Let the Best Drug Win with Errik Anderson

Welcome to the Axial Podcast. Axial is an early-stage investment firm based in San Francisco. We partner with great founders and inventors investing in early-stage life science companies, often when they are no more than an idea. Axial is fanatical about helping the rare inventor who's compelled to build their own enduring business. Eric, well, great talking last 15 minutes. Um, awesome to have you on this podcast and just have a conversation about to you and Alloy and maybe any lessons we can learn, but also just what Alloy can provide the ecosystem. Maybe to start off, you just talk about Alloy, what you guys do.

What we do at Alloy. So, by the way, thank you for having me today. You're so nice. That was a great 15-minute intro. We have so many things we could talk about here today. This sounds great. About Alloy. Alloy is is a— we describe ourselves as a biotech ecosystem company. What we seek to do is to create transformative technologies and services that we seek to share with the world. So we do drug discovery with other partners. There's three legs of our stool: platforms, discovery services, and venture studios. So we think about all three of those as kind of like the broader Alloy model. Our venture studio is called 82VS. It's led by Vic Stone and Mike Schmidt, two of my GPs over there. I run the back of the house. I'm the CEO of Alloy Therapeutics. We've been growing this since 2017, where we officially launched, but kind of been working on it conceptually for a long time. It's a model that is really grounded in an observation that breakthroughs in medicine oftentimes first come from breakthroughs in enabling technology. And the more that we can leverage and share those enabling technologies, we believe we will accelerate the pace of drug discovery and we'll lower the cost of drug discovery. And so if you think about where does all value in our industry come from, all value ultimately comes from drug and a patient. As we get drugs, our insurance companies pay for those drugs. That's where all revenue comes from. And so we try to help folks own part of that revenue stream. And so we get a thin slice of that, maybe for doing drug discovery. We get a thin slice of that for licensing the technology, for helping folks out. If you think about a contract manufacturing organization, they get a thin slice of that for manufacturing the drugs. It's all this ecosystem and this value chain that goes from insight around novel biology all the way to effective drug in a patient. And that obviously takes 10 to 15 years. We play along that spectrum. And so our goal is to support really fantastic scientist entrepreneurs in their dreams of developing new drugs, discovering and developing drugs. And I say scientist entrepreneurs, sometimes that's someone inside a big pharma company, sometimes it's an emerging biotech venture-backed biotech company, Oftentimes it's an academic who has crossed over into one or more of those areas. We try to take the incredible long view on what we do. We have a unique business model of how we reinvest our revenue, and it's attempting to create an ecosystem that we participate in, and over both time and also scope of sort of services and technologies. Yeah, we are just, we're just here to help.

So on the point of Alloy, like what was, you guys started off in antibody humanization.

Yeah, we had a, we started off in antibodies first in more of the in vivo side, right? So my background, it was more on the in vitro side of antibody discovery, working with a team there that has, I think still probably one of the world's best platforms, if not the. There was a gap in the marketplace of how you would get access to an animal. Sometimes you just want to immunize an animal, you want it to produce human antibodies, you just want it to work. We have used that for a number of our drug companies before to complement other technologies and platforms and services that we've built or that we've utilized. And that's really where it started, was to say, hey, look, we just— if we could immunize a transgenic animal and we could just get a deal done quickly, you kind of— the goal was 2 weeks to a contract, ship some mice, immunize it, not pay royalties, boy, we would use that a lot. And it was a very small leap to say, wouldn't everyone in the world want to do that and kind of access royalty-free in a really flexible way? And so that's how we launched our first technology platform. But really, we always knew that that was going to be a step in the path of doing ultimately Venture Studios, starting great, great scientist entrepreneurs building drug companies.

And you did a very clever thing in the beginning. I think that From my understanding, that mouse model was in license from AstraZeneca or some sort of deal with AstraZeneca.

It was. So we were working on our own, and into my lap falls a conversation with someone at a different pharmaceutical company who was aware of this animal that was inside AstraZeneca Metamune. And it wasn't quite finished yet, but at the time, led by Bahija Jalal— Bahija was really— Bahija was very focused on open innovation and sharing technology. I think she created this wonderful culture of, at least among her scientific team and her business team, of like, hey, it's possible we could share some of our stuff. Now, easier said than done. It was actually a different pharmaceutical company, a different executive that was like, became aware of this. And so we worked with that team to spin out. So they were like a few years ahead of us, and they had been working on it methodically to have great freedom to operate and a really high-quality animal. And we just kind of, we hit it off, and I think it was incredibly generous and thoughtful about how a big pharmaceutical company might share a technology like that. And then the deal was we had offered back that they would get continued upgrades and we would finish it and we would find a way to work together. We actually pay a royalty back to them, which is kind of hilarious. There's like a top 10 pharmaceutical company making like positive revenue. Everyone in the world like pays them for access ultimately. So I love that. I really do love that. I think it's a model. And we've continued in those conversations with big pharma about, hey, are there things that you have either acquired or developed through these platform technologies that maybe the team has left of a company you acquired? Maybe there's some interesting innovation that can continue to happen. You could do on top of that. And perhaps what you're interested in is the drugs that came from it, but you're not necessarily interested in controlling the platform exclusively. We would love to be your partner, pull that out of the pharma company, continue to invest in it, improve it. Our pitch is you get all of the improvements. If you bring something to the party and then we start building on top of it, it's a little bit like kind of the Linux model. Like, my background is in software before I was a bioengineer. So I think about this balance between open source software, like the cathedral and the bazaar dynamic here. So we're kind of— we're more decentralized than not. We're more of the bazaar than the cathedral in that metaphor. And so the idea is if a pharma company has something, maybe they had a really awesome acquisition for a few billion dollars and they bought it for a drug, but they've got a platform, we would love to talk to them about spinning it out, continuing to develop it, and sharing it with the world and improving it. And they get access to all the improvements and they never have to pay for those improvements. So we do think that's a, that's a workable model. We've continued to push that model. We have great relationships. We don't like to talk about necessarily all the things and the people we do. Our goal is to be behind the scenes and kind of quiet. You know, my wife knows who I am and she loves me regardless of the crazy things that we do. So that's about like the level of validation that we need. So there is this tension in our model of people knowing who we are and what we do while at the same time we try to stand behind the scientist entrepreneurs and even the big pharma companies we work with. So in our perfect world, we would work with everyone and no one would know that we work with them.

