Errik Anderson of Alloy Therapeutics discusses platform strategies in biotech, product development organizations and artificial intelligence-driven collaboration. The conversation is recorded at NYSE Wired: AI in Bio and hosted by theCUBE.
Anderson outlines Alloy Therapeutics' model as a biotech infrastructure and product development organization that offers technology-enabled services, a venture studio and selective acquisitions to support drug discovery and commercialization. They position Alloy as an AWS-like hyperscaler for biotech offering services, royalties and equity to align incentives and accelerate timelines, and they emphasize AI's role in lowering discovery costs, the value of proprietary private datasets and human-in-the-loop workflows and the need to manage human, regulatory and biological latency while fostering greater collaboration across pharma, startups and public stakeholders.
theCUBE hosts Gemma Allen, John Furrier and David Vellante frame the discussion, focusing on how AI, data and platform approaches reshape early-stage science and the pathways from discovery to clinical development.
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Errik Anderson, Alloy Therapeutics
Errik Anderson of Alloy Therapeutics discusses platform strategies in biotech, product development organizations and artificial intelligence-driven collaboration. The conversation is recorded at NYSE Wired: AI in Bio and hosted by theCUBE.
Anderson outlines Alloy Therapeutics' model as a biotech infrastructure and product development organization that offers technology-enabled services, a venture studio and selective acquisitions to support drug discovery and commercialization. They position Alloy as an AWS-like hyperscaler for biotech offering services, royalties and equity to align incentives and accelerate timelines, and they emphasize AI's role in lowering discovery costs, the value of proprietary private datasets and human-in-the-loop workflows and the need to manage human, regulatory and biological latency while fostering greater collaboration across pharma, startups and public stakeholders.
theCUBE hosts Gemma Allen, John Furrier and David Vellante frame the discussion, focusing on how AI, data and platform approaches reshape early-stage science and the pathways from discovery to clinical development.
play_circle_outlineAlloy Therapeutics: Biotech Infrastructure and Tech-Enabled Services from Discovery to Commercialization
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play_circle_outlineHyperscaler/AWS analogy: neutral platform powering industry participants and enabling ecosystem collaboration
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play_circle_outlineVenture Studios for Scientist-Entrepreneurs: Launching Early-Stage Drug Projects with Founders, Academics and Pharma Partners
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play_circle_outlineAligning incentives through cash, milestones, royalties, and equity to shorten timelines, reduce costs, and maximize clinical success
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play_circle_outlineFuture vision: become the "Walmart of biotech" — independent, scalable platform serving everyone
>> Palo Alto Studio connecting, SiliconANGLE and Wall Street. I'm John Furrier, co-hosting theCUBE here with David Vellante, my co-host.
Gemma Allen
>> Welcome back to theCUBE studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired. And today we have been talking all things AI and biotech. Joining me now to round off the day, last interview of this segment, and to have a conversation on the future and how this industry is converging and leveraging all of these hopeful solutions and technologies is Errik Anderson, CEO and founder of Alloy Therapeutics. Welcome, Errik.
Errik Anderson
>> Great to be with you today.
Gemma Allen
>> So your company is, like I said there, interesting, right? Because you were kind of in multiple pots, in multiple spaces, bringing a lot of therapies and opportunities together on one platform. Break it down for me. Tell the audience, what exactly is Alloy Therapeutics?
Errik Anderson
>> We're a biotech infrastructure company that we describe ourselves as a product development organization, which is a bit of a term we made up, where the feature of that is we do everything from basic research to commercialization to help support other people discovering and developing their drugs. We do not have our own drug pipeline though, which in our industry of pharmaceutical and biotech, it means that the only way we can get a drug approved is if our partners are successful.
Gemma Allen
>> Okay.
Errik Anderson
>> And so we develop proprietary sort of tech-enabled services that we would make available to anyone who is discovering or developing a drug. Some folks start with us in discovery, some folks start with us just in manufacturing or clinical trials now at this point. And we are just building this fully integrated product development organization that is taking the very long view of supporting everyone else's drug pipelines. and on the AI side, there's just some fascinating things that are happening kind of as a layer across that. It's pretty exciting.
Gemma Allen
>> Well, let me contextualize that, or help me too for a second. So you are building a lot of your own proprietary technology, your own, like mini, I guess, companies within this, correct? So are you like an AWS? how do you see this playing out? Do you see yourself becoming like a platform where folks can go and kind of pick and choose particular models? Or, are you looking to build everything yourself and own the kind of end-to-end relationship? What is the kind of—
Errik Anderson
>> I love that you asked that. You're the first person that's picked up on this product development organization model. We think about that as the hyperscaler of the future of biotech and pharma. What are the features of something like an AWS? AWS powers companies that are their customers, that are their suppliers, that are their competitors in some cases, as being just a universal service provider and truly takes a Switzerland-like approach to powering the whole industry. And everyone's success is their success. So almost in that way, yes, I very much think about it that way of how do we power everyone else's success? And so we just look to build these tech-enabled services. Yes, proprietary technologies, but we try to make them available to everyone, usually through a service layer, because that's how we make the business model work. Meaning you come to us with a problem and we give you back a drug or a service that works. But in some cases, the companies we work with, we transfer our technology to them and they can use it themselves.As well.
