Alloy Therapeutics raises $40M Series E to build full-stack AI biotech infrastructure across 17 time zones

this year with some more news.

Really appreciate it, guys. Thank you. Love the show, by the way.

Thank you. Have a good one.

You up next, we have Eric Anderson from Alloy Therapeutics. I love I love I love messing with you.

You love messing with me.

Never gets old.

Well, without further ado, Alloy Therapeutics has raised a series E to build full stack AI biotech infrastructure. Eric Anderson is here live with us. Eric, how are you doing,

gentlemen? I'm doing great today. Yeah, good to have you.

Thank you so much for hopping on. Uh first time on the show. Please introduce yourself and the company a bit.

I'm Eric Anderson. I'm the CEO and the founder of Alloy Therapeutics. We're a biotech infrastructure company that works with a bunch of companies all over the world helping people discover and develop drugs.

Okay, infrastructure. What exactly is going on in the biotech stack? I imagine everything from centrifuges down to bright and PDFs for the FDA to trials. There's so much that goes into that. What what are you focused on specifically?

You got that. So the the technology we have is really around more drug discovery and then into drug development. So the folks that do regulatory, the folks that do clinical, we work with them to discover drugs uh with the companies that we help to support. So we work with big pharma companies, we work with small biotech companies. What's going on in the industry today? The big trend right now is when we talk about infrastructure, who's going to actually do the wet lab work today in the lab. In addition, we've got everything going on with tech bio of all of this in silicico work that's happening. That's really exciting and sort of bringing those things together.

Yeah. Yeah. And the idea is the idea is like you can have like mill, you know, a million times more ideas for different drugs, but then you still have the constraint of the physical world needing to kind of be able to actually run experiments until ideally we could simulate a lot more in the future, but maybe we're not

not there yet.

Exactly. Right. And you can simulate all these things, but it's a bit of the design, build, test, and then you learn. It's that it's that loop we all know. Y

and right now in the biotech space, we've made some incredible progress with Gen AI and machine learning capabilities to come up with a lot of those ideas. You got to close the loop then and actually be able to test them. And then there's a lot of skill that goes in just the skill of drug development of of what makes a good drug and connecting those things together is what we do really well.

So how how much of this will wind up looking like an AWS for drug development? I can provision a certain machine and you have it and I can interface with it all over uh you know the internet and you will do all the physical stuff for me.

Yeah, that's part of it. So AWS just launched a service. Amazon launched a great service that connects

these these generative uh companies back to a back end of how you manufacture the protein and you test it.

That's one small piece to the process. I would say a lot of scientists out there that can design things in silico uh and then send them to a lab like that that will help.

Crazy. Is that not like a crazy side quest for them? Like it's

Wait, did AWS has like centrifuges now and like like

No, AWS is actually just connecting them together. No, it's it's pretty.

I think what they're going for there is that they want to be the cloud if you're going to do your compute to come up with these with these Encilico things. They want to make sure they see all the traffic and then just connect it to anyone else on the back end. Yeah. I think what they're doing.

Got it. Got it. Yeah. Uh so, um

can you zoom out for me and and just do a temperature check on biotech? We we read one article about how uh Boston's going through a really tough time. At the same time, like every time I open up the Wall Street Journal, there's a new billion dollar acquisition.

Yeah. last year felt like like the dark the dark ages for biotech felt like everyone every every uh bio biotech investor that we were talking to was like I don't even know why you'd keep investing in in these companies like the returns have been so bad and then this year is like the biggest year of biotech M&A since

it feels like they're just rich from the GLP1 boom but I'd love to hear your sort of like narrative setting

certainly the GLP1 boom one of the trends that's going on here is that the industry has to restock the shelves for new drugs. As drugs go off patent, there's these revenue cliffs. And so big pharma is sitting on probably the largest pile of capital they've ever sat on and they look to acquire a lot of their innovations from small companies. Those are the folks that we support to create new medicines. So there's definitely a huge M&A trend that's happening this year and it'll continue to happen for the foreseeable future. A big thing that's happening as you read about that news in Boston though is we're doing drug discovery and development here in the US. But there's been a big shift to move it overseas and to offshore it and for pharma to acquire assets from outside of the United States. And so that's that's been more of the big I would say the headwind for the domestic biotech space.