Yeah, that's the way to do it. I think scientists should be superstars and companies like Alloy help them fulfill their potential. Can we, on this point of like, you talk about working with other companies and building this ecosystem, if you could just talk about Reed's Law and the role of Reed's Law long-term for Alloy. I think a lot of people are familiar with Metcalfe's Law.

Sure.

Use it as moats. It really seems like Alloy is relying on Reed's Law long-term to build a moat. Maybe you could just define what reasonable is.

Yeah, sure. Well, it's kind of this network effect, without geeking out too much, right? It's how do you create value that's nonlinear, these network effects? And you mentioned Metcalfe's Law and Bob Metcalfe. I met Bob when he was working with Polaris, right? So just an incredibly nice guy, just a visionary, such a great collaborator, such a great entrepreneur. Right, so Metcalfe's Law, this idea that you plug more nodes onto the network and then there's a scaling effect. The telephone network or the Ethernet network traditionally So if you and I just have a phone, it's not really all that valuable. We can connect it to 10 other people. We all get value by the fact we can call the other 10 people. Reed's law is this idea that we become networked in these subpockets where you have— it's a nonlinear value, so this exponential value that derives from these subnetworks that are created inside the network. It's, in our case, if you start thinking about antibodies, but then you go into technologies related to advanced bispecific antibodies. As an example, that's a subset of our partners who work with one or more of our technologies. And if you have, if you take, it's okay if I'm kind of like geeky on the science here, is that right? We've got a sophisticated post-listening. Yeah, so if you think about like the Fc domain of the antibody and maybe the heterodimerizing domain, do you really need it to be proprietary for one company? Like, is there sort of, are there 8 or 10 of us that are really interested in having a really good version of that? And what we wanna do is we kinda wanna collaborate and share some notes.. And if we each have a handful of preclinical programs, or perhaps we have some early clinical data, and that informs our thinking around the manufacturability or the stability, or even, you know, what is actually happening in, in, in sort of, um, in the underlying biology related to the FC, perhaps that's a great place to collaborate. And it's a subnode, it's a subnetwork where the folks who are collaborating inside that small ecosystem can very rapidly get ahead and create an outsized amount of value versus everyone else.. But that's a subnetwork. Not everyone talking about antibodies is talking about heterodimerizing domains or engineered Fc. And so that's a little bit of the way that we think about Reed's Law, is how do you create these subnetworks across the ecosystem. And one of the ways— so one of our key advisors and a partner of the company, my chief strategic advisor, is a gentleman named Ron Adner. And he is an incredibly accomplished economist. He's written two popular books that make his work very very accessible. I think Ron is famous for being like one of the top ecosystem economists in the world. Now, and Ron, I've never asked him how many there are, but like, but I kind of like, I read my econ papers and his are really good. But his book Winning the Right Game or The Wide Lens is actually, if you read those, it's actually a really good representation of how Alloy thinks about the world. Which is if you're leading an ecosystem, or if you're attempting to participate in the ecosystem and be a leader— there can be many leaders— you, you need to be thinking about how do you actually create value across the ecosystem and not necessarily be telling people what to do. And so what we try to do is to show up inside that ecosystem and be useful and to be valuable. And so one of the ways that we can be valuable is help to coordinate the ecosystem and yet draw no money from it. So some of the things that we do in coordinating the ecosystem, we're not charging people to do it. We try to make it non-transactional. We try to make it very relationship-focused. And we're able to do that because we can play with time in a way, right? So we are a company that exists to be around forever. We reinvest 100% of our revenue into innovation and access to innovation. We can come back to that. It's a bit of a Rorschach test. When people hear access to innovation, almost everybody thinks something different, which is kind of interesting. So that as long as Alloy on the discovery services and the platform side, as long as it makes a dollar of profit, that's a brand promise we make to all of our partners. So when we work with a top 10 pharma company, they give us $1 million, $5 million, $10 million to license technology. They know we are going to spend it continuing to improve that technology, build other technologies that we have the intention of also making accessible to them. So we share our technical roadmap with our partners across our modalities—antibodies, soluble proteins that bind peptide MHC and, uh, and effector cells, a TCR mimic or a soluble TCR. That's our second modality we call Keyway. Our RNA medicines team developing technology that we can share with the world. Our cell therapy, those are our first 4 fully integrated modalities. We look for technologies that can be shared and you can make a lot of drugs off of them. So that's a brand promise as much as anything else, and we're fortunate to have a handful of family offices, some great venture capitalists, most notably ABC, who worked with us really early on. Alex Kolesic is on our board, and of course Joe Lonsdale there. To the founder. They've just been phenomenal visionaries in how they think, give us like the rope and the leash to create the platforms in the time and space across literally decades. Now, they're investors, so they will get liquidity, we'll roll over their equity, but the money that really comes that is available to investors is really in the Venture Studio. So what— imagine if you could start a biotech company without putting any money in, like, and you could get unlimited access to the world's best technologies and services for free And anyone coming around their postdoc, she can just step on the platform and start discovering some great drugs. That's the ultimate— like, if you think about the vision of what Alloy Therapeutics is combined with 82BS, that's the vision, is that, is that we can, we can give access to these technologies and services to really cutting-edge folks. And that's why we fight for efficiency in what we do. We try to drive down the cost of drug discovery because you can take more risk on a crazy idea. You can take more risk on a person who might be a little bit earlier in their career if the cost of doing that is $1 million instead of $10 million. It's all about cost of capital. It's all about risk. It's all about time horizons and IRR. And we've got to balance all of those competing tensions.

You guys have jackets.