Gemma Allen
>> Okay, so AWS also does a great job of integration, right? It's seamless, it's connected, it's kind of one experience, and it creates this, almost like lock-in because it's so easy to do a lot of things in one place. What's the buy versus build decision for you? Do you think about spaces that you want to completely own versus working with partners or buying in technologies or capabilities? How do you balance that, especially in this market?
Errik Anderson
>> I think when I think about lock-in, I think more of, maybe the funny phrase you might knit on a pillow or something, is if you love something, set it free. I think what's really important is that you have a service platform that the customers are free to come and go as they choose, because it's actually, as we build an ecosystem, the best way to lead an ecosystem is one where you are providing value at all times. And the test of that is whether your customer is willing to willingly accept the services that you're providing throughout. Okay, so we run a number of different business units. They're all trying to provide services to be useful at any given moment. And it's great feedback from our customers that they choose to leave the platform or leave the ecosystem. That's actually a form of feedback. And so when we think about how do we build new technologies, how do we build new services, we're just always listening to our partners and to our customers. We also have a venture studio where we support great scientist entrepreneurs who are doing crazy cutting-edge things to make drugs, and they become some of our lighthouse customers who are doing something really creative, and we see these patterns of, oh, well, that's a problem no one's solving. So if there's no other service provider, we might make the service. If there's no technology that's kind of meeting exactly the need, we can take a multi-year investment horizon to make new technology, turn it into a service, offer it to that one customer, and then try to offer it to everybody else as well.
Gemma Allen
>> Okay.
Errik Anderson
>> We do acquisitions, but we're kind of more of like small-scale acquisitions because integrating cultures is a little bit challenging. Scaling those is easier almost sometimes to scale than it is to acquire and inherit somebody else's scaled culture.
Gemma Allen
>> Great. But I want to talk about the Venture Studio, and I want to talk about the moat. But first, I want to understand what— when you think about this from the perspective of a unique buyer persona for this, are we talking large pharma? Are we talking companies that are trying to, get something off the ground? New ventures? who's the unique persona that you're selling into?
Errik Anderson
>> I think of it as a scientist entrepreneur with a clever idea. That happens inside pharma all the time. The way that they buy and seek out partnerships and buy technology or services is a little different than a venture-backed biotech company. so the majority of our customers are venture-backed founders and biotech companies at the earliest stages, but we also work with academics and just solo entrepreneurs with a great idea, and we try to power them with the ability to do drug discovery as efficiently as possible. Sometimes it's easier to discover a drug than it is to start a whole biotech company. And so that's where our venture studio does come in. We try to be very efficient in doing that first stage of discovery. And if something works, well then we're looking to syndicate that either with venture capitalists or sometimes directly with pharma who's interested in early-stage pipeline products there.
Gemma Allen
>> So you're gathering a lot of data too in terms of the trial and error of this industry, which is famous for trial and error, right? But this is an interesting time. And when we think about, these companies that actually make it to market from discovery to a drug, that's highly profitable in the market, that percentage is still quite low.
Errik Anderson
>> That's right.
Gemma Allen
>> you must be spotting some trends, like what's changing, what's evolving, where are you seeing a lot of hope that that percentage will increase significantly? we know that a lot of money has flown into this industry since 2019, and there hasn't been a whole lot of FDA approvals, if any.
Errik Anderson
>> Yes.
Gemma Allen
>> break that down for me a little bit. How do you think about that?
Errik Anderson
>> The way to look at it is on a lag of 5 to 10 years to start with. So a lot of the inventions that we had on the technical side and insights that were in 2020 or 2015, we're just seeing those in the clinic today and seeing approvals. So as you see a lot of the investment come in, you have to think about it as a 5 and 10-year lag where maybe a patient is really going to experience a drug that's transformative to their health. So the places where we're seeing real bright spots, I would say, are these tech-enabled services where there's breakthroughs in enabling technologies that then later lead to breakthroughs in new medicine. So the Human Genome Project 25 years ago, when it was completed, became the blueprint by which so many other technologies and insights could derive from that. So that was like a public data set, and then a bunch of companies started generating private insights and private data on top of that. We see the same trend in 2026 where you have all of this public data that's just flooding the market, and really clever people are looking at those data sets and then deciding which experiments they run that augment that. And in our labs, we'll do more than 40 drug discovery projects this year with other companies. And the pattern we see across that is things that were super risky a year, 2, 3 years ago, people are now making better data-driven decisions around classes of patients that are a subsegment of something else where these highly biomarker-driven hypotheses, new targets, angles on new targets where we're seeing transformative effects of the biology. So the drugs are working so much better in a highly defined patient population.
Gemma Allen
>> And what's the business model here? Is this a platform? It's a subscription-based, is it outcome-based? Are you thinking about the world of usage-based like everyone else seems to be right now?
Errik Anderson
>> All of the above on those. It's our business model over the long run. We just look to make a dollar of profit across everything that we do. What makes us unique is that in some of our cases, we actually do have royalties or milestones because we do the drug discovery.
Gemma Allen
>> Okay.
