret in protein design. Yeah.

You know, I think as we're kind of getting to the end of our conversation, I know you and I could talk about this for hours and could have probably spent a lot of time just in the technical depths of why the technology is so cool. I'm also curious about, you know, just in general, what are you most excited about going forward, both for Archon and just in general?

But there is something really gratifying about being able to actually come out, let people know who we are, what we're going to do. And we've been living this. Obviously, now we are public or not public, but we are not in stealth anymore. And it's really nice to be able to share what we're doing and also speaking to people that are just...

ultra technical in the know and they look at what we're doing and they're like, wow, I've actually always wanted to solve this type of problem, but I've actually never known how to do it. If this works the way you guys are trying to build this, this could be the new gold standard. That's a huge one I'm excited for because

You know, thematically, it's just we want to be able to back up what we say with action. And, you know, being able to leverage the financial support that Madrona and our other investors have been able to offer us actually allows us to make this a reality.

Well, I know that everyone at Madrona has been just thrilled to be a part of the journey and to help you guys get to where you are and for the rest of the journey to come. And so I'm just also super honored that we were the ones to be able to talk about this together in person for the first time. I really appreciate you having this conversation. Thanks a lot, Chris.