You have "Let the best drug win." Yeah, right here on the back of our coffee mug. It's a constant daily reminder. You know, it's interesting, Josh, because in the early days, like, we know what it means. And then it's like 2 or 3 years in, someone was like, "Well, it's kind of aggressive." And I was like, aggressive? We intend it to be the opposite. It's like super friendly. Like, what do you mean? What we mean by it is this idea that, well, first of all, if all value comes from drugs and a patient, everything else is derivative. But at the end of the day, the only way in a society, theoretically, right, in a society, the only way that you get innovation and cost control Is through competition. Perfect. I really want innovation in medicine, right? The whole point of how Owl is doing what it's doing is the cycle of 10 to 15 years of drug discovery, of technology buried in the company that gets acquired, that then is patented and no one gets access to it. We no longer have any academic research in America, maybe in the world, but certainly we can just pick on the United States. What I mean by that is If you are sitting there at Pfizer and you read an amazing new paper that's published in an academic journal, you know that you cannot practice the invention that's in that paper. Yep, you know that. Why is that? It's because it's already been filed on. And then we know that our tech transfer office in our university have done a really good job of creating great relationships with really spectacular venture capitalists. And so there's— or maybe folks like ADTBS— and we're there trying to license the technology. So by the time a top 10 pharma company shows up and says, hey, I'm a pharma executive, can I license the technology? The price just went up tenfold. Yeah, only one person can license it. So we have this tension in the way that we create, in the way that we innovate today, uh, in this translation from really academia to emerging biotech into pharma. And that's sad. We need a little bit of a different business model. Almost you need a fourth type of, of player instead of just academia, emerging biotech, and pharma. You almost need a layer on top of that that it's willing to play with time and capital a little bit differently. And that's what Alloy— what we've been trying to build at Alloy is how we spread that across time. And so that means in some things we give them away for free. In many cases, we show up and we try to do services at the lowest cost possible, make access to technology. Of course, we have a business to run. We have to find some way to pay for this, but efficiency really helps to drive that down.

Of course, I think Alloy is like a synthesis of all of your experiences. Software engineer from AtomLab, Elector Compass, and even the rugby team, teams you own. Um, could you like talk about maybe the early influences, early work you did before Alloy that set up the company? Uh, you know, one example I think of is just you're at Dartmouth and you do this extensive patent search that sets up AtomLab and you find Daniel Workshop in the process. So Yeah, what are some early work you did? What work in your career was sufficient for you to start Alloy?

I think, or yeah, to start it, I think all of us as entrepreneurs, right, you have an entrepreneurial pursuit of your own, right? It is the sum of our experiences and the lessons we learned. And then you look back on it 10 years later and like, I could have done that so much better or differently. So it's great. We're always learning. Wonderful. I'm an econometrist as an undergrad. Like hardcore statistics as econ, this branch of econ, and it really— there was a professor, David Blanchflower, that I met. My advisor was a gentleman named Matt Slaughter, who's currently the dean at the Tuck School of Business. I had two really, really, really great professors. I had many great professors as an undergraduate, but with Blanchflower, I did some independent studies, and it was just running regressions in the basement of the computer center and like with kind of his data sets and some big data. And I think I just stumbled into that because I certainly had a background in software and it was wrangling data, which is interesting. That led to really thinking about portfolios, right? To thinking about regressions and looking for the drivers of teasing out what are the drivers of outcomes. So that was probably the most important background as I went into venture capital. But I was very, very lucky to be Lehman Brothers' first intern, actually. There was 3 of us in a winter internship, and then they had like the full internship that summer, because Lehman used to be on my Amex, and then before that it was like old school and stuff. So oddly, this was like the first intern. So I worked in the consumer, industrial, automotive group. That's what I got assigned to. That was super fun. But then I went down and like poked around at the venture shop and asked them if they needed any help. And so I was really, really lucky to be there during telecom deregulation and the first internet bubble, working with a phenomenal team, uh, doing venture capital, and just learned a lot. I mean, you learn so much more from failures than you do from successes, because when everything is being successful— like when, when our— we just lived through this in the last decade, right? So when everything's up and to the right, you're like, I think everything I'm doing is working fine. Like, this is— I'm gonna do more of this. And then like interest rates go up and like things— you're like, hold on, the thing I was doing before didn't work. So When you live through a few bubbles and you live through cycles, and if you were a student of history, you should read your history and don't believe too much that the future is going to be different than the past. I think largely human psychology is going to be the same in the future, and therefore, a lot of markets are going to participate and behave the same way. So I had that as a background. And then by the time when I was in grad school, went back to Dartmouth in grad school, and And what, yeah, one of you mentioned the patent thing. One of the hacks that I found as I was working on starting the biotech company, and it really, so I actually fell in with a really phenomenal professor that had this, just, he's like a really dynamic and exciting, like energetic person, Tilman Gerngross. He's a professor at Thayer still today. And any guy just like, you know, got fired, he was fired up about venture capital. He had co-founded his own company, was the CSO of a company called Glycofy, heavily involved in the business side and the scientific side. And so Tillman and I hit it off early on. He was my PI. We got into a fair amount of trouble together, and I was working in the background of trying to think about starting a biotech company. I had great professors at Tuck. I was allowed to do some, some independent studies. I did talk in my free time. I was at the engineering school. I lived there, and, uh, and Tillman was a good PI. I wrapped up some stuff in the lab. And just kept riffing on ideas. And one of the things in kind of the back and forth of riffing on ideas, started looking at a handful of different things, but one of them just in the antibody space. And here's a hack. It was, you can go read all the scientific papers and then you try to figure out what works and doesn't work. It turns out like it's hard to reproduce the data in some scientific papers, but simple observation, if you read a patent where the maintenance fees are still being paid, So it's like an active patent. The claims actually become a very succinct summary of what is perceived as valuable. And you can read the claims and you can sort of figure out, oh, this is valuable, this is not valuable, and back up into the spec and you read the description and then from there you can back up into the papers. So it was almost like total way to hack the summary. This is before we had large language models and like ChatGPT would summarize our stuff for us. Like the kids today have it so easy. It was a total hack. And I think, you know, what's interesting is I had my background in venture capital and at Lehman Brothers Venture Capital and kind of thinking about the patentability of things and again, how important that is to an investment. But it was actually, it was really important when I was working with Tilman. I remember he had that view of the importance of IP from the business perspective, but it came from him being an engineer and a scientist, right? So I think that was really, really important to be working with him and kind of the mentorship component of that, of kind of thinking about patent claims through that lens of like what's actually the science here and what does this say? And that was really transformative. So pulling out some patents and I was organizing them.