Errik Anderson
>> What that means is we get paid to do the work, or maybe we lose money doing the actual drug discovery work, and then as the drug is successful, as it goes into the clinic and gets approved, we get multimillion-dollar milestones and then a percentage ultimately of drug sales. That makes us different than a typical service provider. Typical service provider falls into this trap of, I've gotta be paid for the work that I do today, And what ends up happening is a misaligned incentive of a typical contract research organization where as a CRO, you kind of want the timelines to go long because you want to make more money and you kind of want it to go slowly. We're very, very motivated with an aligned incentive that says we want the timelines to be short. We actually want the cost to be low, even past what we do in discovery and how we support in the clinic. And we're looking for the probability of success. So that convergence rate of a drug when it moves through the clinic How do we maximize that probability of success so that we reduce timelines and we get drugs approved faster?
Gemma Allen
>> Okay.
Errik Anderson
>> That's a unique feature of our business, but we get paid cash for services. We get later-paid milestones and royalties. We have equity in some of our projects. We own part of the companies. And so when they're successful and they go public, we participate in that. And then we plow all of that money back into building new services and making them available to everyone else in the world.
Gemma Allen
>> Wow. Like all good business models. So let's talk about the Venture Studio because you're by background a venture guy.
Errik Anderson
>> Yeah.
Gemma Allen
>> Biotech seems quite a unique animal from everything I've learned today. I've done quite the crash course, and venture dollars, we're told, are tight. A lot of folks come on the show and said it's very easy to raise money if you can prove the drug, the mass applicability of a drug, if you can bring a drug to market.
Errik Anderson
>> Sure.
Gemma Allen
>> It's harder to raise money in the kind of services-driven industry because it's coming from a different pot of spend.
Errik Anderson
>> Sure.
Gemma Allen
>> What are your thoughts? what are you seeing and what are you specifically scouting for?
Errik Anderson
>> Well, okay, what we're seeing is I look at trends in other industries. So as you mentioned, I was a tech investor before I was a biotech guy. if you look 25 years ago, the cost of doing a tech company today versus 25 years ago is 100 to 500 fold lower. It is easier to start a tech company. What that means is we see a lot of risk-taking in tech that was never possible in the year 2000 when I was in venture.We see a similar trend in biotech today. So although it feels like there's not enough capital available, that's always the problem in biotech, and we never have enough money to do what we do. It's actually the trends of AI and accessing these platform models like ours, or these service providers that are super high quality. It actually is lowering the cost of turning an idea into a medicine and then running the clinical trial. And we're really only in the early stages of how AI is changing how efficiently we do drug discovery and development. The consequence of that is I think we will see many more scientist entrepreneurs with really clever ideas around new drugs that will be able to get funded because what used to be a $10 million question is now a $1 million question. That's a 10x improvement in the cost of answering a deep scientific question. Our company powers exactly that. What we're trying to do is lower those costs and make those technologies available. We might spend 5 or 10 years developing a technology and if you've got a clever idea, we can do your drug discovery starting tomorrow and maybe finish it up in 3 or 4 months, 3 or 4 weeks in some cases in extreme discovery scenarios. And you didn't have to build the technology. You don't have to invest in all the timelines and then to answer your question. And so that's what we saw in the tech stack. When we think about circa 2000, when I started my first venture-backed biotech company, I had to start, I had to build the email server. I was a software guy before. I was literally Windows Server and starting the— that's crazy, right? To start a biotech company, you had to be good at IT. And now on your credit card, you can start a tech company easily.
Gemma Allen
>> Well, let's stay on the topic of tech for a second, and talk about what we always end up talking about on this show— AI, right? Specifically, these harness models, these LLMs, these frontier labs, what's being developed in that space, how proprietary some of the additional tech advancements are, especially for an industry like biotech. Heard about Claude Science. I hope I'm not misquoting that.
Errik Anderson
>> You got it. Yeah, yeah.
Gemma Allen
>> And I spoke to a chap earlier who told us about how he has partnered a lot with Anthropic on this, and they've kind of legitimized each other's work, I guess, in some respects. But what are you seeing happening? Because in other parts of tech, right, there is a little bit of a, yes, an enthusiasm, but also an inertia around who owns this relationship, who owns this data, who owns this model. is this like a cutting off my nose to spite my face approach to building something? What are you seeing and how do you think about that?
Errik Anderson
>> I think first, the first principles of our industry is that all value in our industry ultimately comes from a drug and a patient. And so everything else is derivative value, meaning if it goes to zero, the patient does not care. You are sick, you show up at your doctor, she gives you a drug that works. you do not care how long it took to make, you don't care how much it costs. So we just, you have to remember that as a first principle and that everything else is driving towards commoditization ideally, right? We're getting very, very efficient at doing these things. So the trends that we see in that and how AI is affecting this, I guess if that's the place where I would take this is how do we power the teams and the companies that are leveraging these technologies? So a foundational model is making us more efficient at everything we do. How it's making us efficient is changing every day based on the proprietary data that we generate. So there's all the public data. The NIH this year will fund $47 billion of, effectively public data generation. You gain advantage by having private data, and then we're using these foundational models. Many companies are building their own, sort of training their own weights and models on top of that. The harness you have on it is very interesting because that's something that I think is easily available for people to build their own harnesses. And you see an incredible difference in the effectiveness of some of the tools that we're using and we're building ourselves without even changing the foundational model.