Okay. Uh how are you feeling about just acceleration in drug development generally? Like we you know in in cyber security agentic coding like there's these very clear uh scaling laws and you know we have the meter chart of the amount of time an AI system can work on a single problem. It's doubling. It's on a very clear trend. I haven't seen a chart that's like that for biotech, but it feels like we're going through advancements and we're just getting more cures. So, something's happening. But are you tracking it at a quantitative level yet or just qualitatively? How do you feel about uh drug development products?

Sure.

We're living in an era right now where the trend of all of the drugs that we're discovering. We have an acceleration in the amount of innovation that's coming from our labs. So, so that is just an incredible uh trend that is supporting everything we're doing in the lab. So, that the byproduct of that is of course generating massive amounts of more data, making sense of that data and this is where a lot of the machine learning is coming in is how do we digest all of the data that's being created in the industry making sense of it and then turning that into new cures as rapidly as possible. So that is an enormous trend right now in the industry.

Yeah.

Uh and and the advances that we have just from literally using cloud and open AI even in the lab and just day-to-day things. Yeah.

You're seeing a handful of things come together.

Huh.

So first of all, you see this explosion of data. You see the wet lab capabilities largely looking the same.

And what's happening then is we're trying to organize that data and turn it into new curus as rapidly as possible. and and in the background what we have is a number of new companies, new entrance in the tech bio space that I think are just natively better at understanding this massive data problem and being able to make sense of it.

And then on the other side, you have the pharma and biotech which are actually you require all of those skills to actually make sense of what's going to work in a in like a human biological system. Yeah.

So,

what's coming together this

this year, I would say, is that there's a lot more folks in tech bio that are getting better, but then we're just seeing the bio folks actually get better at tech. So,

basically, you're at this place where like the tech bio folks need more bio

and the biotech folks need more tech.

And if you're bringing those things together, I do think we're going to have an acceleration in a lot of the cures that we're making.

Interesting.

Uh, give us a view into how big pharma executives are thinking right now. How are they confused why everyone and their grandma is injecting themselves with Chinese peptides yet at the same time like hype more skeptical of vaccines than than uh maybe ever. I feel like this kind of this interesting uh uh dichotomy.

Yeah, it's well in the industry today, I would say the executives in farmer are looking at it from the same place they always do, which is about efficacy and patient safety. And so we're looking for drugs that work and then proving that they work in in animals and then ultimately in humans. So peptides being injected into humans, I think everyone's just saying, "Hey, what's safe? What's efficacious?" The FDA has done some pretty amazing things uh in this administration, I think, to give flexibility for what's allowed. Uh there's been some incredible changes that have happened that I think will accelerate uh the pace of innovation, what we do in the regulatory space, in the clinic as we're testing in humans. I think pharma is apprehensive about the changes, but overall they're excited that things are moving along and that we're going to see a lot new drugs coming on the market.

Can you help me understand uh the flow to get to like a data boom in biotech? because I I would assume that that's more driven by uh like dropping costs of DNA sequencing than anything from the Gen AI world because the but maybe there's something where the Gen AI world can process data that was previously like locked up in PDFs or something like what what is actually driving the data boom?

It's those things really coming together. So certainly the the continued falling cost of DNA sequencing. Yeah. And then the falling cost of all the other types of data that you can generate along with when you're sequencing someone's DNA. So if you go to a place like function health here or like what you can pull off your aura ring or your Apple Watch, there's actually a massive amount of data that is that is being generated passively.

And right now the ability to connect that data to I would call it real world data that we can connect to what's happening in patients. Yeah.

Is a level of complexity that we just haven't seen before on the data side.

Yeah. But it's got to be rooted back in basically the wet lab. You're describing these things of uh of taking your DNA or your tumor DNA and you're learning from what's actually happening in a patient.

Yeah.

And bringing those together is actually a huge data problem.