And what was your— I have this romantic image of you in a library at Dartmouth reading patents, but the reality is probably much more.

No, no, no. That's exactly how it was. You go into the library, it's beautiful. And I'd be in there. No, like the grad school office with no windows in it. Exactly. 6 guys around there just like stinking up the place. That's great. Yeah, exactly. No, it was, you know, back then I made a FileMaker database and I automated, I wrote a script 'cause the USPTO was organized, but we actually didn't, there was an expensive piece of software that I couldn't get. Of course I couldn't afford that. And so I had to kind of manually suck data out of the USPTO. And so with a little bit of a script, dropped it into FileMaker, organized it. Until now we're a bit of a rhythm. He was still, we were doing this when he was still running Glycofy and then post-Glycofy before we'd started Adamant together. We found Dane through the patents, like you know that story and the papers. I mean, they knew each other by reputation or they're great engineers, right? So the, yeah, just kept refining that FileMaker database and I remember it was, it was literally hundreds of thousands of patents that had the word antibody in it that were trimmed down to anything that really related to the technology, and the philosophy was kind of riffing on how do you create a technology platform that can discover drugs and discover a lot of drugs, but you kind of separate the platform aspect of it from the drugs itself. And among us all as like the early folks, there were sort of independent observations on why that is valuable. Venture capital goes through cycles around funding platforms versus products in the biotech space. I think we're going through one of those cycles today, right? As capital gets really expensive, you have this tendency to move towards things that are already in the clinic or sort of much more validated. There's less of a willingness to fund things that are on the platform side because our cost of capital is very high and those timelines get extended. So anytime you have high cost of capital, it's hard to take long timelines. So yeah, that was, I mean, that was, that was like one of many, many things I was doing that could have been a waste of time or not waste of time.

But that one worked out pretty well. That's awesome. Do you miss it? Sometimes I miss the grind of like that busy work that sets up your career or something. I don't know if you miss reading those patents.

It's funny you say that because I think my team tells me all the time, like, I get intimately involved in the details of my business. And that phrase rolls off my tongue because our team on our K1, on our management team, every quarter we write a memo, long-form memo. Everyone writes an update on what's happening in their part of the business. And we do that because I want that independently, an independent check on whether our individual business unit owners or the heads who run our scientific, that we can talk about what we're doing. And I read it, and sometimes I'm surprised. I'm like, ooh, you're kind of working on something that like we have kind of a complicated business, about 100 people. So it's an opportunity for us to sync up our thinking, actually. And then it's all in one place and we give it to the board. And it's like 15,000 to 20,000 words sometimes, which is even short, but just inevitably it gets kind of long. And, but if you read those, you know exactly, or at least our best description of what our business is and where we're headed. And I always slap a cover letter on it, sort of read everyone. Read everyone's memos and consolidate my thoughts of here's where we're at as a company. And in the last quarter's memo, I was like, in part of my memo, I said, I've been lied to my whole life. And I bet you've been lied to as well. And like, this is going to be really hard. But here's the thing that I've been lied to about. People tell me not to micromanage. And what I realized was I'm not micromanaging. I'm just intimately involved in the details of my business. Business. Yeah. And micromanagement is telling people how to do their job. Intimately involved in the details of your business is being very curious about how everything works. Like, hey, is this working? And so my expectation in running any of our companies is that the people who are doing the work or close to the work, they should be empowered. And if you are empowered, then you know what you're doing. So, but the thing is, I have this— like, I pulled a picture in this part of the memo, you know, kind of the whole phrase turtles all the way down. Recursive software. Oh my God, like, okay, it's like a software recursion thing, right? So on the— the world is on the back— is balanced on the back of a turtle. What's under the turtle? Oh, it's turtles all the way down. Um, it's a software recursion. So, so this idea that if I am not intimately involved in the details of my business, that's okay. I go to Josh, it's like, Josh, you run your BU, and it's like, hey, tell me what's going on this thing. You're like, I don't know, I gotta ask Susan, she knows what's going on. And then you go ask Susan and Susan's like, I don't know, you know, I don't micromanage, I gotta go ask Johnny. Johnny, what's going on? And you go all the way down to like the lab tech, and the lab tech's like, yeah, here are the details. But the lab tech has no context for how it fits into a complicated drug discovery and development picture, and so you lack then the context. And so in my business, in Alloy, I have a great scientific partner and business partner here at Alloy, Piotr Bobrowicz, who's really the brains of the operation. He's the keeper of the long-term roadmap. So Piotr is our head of all of research. He's been with us, I mean, he and I have been working together since 2000, 2003, where he was— 2004, where he was my external thesis advisor. He actually was at GlycoPhy at the time. So we've worked together for a really long time. And so he's the one that is like the keeper of the whole roadmap and thinking about what are the things we build and how it fits together. And so he's kind of the brains of the operation, the genius of how the science comes together. And he relies on our domain experts, but he ties it all together. Observations down these silos of what we do, whether that's RNA medicines, or it's an RTCR mimic group in Keyway. He ties that all together. So I feel the same way about our things. Like, if you go all the way down to the bottom and only the lab techs know the details because you're afraid of micromanagement, well, then you lose the context of how the pieces come together. Oh, hey, Josh, if you really want to piss off engineers, ask them this question. Yeah, what is the most important branch of engineering? And kind of, I mean, I'll let you think about it.

You want to answer that? Systems.

I think systems. Systems is my answer. That's right. That's what I would say. Okay, wait, wait, hold on. Why are you saying systems?

Because it's like bringing everything together.

Important to everyone. There you go. So it's, so although like maybe not the most complicated, sort of like liberal arts for engineering. So the systems engineering is the most important branch of engineering, you may argue, because there's a lot of other specifics, like, I don't know, we could probably do without electrical if we hack it with something in bioengineering perhaps. So, but systems at the end of the day, you got to take a step back and how you integrate the pieces. It's kind of this API-driven model of how you create technologies, and you wrap it in a service layer, or you put it through a layer of abstraction. What big pharma really wants, it wants to come to us and say, hey, can you just give me a drug that cures this disease? And I really would like it pretty soon, and can I buy it for a very low price? I would love to be able to deliver that, right? Some world where AI discovers all of our medicine for us, and we can do that, and we cure everything in like a weekend. We'd love to live in that world. Like, I'd go find another job. I'm sure there's something else I can do to teach school in that world where we cure everything in a weekend. Um, but that's where everything else is just a layer of abstraction. I don't trust you to do that. Can you put together all of the pieces behind that? Um, high-quality science on time, ahead of schedule, like, ethically done? Like, boy, you just sign me up. Where's that— where's that contract research organization that can do that for me?