Gemma Allen
>> So are you seeing people build harness layers? They're building wrappers.
Gemma Allen
>> It's—those are two different things. what are you truly seeing? Are people building on top, or are people actually building uniquely proprietary technology specifically for drug discovery?
Errik Anderson
>> We see both. We absolutely see both. And there's a limit to what you can actually do in drug discovery. I throw that in air quotes because, what part of it is actually the designing of the molecule?
Gemma Allen
>> It's—
Errik Anderson
>> there is a massive amount of data that's necessary to come up with a novel hypothesis of how the physics of protein folding works. There was an incredible innovation in this with AlphaFold. That was mainly public data with private insights and very clever and some private data, and they got a Nobel Prize for doing that. Incredible. So what's happening next is where are people developing their own private datasets and more importantly, their private insights? So we think about human in the loop as always being an important part of what we do in science. I don't think that's going away anytime soon.
Gemma Allen
>> I hope not.
Errik Anderson
>> Certainly not. But one of the things we do think a lot about is human latency versus biological latency. So one of the trends, no matter how good the models work, we see human latency trending towards zero in many of our activities. That bumps right up against something like regulatory latency. The FDA is going to take more time than we would like. That's probably a good thing because we wanna be careful when we're putting drugs into patients. So that's never gonna go down to zero. There's always gonna be latency in that. That's a form of human latency. Biological latency is really interesting because some experiments just take time. We run mouse studies all the time and it takes 3 weeks. I can't dose 3 mice in a 3-week study and get the answer in a week. You just, you can't do it. It takes 3 weeks to run that study in the same way that some clinical trials take 5 years to determine the endpoint. What's really exciting today though, when you think about that proprietary data that a pharma company is generating today for that clinical trial that might cost hundreds of millions of dollars and take 5 years, if they're doing it right, they're collecting data that the next time they run that trial, maybe they can do it with fewer patients or in 4 years or 3 years or 2 years. We're able to generate and then also document and analyze data because of the AI. So we have real-world data that's coming in through the lab or in the clinic. And if we're doing a good job of organizing that data, the next time we run a clinical trial, it'll be faster and it'll be more efficient and with fewer patients. And that's the flywheel that probably will play out over 3 and 5-year cycles. But the difference is 15, 20 years ago, we were on a 10 to 15-year drug cycle. What we're seeing today is maybe a 5 to 10-year drug cycle. So it's not totally obvious that it's happening, but from the inside, when we see how you go from an idea to a drug and we see what's going to work in a human, we see that in the discovery in the lab every single day. We see that in the clinic every single day. It's not obvious to patients until you see the compounding of that, I think through 2 or 3 cycles.
Gemma Allen
>> So Errik, what's ahead for you and the team at Alloy Therapeutics? What does the next 6, 12 months look like? What's the focus? Where are the big bets?
Errik Anderson
>> Two things. I come from a tech background, as you mentioned, so I think the biotech industry needs more tech, but the tech bio industry also needs more biotech. So we see that convergence. That's what's next. We're right at the nexus of that because we do both things. So we're native in that, and it's really exciting to see that trend. I think the other thing that's somewhat contrarian is the future of the pharmaceutical industry looks almost exactly like the present. What I mean by that is pharma will continue to sell drugs to patients, and they're going to work really hard on their internal drug discovery. And they're also going to access innovation through an external mechanism of buying small companies and collaborating and licensing with others. If there is something that has changed, I think that ability to collaborate is increasing. Sort of just the models of collaboration, the trends of collaboration, democratizing access to tools and technology and data is a huge driving force. So in the future, I see much more collaboration. we as a business are driving that as the fundamental part of our business. We will never have our own drug pipeline. Because we seek to collaborate with everyone. That's why our name is actually Alloy. It's right in the heart of what we do. And I don't think that's just us. I think we're able to be successful at this moment because it is a general trend over the last two decades that there's a willingness and an eagerness on the part of pharma, but also governments around the world, not just in the United States, patient advocacy groups, everyone that's participating in this global endeavor to make better medicine is willing to collaborate today in a way that was more challenging 10 years ago or 20 years ago. Or 30 years ago, and I think that trend's gonna get even better. So we'll access stuff
Gemma Allen
>> better.Well, I've definitely had some interesting conversations today with some folks in the space, and there's some phenomenal founders and innovators, and I've said to a few of them off camera, I really hope you stick with the chops in this, don't sell to big pharma, go the whole mile.
Gemma Allen
>> Yeah.Ring the bell at the New York Stock Exchange. we'd love to see more of this.
Errik Anderson
>> So it's interesting you say that because we're set up actually as a company that is designed to stay independent and to service everyone. So it's this idea. I think there needs to be large-scale companies. You think of some that are on the New York Stock Exchange that are very large, that service pharma, and they find a way to navigate a little bit like your AWS model. You find a way to navigate that tension between being a service provider, being even a customer of some of their products, a competitor in some ways. We need things like our product development organization, these scaled organizations that can truly grow forever and indefinitely. And if there were one thing that I would say I hope we aspire to be at Alloy is I just want to be the Walmart of biotech, right?