Yeah, I think that thread is a little longer. It's like As a CEO, how do you stay, you know, a purview scene at the whole organization and stay in the front line? You know, I think working with CEOs myself as a partner, yeah, that's a big struggle as a company grows. And maybe, maybe we could sidestep that whole— you don't—

well, how do you do that? You do, you do investing, right? You do early stage investing. So how do you balance that? Yeah, yeah, yeah. So how do you balance— I think it's the same way as like a CEO, right? How do you balance that that need to know all of the details. And you've gotta make judgments and assessments. You make capital allocation decisions.

As an investor, I strive to be available but not active. And I think maybe as CEO, you're the same way. You're available to everyone, but you don't try to micromanage them or ping. And I'm not constantly emailing founders about like, what's going on in the company? You'll let me know when you let me know.

And if usually I have to intervene, I had my 360 review today, so I am sensitive to my feedback. No, it's hard to balance that line. Sometimes you're over the line in like opening the door and sniffing into the room and trying to figure out what that smell is.

Who's giving you feedback? Who's the guy above you?

Who's the woman above you? I have phenomenal board. I'm so lucky with my board. So I have I have a handful of CEOs on my board, and I have a handful of wonderful investors who think like CEOs on my board. I have a few crazy people, and I won't say which ones are which. But I say crazy, good crazy, so very contrarian views. But we've got a good relationship. So there's a controlling class of stock in Alloy. So the company cannot be sold. So we exist to be around forever. We reinvest 100% of our revenue into innovation and access to innovation. And so we have had a relationship with our board and investors where that's set up from the beginning. And I think my investors and my board know that I will work hard every single day. I do think when you take money from an investor, you work for whoever gives you money. I take that really seriously. I grew up on a farm. So when you're in a business, you take money from someone, you need to work very, very hard to make them money. That's the thing. But now my passion and what I'm very, very interested in is how do we turn that money into making breakthroughs in science and medicine, and that I get really, really excited about working with talented folks who have surprising ideas. So I have a great— I mean, I get feedback from that group. I don't think— I think they probably navigate the "I don't want to piss anybody off" thing as much as we all do. But my K1, my management team, is a really, really, really good group of people. We are We're not a top-heavy organization, but we're highly experienced. And one of the ways that we make that work is everybody works. So one of the things that makes us kind of an odd organization at Alloy is the folks all the way up at the top— well, I told you about Piotr, I mean, he's head of research, he's on the board as well. That guy works. Like, he's up early, he's working late, like, he finds balance in his life as we try to do, but no, he's going to be intimately involved in the details of things he works on as well. So So part of it is how do we work as a team? I got a great team. That helps. But we also try to stay small. I think that's really important. So the closer you are to the work and to the data, the more nimble you can be. How do you— there's just a limit to the number of things you can integrate in your mind of complex thoughts. So you need layer of abstractions as well. But if you're a 100-person team, like what we are, you're a 100-person team, you know everyone's name. You know, probably their kids' names and their spouses' names. You know what they're working on. There's tools that we have to make that more transparent. It helps us coordinate our activities. But we also have this concept of integrated independence. It's a made-up word, but what we mean by it is we can have independent teams. Like, we have a facility in Athens, Georgia that does antibody discovery. And from the outside, everyone's like, wait a minute, isn't that what you do in Boston? Like, why do you need this extra team? But the truth is there's an independent person running that. Rick Schimpitz is the CEO of Datamav, named after Daedalus and Icarus. He got to— he gets to name it. I love the story. So the whole story of Datamav is, is that in the story of Icarus, if you remember, Daedalus was his father. The wings— everyone remembers the part of it where like, you don't fly too close to the sun. But the other part of that story that people forget is you actually don't fly too low to the ocean because the waves would, would lap and get on the wings and weigh them down and also drown. So it's kind of a golden mean sort of story and only remember the kind of the part of the story that like the tallest poppy gets cut off, which is kind of a different story in our culture. So Datamap was an engineer and the idea is you don't go too high, but you also don't go too low. So what is like a purpose fit, like a fit for purpose? Like how do you be really, really fast and super high quality of doing protein engineering and antibody discovery? And they developed and invented a different workflow that can be used in some context and be like so much better. It leverages some of our in silico approaches, so it's more of the integration of the in vivo, the in vitro, and the in silico together in a really high throughput way. And so in this kind of notion of integrated independence, he's an independent P&L, independent business unit. But yeah, kind of that pride of ownership and authorship also, like, as it works, it continues to work. All credit to Rick and the team down in Athens because they They're the ones that built it. They're the ones that execute on it. He's highly integrated with our business development team. He's highly integrated with our team in Waltham run by Ken Bonsgaard. He gives advice to everyone else on the K1. We are integrated, but he's allowed to be independent. So it's how do you develop an entrepreneurial mindset inside a big company?

On this point of incentives and organizations and then business model innovation in biotech, something I'm investing in, but I need to learn a lot more. And could you talk— maybe you have a few questions, you can just answer them in a bunch. It's like, one, why do you think antibodies have been the richest place— space for anybody for business model innovation in biotech? You know, you think about your career, you know, the companies you've been involved with, they've been built on antibody discovery and drug development. Why is that?

Why is antibody—

why are the only kind unique businesses in biotech really relate to antibodies? Two, related to that, how do you think about business model innovation in biotech going over the next 20 years? And then where is it going? Is it going to be isolated antibodies or could it expand to other programmable medicines? I think earlier about Reed's Law, there has to be some sort of programmability to modality. Small molecules, you probably can't do what you suggest about FC domains. Antibodies, RNA, TCRs, you definitely can. And then the third part is related to all that. Where do you take inspiration from? Because for me, in biotech, I take inspiration from like non-biotech companies like Danaher, Constellation, like, you know what I mean, like, like, uh, uh, uh, Teledyne or something. So like, that's a whole bunch of questions. Maybe totally.