Gemma Allen
>> I love that.
Errik Anderson
>> That we are the platform company that we save people money so they live better lives is the core, that is the mission of Walmart. And that's kind of a beautiful mission.
Gemma Allen
>> A wholesome mission.
Errik Anderson
>> Completely. And so if we track towards that, how do we build the scaled business that can service everyone so that they can live better lives? And I do think that comes down to reducing costs, shortening timeframes, and helping everybody else be successful. So that would be my dream. I hope we are around, maybe ring the bell in the New York Stock Exchange, but definitely being an independent service provider and a technology provider to everyone around the world, hopefully as efficiently as possible. That's our goal.
Gemma Allen
>> Well, Errik, you gave me the perfect coined phrase to finish out today on these 10 interviews we've had with biotech founders, and that is the future of biotech needs more tech. And we've certainly heard some really innovative stories and, developments today that were new to me. So I've learned a lot. So thank you so much.Thank you for joining us.
Errik Anderson
>> This is amazing.
Gemma Allen
>> Yeah, I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is NYSE Wired: AI in Bio. We had some great conversations with some true leaders of industry. We also have our MedTech Unplugged series. We talk to folks on an ongoing basis who are reshaping the medical technology space of tomorrow. Thanks so much for watching.
>> Palo Alto Studio connecting, SiliconANGLE and Wall Street. I'm John Furrier, co-hosting theCUBE here with David Vellante, my co-host.
Gemma Allen
>> Welcome back to theCUBE studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired. And today we have been talking all things AI and biotech. Joining me now to round off the day, last interview of this segment, and to have a conversation on the future and how this industry is converging and leveraging all of these hopeful solutions and technologies is Errik Anderson, CEO and founder of Alloy Therapeutics. Welcome, Errik.
Errik Anderson
>> Great to be with you today.
Gemma Allen
>> So your company is, like I said there, interesting, right? Because you were kind of in multiple pots, in multiple spaces, bringing a lot of therapies and opportunities together on one platform. Break it down for me. Tell the audience, what exactly is Alloy Therapeutics?
Errik Anderson
>> We're a biotech infrastructure company that we describe ourselves as a product development organization, which is a bit of a term we made up, where the feature of that is we do everything from basic research to commercialization to help support other people discovering and developing their drugs. We do not have our own drug pipeline though, which in our industry of pharmaceutical and biotech, it means that the only way we can get a drug approved is if our partners are successful.
Gemma Allen
>> Okay.
Errik Anderson
>> And so we develop proprietary sort of tech-enabled services that we would make available to anyone who is discovering or developing a drug. Some folks start with us in discovery, some folks start with us just in manufacturing or clinical trials now at this point. And we are just building this fully integrated product development organization that is taking the very long view of supporting everyone else's drug pipelines. and on the AI side, there's just some fascinating things that are happening kind of as a layer across that. It's pretty exciting.
Gemma Allen
>> Well, let me contextualize that, or help me too for a second. So you are building a lot of your own proprietary technology, your own, like mini, I guess, companies within this, correct? So are you like an AWS? how do you see this playing out? Do you see yourself becoming like a platform where folks can go and kind of pick and choose particular models? Or, are you looking to build everything yourself and own the kind of end-to-end relationship? What is the kind of—
Errik Anderson
>> I love that you asked that. You're the first person that's picked up on this product development organization model. We think about that as the hyperscaler of the future of biotech and pharma. What are the features of something like an AWS? AWS powers companies that are their customers, that are their suppliers, that are their competitors in some cases, as being just a universal service provider and truly takes a Switzerland-like approach to powering the whole industry. And everyone's success is their success. So almost in that way, yes, I very much think about it that way of how do we power everyone else's success? And so we just look to build these tech-enabled services. Yes, proprietary technologies, but we try to make them available to everyone, usually through a service layer, because that's how we make the business model work. Meaning you come to us with a problem and we give you back a drug or a service that works. But in some cases, the companies we work with, we transfer our technology to them and they can use it themselves.As well.
Gemma Allen
>> Okay, so AWS also does a great job of integration, right? It's seamless, it's connected, it's kind of one experience, and it creates this, almost like lock-in because it's so easy to do a lot of things in one place. What's the buy versus build decision for you? Do you think about spaces that you want to completely own versus working with partners or buying in technologies or capabilities? How do you balance that, especially in this market?
Errik Anderson
>> I think when I think about lock-in, I think more of, maybe the funny phrase you might knit on a pillow or something, is if you love something, set it free. I think what's really important is that you have a service platform that the customers are free to come and go as they choose, because it's actually, as we build an ecosystem, the best way to lead an ecosystem is one where you are providing value at all times. And the test of that is whether your customer is willing to willingly accept the services that you're providing throughout. Okay, so we run a number of different business units. They're all trying to provide services to be useful at any given moment. And it's great feedback from our customers that they choose to leave the platform or leave the ecosystem. That's actually a form of feedback. And so when we think about how do we build new technologies, how do we build new services, we're just always listening to our partners and to our customers. We also have a venture studio where we support great scientist entrepreneurs who are doing crazy cutting-edge things to make drugs, and they become some of our lighthouse customers who are doing something really creative, and we see these patterns of, oh, well, that's a problem no one's solving. So if there's no other service provider, we might make the service. If there's no technology that's kind of meeting exactly the need, we can take a multi-year investment horizon to make new technology, turn it into a service, offer it to that one customer, and then try to offer it to everybody else as well.
Gemma Allen
>> Okay.
Errik Anderson
>> We do acquisitions, but we're kind of more of like small-scale acquisitions because integrating cultures is a little bit challenging. Scaling those is easier almost sometimes to scale than it is to acquire and inherit somebody else's scaled culture.
Gemma Allen
>> Great. But I want to talk about the Venture Studio, and I want to talk about the moat. But first, I want to understand what— when you think about this from the perspective of a unique buyer persona for this, are we talking large pharma? Are we talking companies that are trying to, get something off the ground? New ventures? who's the unique persona that you're selling into?
Errik Anderson
>> I think of it as a scientist entrepreneur with a clever idea. That happens inside pharma all the time. The way that they buy and seek out partnerships and buy technology or services is a little different than a venture-backed biotech company. so the majority of our customers are venture-backed founders and biotech companies at the earliest stages, but we also work with academics and just solo entrepreneurs with a great idea, and we try to power them with the ability to do drug discovery as efficiently as possible. Sometimes it's easier to discover a drug than it is to start a whole biotech company. And so that's where our venture studio does come in. We try to be very efficient in doing that first stage of discovery. And if something works, well then we're looking to syndicate that either with venture capitalists or sometimes directly with pharma who's interested in early-stage pipeline products there.
Gemma Allen
>> So you're gathering a lot of data too in terms of the trial and error of this industry, which is famous for trial and error, right? But this is an interesting time. And when we think about, these companies that actually make it to market from discovery to a drug, that's highly profitable in the market, that percentage is still quite low.
Errik Anderson
>> That's right.
Gemma Allen
>> you must be spotting some trends, like what's changing, what's evolving, where are you seeing a lot of hope that that percentage will increase significantly? we know that a lot of money has flown into this industry since 2019, and there hasn't been a whole lot of FDA approvals, if any.
Errik Anderson
>> Yes.
Gemma Allen
>> break that down for me a little bit. How do you think about that?
Errik Anderson
>> The way to look at it is on a lag of 5 to 10 years to start with. So a lot of the inventions that we had on the technical side and insights that were in 2020 or 2015, we're just seeing those in the clinic today and seeing approvals. So as you see a lot of the investment come in, you have to think about it as a 5 and 10-year lag where maybe a patient is really going to experience a drug that's transformative to their health. So the places where we're seeing real bright spots, I would say, are these tech-enabled services where there's breakthroughs in enabling technologies that then later lead to breakthroughs in new medicine. So the Human Genome Project 25 years ago, when it was completed, became the blueprint by which so many other technologies and insights could derive from that. So that was like a public data set, and then a bunch of companies started generating private insights and private data on top of that. We see the same trend in 2026 where you have all of this public data that's just flooding the market, and really clever people are looking at those data sets and then deciding which experiments they run that augment that. And in our labs, we'll do more than 40 drug discovery projects this year with other companies. And the pattern we see across that is things that were super risky a year, 2, 3 years ago, people are now making better data-driven decisions around classes of patients that are a subsegment of something else where these highly biomarker-driven hypotheses, new targets, angles on new targets where we're seeing transformative effects of the biology. So the drugs are working so much better in a highly defined patient population.
Gemma Allen
>> And what's the business model here? Is this a platform? It's a subscription-based, is it outcome-based? Are you thinking about the world of usage-based like everyone else seems to be right now?
Errik Anderson
>> All of the above on those. It's our business model over the long run. We just look to make a dollar of profit across everything that we do. What makes us unique is that in some of our cases, we actually do have royalties or milestones because we do the drug discovery.
Gemma Allen
>> Okay.
Errik Anderson
>> What that means is we get paid to do the work, or maybe we lose money doing the actual drug discovery work, and then as the drug is successful, as it goes into the clinic and gets approved, we get multimillion-dollar milestones and then a percentage ultimately of drug sales. That makes us different than a typical service provider. Typical service provider falls into this trap of, I've gotta be paid for the work that I do today, And what ends up happening is a misaligned incentive of a typical contract research organization where as a CRO, you kind of want the timelines to go long because you want to make more money and you kind of want it to go slowly. We're very, very motivated with an aligned incentive that says we want the timelines to be short. We actually want the cost to be low, even past what we do in discovery and how we support in the clinic. And we're looking for the probability of success. So that convergence rate of a drug when it moves through the clinic How do we maximize that probability of success so that we reduce timelines and we get drugs approved faster?
Gemma Allen
>> Okay.
Errik Anderson
>> That's a unique feature of our business, but we get paid cash for services. We get later-paid milestones and royalties. We have equity in some of our projects. We own part of the companies. And so when they're successful and they go public, we participate in that. And then we plow all of that money back into building new services and making them available to everyone else in the world.
Gemma Allen
>> Wow. Like all good business models. So let's talk about the Venture Studio because you're by background a venture guy.
Errik Anderson
>> Yeah.