Well, I'm gonna have to like track back and ask you, so I'll start at the I'll start at the end. Where do I take inspiration from? Everywhere in the world, right? So sometimes what passes for innovation is the thing that you just lifted from another business model. So by the way, everything in the way that we think about milestones and royalties really comes from like the film industry. If you look at like the blockbuster industry of like how the film— so there's things you can learn there about slate financing and how you think about points in a film and where risk is actually taken, the timelines, how it pays out. So you absolutely can learn from other places. At Alloy, we do CEO book club. Actually missed last quarter. We've been so busy. Actually, now that I'm saying it out loud, I gotta get that. The CEO book club is one where we read a book. It doesn't have to be anything about biotech, but you have to think about it in the context of our business. So that's what we try to do. We come together and think about it. So we read Legacy by James Kerr, James Kerr, um, and that's about, um, that's about the New Zealand All Blacks. By the way, I didn't pick that one, although yes, we do a lot in rugby. Um, the New England Free Jacks here in Boston are the current— Do you play rugby? Have you ever played rugby? I played rugby in high school and college. Um, I was not good at rugby. Um, so my business partner Alex Magleby, who is my co-founder of the Free Jacks, We, we invented the Free Jacks, the New England Free Jacks, and as part of Major League Rugby, which was a league that was setting up. So we were involved kind of from the beginning. We were not one of the first teams. We were kind of like having dinner with the folks and looking at it from the sideline, being like, are you guys— is this gonna work? Um, Major League Rugby is awesome.

Um, Jeff, our spot, the San Francisco branch. I'm happy. I'll put my hat in the ring.

A lot we can talk about. We talk to sports team owners about how hard it is to have a team in San Francisco. I will go down that path with you There's a great Kezar Stadium.

I work at a Kezar. It's a great state historical stadium.

We need another podcast on this so I can tell you all about challenges with sports teams in San Francisco if we want to do that. I would love to have a team there. We'd love—

next time.

Okay, next time. Yeah, take inspiration from other places because the— and certainly, um, the cheapest lessons, uh, and the cheapest mistakes are ones that you learn from somebody else's mistakes. So pay attention. Um, this is, uh, Inspiration, basically from everywhere else, but certainly from biotech. There are— if you peel back the layers of what is going to happen in the world, it's all going to come down to human psychology. We care about these things because people care about them. And so you look at— I mean, asking a question of where does wealth come from, right? So all wealth in the world— these are very simple concepts— all wealth in the world comes from turning raw materials into something useful. That's it. That's all we're trying to do. That's why the GDP of Mars is zero. There's nothing useful there because there's no humans to actually consume it. It doesn't matter what's there. So therefore, it's all about the efficiency of which we turn raw materials into something useful. And this is why technology is so amazing, because technology and our ability to patent things and then share those patents and protect them and the profit motive and the incentive for people to do hard work and part with their capital and do this thing. So this, this wonderful treadmill that we were on for the last few hundred years of protecting intellectual property results in technology that turns raw materials into something useful. Okay, great. So that's, that's the game that we are playing. And of course, as a society, then we're talking about how do we spread that wealth. So in the world where the software and the robots make everything for us, we need to have a really serious conversation about who gets the benefit of that wealth creation. And this is why trade balances are important, because those create local pockets of wealth in our communities. And we have a philosophy of investing in the communities we participate in. That's why we have our rugby team and other things. So we take inspiration from, let's say, just the basics of how human nature works, and we try to solve problems that are useful. Because I like puzzles, let me just say the really selfish thing is I think my brain is just wired in a way, we're all wired for novelty to some extent. We have a dopamine system that wires us for that. And so for me, the particular type of novelty comes down to puzzles. I read a book, a woman was talking about how like she gets into a state of flow, you know, like the Mihaly Csikszentmihalyi concept of flow where you just get lost in what you're doing. So earlier when you talked about like Do you miss the time where you're just like geeking out on a model or like crunching the data or like pulling patents? Yeah, because like anyone who's ever like done software or like, I don't know, you get like lost in an Excel model as an investment banker. Like there are those, there's the work that you do where you get lost in it and you get into the state of flow. That is the thing that I'm probably addicted to, is this feeling of like, like this kind of overlap of like a sufficiently complicated problem working with kind of feeling like it's worthwhile. And if you layer in, you're working with good people on top of that, that's kind of like the magic sauce. So, okay, so you asked the second question, where are we going in 20 years? Hold on, antibodies and business model innovation, that's an interesting question.

Yeah, they're related. It's just like, I love case studies. Yeah, yeah. I look at some of the most— I mean, it's hard to get data on this. It's hard to know the true returns on equity.

Let's make up some data together. What are you thinking? What are the examples?

I mean, Regina Ronald is a crazy example. They got diluted a lot. But Accelera is a contemporary of yours, and they— it's incredible. I think, I think Kara owns a bunch of that company. So I think the metric is how much the founder owns at the end.

That's— well, that's— but that, but that's correlated with how much capital you need. So back when I was in venture, we were doing late-stage venture. This is sort of mezzanine, what we call crossover today. Um, but then the pattern of venture creation, even in tech back then, like we didn't have all the layers of abstraction like we do today. So even when we started Atom App, I like set up a server, like, like an email server. Like we, like, we had, like, seems like ancient history. So, uh, we would invest in tech companies. It would cost like $10 million to build a software company in, like, this is like circa 2000, called the first internet bubble. Um, of course the cost of that today is like $10,000 maybe. It's like nothing. It's basically your time. So we're not going to see the same pattern in the wet lab, right? Because this is not digital. And I think that's where some people miss it. And sort of if you go too much digital, like completely digital in your thoughts around how biology works, you're going to kind of miss the mark. But so that's why we're really focused on making the wet lab efficient, supported by AI and ML. So I think software in the in silico approach will support the wet lab and make it more efficient. And then you need this feedback loop of what you what you can do in the wet lab and feed back into your dry lab. And it's really about making that efficient. The world where we wake up and the software does everything for us and discovers drugs on the protein side, if that's the day, you know, the day before we would have done everything on the small molecule side. And frankly, small molecules, if they work and like they're highly specific, like you can take them orally, they're like easier to manufacture, like, aren't we eventually just going to have small molecules for everything? Antibodies are a bit of a nice platform to work on that's super flexible. But I don't know, maybe that we end up with small molecules for every protein therapeutic we have today, and that'd be great. It seems like the ML is going to solve the small molecule problem a heck of a lot faster than a complicated protein problem. But we'll see.