Gemma Allen
>> Biotech seems quite a unique animal from everything I've learned today. I've done quite the crash course, and venture dollars, we're told, are tight. A lot of folks come on the show and said it's very easy to raise money if you can prove the drug, the mass applicability of a drug, if you can bring a drug to market.
Errik Anderson
>> Sure.
Gemma Allen
>> It's harder to raise money in the kind of services-driven industry because it's coming from a different pot of spend.
Errik Anderson
>> Sure.
Gemma Allen
>> What are your thoughts? what are you seeing and what are you specifically scouting for?
Errik Anderson
>> Well, okay, what we're seeing is I look at trends in other industries. So as you mentioned, I was a tech investor before I was a biotech guy. if you look 25 years ago, the cost of doing a tech company today versus 25 years ago is 100 to 500 fold lower. It is easier to start a tech company. What that means is we see a lot of risk-taking in tech that was never possible in the year 2000 when I was in venture.We see a similar trend in biotech today. So although it feels like there's not enough capital available, that's always the problem in biotech, and we never have enough money to do what we do. It's actually the trends of AI and accessing these platform models like ours, or these service providers that are super high quality. It actually is lowering the cost of turning an idea into a medicine and then running the clinical trial. And we're really only in the early stages of how AI is changing how efficiently we do drug discovery and development. The consequence of that is I think we will see many more scientist entrepreneurs with really clever ideas around new drugs that will be able to get funded because what used to be a $10 million question is now a $1 million question. That's a 10x improvement in the cost of answering a deep scientific question. Our company powers exactly that. What we're trying to do is lower those costs and make those technologies available. We might spend 5 or 10 years developing a technology and if you've got a clever idea, we can do your drug discovery starting tomorrow and maybe finish it up in 3 or 4 months, 3 or 4 weeks in some cases in extreme discovery scenarios. And you didn't have to build the technology. You don't have to invest in all the timelines and then to answer your question. And so that's what we saw in the tech stack. When we think about circa 2000, when I started my first venture-backed biotech company, I had to start, I had to build the email server. I was a software guy before. I was literally Windows Server and starting the— that's crazy, right? To start a biotech company, you had to be good at IT. And now on your credit card, you can start a tech company easily.
Gemma Allen
>> Well, let's stay on the topic of tech for a second, and talk about what we always end up talking about on this show— AI, right? Specifically, these harness models, these LLMs, these frontier labs, what's being developed in that space, how proprietary some of the additional tech advancements are, especially for an industry like biotech. Heard about Claude Science. I hope I'm not misquoting that.
Errik Anderson
>> You got it. Yeah, yeah.
Gemma Allen
>> And I spoke to a chap earlier who told us about how he has partnered a lot with Anthropic on this, and they've kind of legitimized each other's work, I guess, in some respects. But what are you seeing happening? Because in other parts of tech, right, there is a little bit of a, yes, an enthusiasm, but also an inertia around who owns this relationship, who owns this data, who owns this model. is this like a cutting off my nose to spite my face approach to building something? What are you seeing and how do you think about that?
Errik Anderson
>> I think first, the first principles of our industry is that all value in our industry ultimately comes from a drug and a patient. And so everything else is derivative value, meaning if it goes to zero, the patient does not care. You are sick, you show up at your doctor, she gives you a drug that works. you do not care how long it took to make, you don't care how much it costs. So we just, you have to remember that as a first principle and that everything else is driving towards commoditization ideally, right? We're getting very, very efficient at doing these things. So the trends that we see in that and how AI is affecting this, I guess if that's the place where I would take this is how do we power the teams and the companies that are leveraging these technologies? So a foundational model is making us more efficient at everything we do. How it's making us efficient is changing every day based on the proprietary data that we generate. So there's all the public data. The NIH this year will fund $47 billion of, effectively public data generation. You gain advantage by having private data, and then we're using these foundational models. Many companies are building their own, sort of training their own weights and models on top of that. The harness you have on it is very interesting because that's something that I think is easily available for people to build their own harnesses. And you see an incredible difference in the effectiveness of some of the tools that we're using and we're building ourselves without even changing the foundational model.
Gemma Allen
>> So are you seeing people build harness layers? They're building wrappers.
Gemma Allen
>> It's—those are two different things. what are you truly seeing? Are people building on top, or are people actually building uniquely proprietary technology specifically for drug discovery?
Errik Anderson
>> We see both. We absolutely see both. And there's a limit to what you can actually do in drug discovery. I throw that in air quotes because, what part of it is actually the designing of the molecule?
Gemma Allen
>> It's—
Errik Anderson
>> there is a massive amount of data that's necessary to come up with a novel hypothesis of how the physics of protein folding works. There was an incredible innovation in this with AlphaFold. That was mainly public data with private insights and very clever and some private data, and they got a Nobel Prize for doing that. Incredible. So what's happening next is where are people developing their own private datasets and more importantly, their private insights? So we think about human in the loop as always being an important part of what we do in science. I don't think that's going away anytime soon.
Gemma Allen
>> I hope not.
Errik Anderson
>> Certainly not. But one of the things we do think a lot about is human latency versus biological latency. So one of the trends, no matter how good the models work, we see human latency trending towards zero in many of our activities. That bumps right up against something like regulatory latency. The FDA is going to take more time than we would like. That's probably a good thing because we wanna be careful when we're putting drugs into patients. So that's never gonna go down to zero. There's always gonna be latency in that. That's a form of human latency. Biological latency is really interesting because some experiments just take time. We run mouse studies all the time and it takes 3 weeks. I can't dose 3 mice in a 3-week study and get the answer in a week. You just, you can't do it. It takes 3 weeks to run that study in the same way that some clinical trials take 5 years to determine the endpoint. What's really exciting today though, when you think about that proprietary data that a pharma company is generating today for that clinical trial that might cost hundreds of millions of dollars and take 5 years, if they're doing it right, they're collecting data that the next time they run that trial, maybe they can do it with fewer patients or in 4 years or 3 years or 2 years. We're able to generate and then also document and analyze data because of the AI. So we have real-world data that's coming in through the lab or in the clinic. And if we're doing a good job of organizing that data, the next time we run a clinical trial, it'll be faster and it'll be more efficient and with fewer patients. And that's the flywheel that probably will play out over 3 and 5-year cycles. But the difference is 15, 20 years ago, we were on a 10 to 15-year drug cycle. What we're seeing today is maybe a 5 to 10-year drug cycle. So it's not totally obvious that it's happening, but from the inside, when we see how you go from an idea to a drug and we see what's going to work in a human, we see that in the discovery in the lab every single day. We see that in the clinic every single day. It's not obvious to patients until you see the compounding of that, I think through 2 or 3 cycles.
Gemma Allen
>> So Errik, what's ahead for you and the team at Alloy Therapeutics? What does the next 6, 12 months look like? What's the focus? Where are the big bets?
Errik Anderson
>> Two things. I come from a tech background, as you mentioned, so I think the biotech industry needs more tech, but the tech bio industry also needs more biotech. So we see that convergence. That's what's next. We're right at the nexus of that because we do both things. So we're native in that, and it's really exciting to see that trend. I think the other thing that's somewhat contrarian is the future of the pharmaceutical industry looks almost exactly like the present. What I mean by that is pharma will continue to sell drugs to patients, and they're going to work really hard on their internal drug discovery. And they're also going to access innovation through an external mechanism of buying small companies and collaborating and licensing with others. If there is something that has changed, I think that ability to collaborate is increasing. Sort of just the models of collaboration, the trends of collaboration, democratizing access to tools and technology and data is a huge driving force. So in the future, I see much more collaboration. we as a business are driving that as the fundamental part of our business. We will never have our own drug pipeline. Because we seek to collaborate with everyone. That's why our name is actually Alloy. It's right in the heart of what we do. And I don't think that's just us. I think we're able to be successful at this moment because it is a general trend over the last two decades that there's a willingness and an eagerness on the part of pharma, but also governments around the world, not just in the United States, patient advocacy groups, everyone that's participating in this global endeavor to make better medicine is willing to collaborate today in a way that was more challenging 10 years ago or 20 years ago. Or 30 years ago, and I think that trend's gonna get even better. So we'll access stuff
Gemma Allen
>> better.Well, I've definitely had some interesting conversations today with some folks in the space, and there's some phenomenal founders and innovators, and I've said to a few of them off camera, I really hope you stick with the chops in this, don't sell to big pharma, go the whole mile.
Gemma Allen
>> Yeah.Ring the bell at the New York Stock Exchange. we'd love to see more of this.
Errik Anderson
>> So it's interesting you say that because we're set up actually as a company that is designed to stay independent and to service everyone. So it's this idea. I think there needs to be large-scale companies. You think of some that are on the New York Stock Exchange that are very large, that service pharma, and they find a way to navigate a little bit like your AWS model. You find a way to navigate that tension between being a service provider, being even a customer of some of their products, a competitor in some ways. We need things like our product development organization, these scaled organizations that can truly grow forever and indefinitely. And if there were one thing that I would say I hope we aspire to be at Alloy is I just want to be the Walmart of biotech, right?
Gemma Allen
>> I love that.
Errik Anderson
>> That we are the platform company that we save people money so they live better lives is the core, that is the mission of Walmart. And that's kind of a beautiful mission.
Gemma Allen
>> A wholesome mission.
Errik Anderson
>> Completely. And so if we track towards that, how do we build the scaled business that can service everyone so that they can live better lives? And I do think that comes down to reducing costs, shortening timeframes, and helping everybody else be successful. So that would be my dream. I hope we are around, maybe ring the bell in the New York Stock Exchange, but definitely being an independent service provider and a technology provider to everyone around the world, hopefully as efficiently as possible. That's our goal.
Gemma Allen
>> Well, Errik, you gave me the perfect coined phrase to finish out today on these 10 interviews we've had with biotech founders, and that is the future of biotech needs more tech. And we've certainly heard some really innovative stories and, developments today that were new to me. So I've learned a lot. So thank you so much.Thank you for joining us.
Errik Anderson
>> This is amazing.
Gemma Allen
>> Yeah, I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is NYSE Wired: AI in Bio. We had some great conversations with some true leaders of industry. We also have our MedTech Unplugged series. We talk to folks on an ongoing basis who are reshaping the medical technology space of tomorrow. Thanks so much for watching.
Gemma Allen