There's a language of protein. I kind of disagree with that. I agree with the premise, like 100 years from now, we should have— every company should be like Morphic. 100 years from now, or like— yeah, it's gonna take some time.

No, no, look, every time— I mean, what are we not— what are we not going to cure in 30 years, 40 years?

We'll cure most diseases. We'll cure every genetic disease by that time, in my opinion. But how do I say this? As an investor, as a scientist, I think, yes, I agree with you that drugs should be convenient, and maybe not 100 years, but just like more than 20 years. But like right now, as an investor, antibodies are so wonderful because the burden of proof is so much lower to do business transactions.

It's a plat— okay, so I'll go down the antibody path. So I don't accept the premise that it's only in antibodies, but I do— maybe RNA. I see the pattern. I see the pattern in antibodies. We can stick with that. The— here's why antibodies are so great. Um, it's because it's a platform. It's a highly validated platform. I mean, this is what evolution Evolution has evolved to be the soluble form of our adaptive immune system. So we have B cells and we get antibodies from that. For the listeners at home who are not immunologists, because apparently they didn't experience COVID where everybody got good at immunology, you have B cells and T cells. B cells make antibodies. And so when we take a vaccine, we're trying to induce our B cells to make antibodies that work and fight off disease. And there are also T cells and, oh my gosh, now I'm just like embarrassing myself in front of all of your listeners. I know the immune system is complicated, but just conceptually, the B cell, if you think about this as an engineered system, the B cell is the system that produces a soluble protein that can fight off disease in an adaptive, and that's an antibody. The T cell system, to overly simplify it, has a T cell receptor on the surface, and it can detect, it's designed to go find a T cell receptor to find a peptide MHC, so that's an intracellular target. It's an intracellular protein that gets presented on the surface of the cell in the form of a peptide MHC. And then the T cell receptor comes and finds that. Now, that's a cellular approach. We don't have soluble T cell receptors in the body. And one of the reasons for that is because it would be dumb evolutionarily. There's only so much diversity budget you can fit in your blood. And so B cells do their job, T cells do their job. And so we have these mechanisms. But we are clever apes., right? So you can learn, where do I take inspiration from? I think biologically and scientifically, take inspiration from nature. And so we're always looking to hijack natural mechanisms. You observe what's happening in the human body in nature, and you try to copy that and hijack it. We are smart apes. So if you look at a T cell receptor, what if you could make that soluble, which makes it a manufacturable drug? But the problem is when you make it soluble, oof, well, now it's actually not gonna have the killing power of the cell behind it. Okay, great. So what if we boost the efficacy? What if you could make it have the killing power. This is where, remember Patrick Bowerly's work, bispecific T cell engagers, the BiTE, like the official BiTE word is like a trademark term that Micromet trademarked and then sold to Amgen. I don't like to use BiTE. We talk about soluble proteins that bind peptide MHC and effector cell. So a soluble protein, if you can engineer them to be highly specific, to truly differentiate between a peptide in the same MHC and like, closely related peptides, and then you can bring the efficacy so that, so the cell engager can engage in the proper way, whether that's a T cell, an NK cell, or otherwise. That is a phenomenal model. That's a phenomenal model. So we're just using our brains to do that. That is actually Alloy's second modality. Fully agree. Great idea. And by the way, it's not our idea, but Keyway is the only fully integrated, like, freely and broadly accessible TCR mimic platform platform and also soluble TCR. So the team under Dongxing Zha— Piotr Poprowicz, keeper of the technical roadmap, had started on this stuff. Dongxing Zha was working at MD Anderson at a platform called ORBIT with a really great team there, including some folks who we have now on our team. So Dongxing leads Keyway, which is our fully integrated TCR mimic discovery shop, and it goes from everything from making antigens all the way through to specificity testing supported in vitro and with our machine learning approach. So on the software side, so you got to build all of these pieces, wrapper it in a service, and you can get that at Kiway. What I love about Kiway is Dongxing actually named it. So again, with our philosophy of how do you engage great scientist entrepreneurs who have these like transformative ideas, so Dongxing independently had this idea of how he would build this platform. He was already doing it at at MD Anderson. And so we were able to come together and really industrialize that. And so, so now we work with a number of companies doing TCR mimic discovery. And so that is— so at the heart of that though, our, our TCR mimic is an antibody framework because it is— we know how it behaves. There's a, there's a manufacturing infrastructure. The agency, the FDA, knows how to read our data on whether this is a stable molecule and how it's been manufactured. So So the reason why TCR mimics, I think, have very long legs is that we already have all of the supply chain and the infrastructure of how to think about it, both from a manufacturing and a regulatory standpoint. Everyone knows how to work with this. We've already driven down the costs of things like Protein A, the cycles of developing these things. We helped to found a CDMO in the Midwest in Oklahoma called Wheeler Bio. So Wheeler Bio can make monoclonal antibodies and bispecifics., and since the TCR mimic is just a bispecific, we can integrate in that process. And so now you like, you can get to the clinic much more quickly. And so it's a flexible platform you can build on top of. I think in antibodies, if you look back at the history of antibodies, there was a, there was a bit of a patent war, right? Morphosis, Dyax, back in the day, Domantis, really great technology, kind of forked and found freedom to operate in a different way. Lilly acquired a company called Applied Molecular revolution. So Dyax even created a whole model that actually, you know, Adimab didn't make up the model of having this, of doing what it did and taking like a slice of the milestones and the royalties. Dyax actually had their LFRP. They had like, and Cowen Healthcare Royalty Partners had actually helped to fund that. And so they had eventually people knew Dyax really as the drug company, and that's what they were ultimately acquired acquired for at a very nice price. But before that, all their technical expertise was, of course, making phage libraries. And there was a data— like, everybody sued each other back then, like, for the IP. And so what we were doing between me and Tillman and Dane, and then I think the next 3 people that really joined that were critical to the success— Piotr was one of them, Michael Feldhaus was another one, and then Max Vasquez. You kind of think, like, I remember the early days, like, if you take any of those 6 people out, like, Adamant probably wasn't a company. Eric Crowland comes in straight out of his postdoc. He's now the CSO, so kind of like everyone's kind of grown up together. So that team really had to pull together all of those things at a moment in time. And to be able to make, like, to make that technology work was really built up on top of the work, including the business work of, okay, you're Dyax and you got a phage library. You need something like gatekeeping because if you have one library and everyone's drawing, fishing from the same pond, you're going to pull out the same antibodies, the same fragments of antibodies. And so it was like, okay, well, what if you didn't have gatekeeping? Would that be useful as a business model? Right? So the only way that we were, we were able to have that thought, wouldn't that be useful, was because someone else was already doing something. They kind of bumped into the challenges that they experienced with their business model. So a lot of the things we do are just at a moment in time as entrepreneurs, and the things that we build, and it's learning from other people's experience. So these things don't stand learn at all.

And that's also true of Alloy. Hey, your point of knowing your history— maybe we can— I know you're really busy, so let me— the last question is just looking forward over the next 12 months, what are you most excited about Alloy? Uh, I'm excited about the RNA products personally. I think that's the next frontier in my, my opinion. Uh, and then maybe what else you look—

what are you excited about beyond Alloy? What am I excited about? So the first question is, what am I excited about at Alloy, kind of the products 2024? What 2024. What's on the docket? Oh my gosh, I just never want to cheat on my antibody and bispecific and TCR mimic background, of course. But yes, our third integrated modality in RNA medicines, led by Vinod Vathepatikal on our team and advised and also led by Sudhir Agrawal. So Sudhir got together with a member of our team, Chris Pacheco, and Andy Peterson. So Andy is actually the CEO of Broadwing, a company we co-founded with Maze Therapeutics in the ophthalmology space. So these things this like mishmash of things that come together. We all stay close and we swap notes and we do things. So Andy led us to Sudhir and Chris and to this discussion. Piotr Bobrowicz with the technical roadmap around RNA medicines, or just genetic medicines in general. It was a focus area we were paying attention. Sudhir was the inventor of GATMER, and he had licensed that technology to Ionis. There's obviously approved drugs, many drugs in the clinic, and Sudhir continued to work on things that would improve improve upon gapmer and make these, these antisense oligonucleotides even more effective. And Sidere invented and cooked up an incredibly exciting transiently circularized structure that it filed some IP on. We then got into a relationship with Sidere where our business model is we're seeking to share that with the world. That really resonated with Sidere. He wanted to, he wants to see this technology in the hands of as many companies as possible, make as many drugs as possible. We talk about access to our technology as having the appropriate level of exclusivity. Appropriate level, like what's appropriate? I don't know. So our bias is that everyone gets to use it, but that runs into business goals. And so what we know is if you just throw everything at open source, you will never get funded. And so there has to be a monetary component to this. So the appropriate level of access for some technologies, like a transgenic mouse that makes human antibodies, anyone in the world can use it. It in no way diminishes the value of that animal by somebody else using it. And then there's a layer of exclusivity for others. So our bias in developing this— so Sidir had this, this work, he'd filed some IP on it, and he had great data. We then started working with him, we recreated the data, we advanced it. We've been working together for a few years now. And man, this anti-clastic ASOs and the anti-clastic when it goes into siRNA, I think it just, it works. It's the cleanest data set I have ever seen. Around this. It just looks like an engineering problem at this point. Like, we see, like, you start to chemically modify it and you see just, like, wonderful curves that are super predictable. This has been done at CROs and also in our hands. I think as a venture capitalist, you kind of dream about someday waking up and finding some technology that came out of Harvard, MIT, that would look 10% as good as this dataset. It just works, and it's phenomenal. And I'm cautious to tell everyone I can take absolutely no credit for it. Like, literally, when this was proposed, I'm like, Gotta go read some review articles on like, what the hell is an ASO? It's— I'm like a little bit joking, but that's— that was like my level of sophistication when we're coming into RNA medicines was really led by first Piotr and then through some of our, you know, our EIR and our— the CEO of BroadWing. So you've got Andy, got a relationship with a few other folks. So all these folks come together just having an open heart and an open mind about how we collaborate. And people bring us wonderful things. And if you can validate those experiments with a few million dollars, for us, adding a whole platform like Keyway, it's kind of like the Adamab of TCR mimics. It's like, it's fully integrated, it's available, you can license it, you can replicate it, we're happy to do all your work for you. Like, in 20 years, there will be just as many soluble proteins that bind peptide MHC and an effector cell as there are antibodies in the clinic today. That is my prediction. That is true. We just need We just need to not fight over the IP. Everyone gets access to the platform, discover as many drugs as you want, may the best drug win. So that's our philosophy. And so for RNA medicines and for anti-clastic, so we're looking for other technologies and how we collaborate. I think there's some natural places like in delivery where it kind of should be a consortium model. Um, we certainly are, are very willing and happy to throw our IP into that and help to, uh, around delivery and otherwise. Now, anti-clastics are proprietary, the Cedir developed We continue to file on that, but it's certainly our goal and our bias in early '24, or instead of having conversations with big pharma, as the data were coming together this year and last year, it became really obvious that if we really want to push this hard into humans, we need to have one or two partners who want to go on the ride with us and put a lot of money into it. Our approach is to seek some partnerships with one or more pharma companies who want to want to talk about how they put some, some wood behind the arrows here. We think that's how we want to accelerate. So we kind of, we run these millions of dollars of experience, tens of millions of dollars experiment, kind of get to the point where you're like, oh my gosh, there's like, we got to figure out how to do this together. So we're out there actually with Locuswalk right now, who's been a great partner in some of the things we've done historically. So Jeff Meyerson and team at Locuswalk are having conversations with pharma companies around that data and working with Sidir and Vinod. It is really exciting. I'm really, really excited about that.