I I imagine you work with like mostly like big pharma or real biotech companies, but we're also seeing this like boom in like a single person vibe coding a cancer cure for their dog. like do you have a policy for whether like how small a team can be because I imagine it's not far from you getting like an inbound from like a single person who's like I want to do this by myself I'm a solo

I can be trusted with advanced AI by

and maybe they should maybe they shouldn't be I don't know I just want to know how you've like grappled with it maybe it's just not a business concern so you don't need to worry about it but I'd love to know like how are you processing that idea of

no I mean I think everyone could be trusted with this generally so that's actually not the current don't worry about kind of these fear mongering that's happening on this front. Okay.

Uh

at our company we service anyone who is interested in discovering new drugs. And so that's a lot of what we try to do with our company is how do we democratize access to many of these tools. Yeah.

We started in a particular place nearly 10 years ago. And that was before we had any of this Gen AI work going on.

Sure. Sure. And it is lower that single person biotech company or maybe just more of the the virtual biotech company where you've got five or 10 folks and they can work with a different contract research organization to help do their drug discovery and development.

That's been a trend for a while. What's happening is we're just getting more efficient at it today.

So I do think the future biotech company is going to be much much smaller and be able to plug into these different resources and be so much more efficient at coming up with ideas and testing them.

Yeah. Yeah. Yeah, I mean it is interesting. Uh tech loves to sing the praises of like the five or 10 person team, but there are a lot of biotech companies where it's like one genius researcher who discovered something and a couple support staff and then a lot of outsourced stuff all the way to okay, we're ready to sell it and it's mostly just a research or this is not entirely new there. uh you you mentioned that you're not worried about like doom related to uh like bio uh but like you know are how how how are you grappling with the idea of like somebody making a super bubanic plague or you know some new flu like are are do you feel like there's safeguards or h how have you processed that question

there there's lot groups of folks that are worried about this and I think the United States military and some of the the consortiums that we've been involved with are giving that thought it really comes down to though is you can make a lot of things that might be dangerous. There's always a bad actor problem. The way that we think about that is through our biocurity division. We try to make sure that the capabilities that we need to have in the United States are always available and accessible to us. So call it medical access capabilities. We learned a lot of lessons in co everything from could we actually just test for for viruses in the community and do we have the reagents available to do that and then of course we had masks and everything else. So from our perspective, we think about biocurity as a way of making sure that you do all of those components from being able to surveil what's happening in the theater all the way out to can we discover and develop a drug very rapidly. And there's some great uh different initiatives that are going on of these ideas. Can you go from a threat to 100 days later actually have a drug ready to go? and uh our company and others participate in in making sure that there's just a really robust response available with incredible supply chain and and sort of make sure we can do everything here in the United States at all times.

Yeah. Yeah. I mean it certainly seems like uh like the the the advancement in the positive side like we're seeing a major major uh swing to the upside right now. Uh every time I hear about one of these new medicines or new treatments it seems really positive. There was a huge story about pancreatic cancer recently which was a complete white

right right now we've got a conference that's going on and we saw two different studies that were showing just for some of the patients that were on drug it was six years later they still had no disease and that's saw we know about pancreatic cancer it is really really tough

oh it's it's really incredible it's one of the worst worst cancers we have but I think this is the overall trend we are living in a world where we will cure everything that is curable I think in the next three decades. It's really just a question of and maybe even faster than that. It's a question of how fast can we accelerate and really give as many people as possible access to these incredible tools. And just like in tech, I mean where you saw these very small companies be able to do incredible things in the last 5 10 15 years. I was investing back during the first internet bubble uh back in in venture capital 25 years ago. And in those times the world just looked a different place. We actually middleware was 10 years old. I I was I'm like 48 right now. So yeah, I was I was still a child.

You look late you look like late 30s. So So that's

that's good. Good for you.

I was a child at the time. But I mean it was incredible because there was a lot of the same criticisms that we're hearing in the tech space right now. And as it relates to biotech, it was like we were wrong about everything back then except for what we were right about.

Yeah.

We we did see the flow of investing coming in and many many things went bankrupt, but the things that didn't go bankrupt changed the world. Yeah. Yeah,

and that exact same thing is happening today that you're going to see incredible number of winners. And I do think biotech is going to be important part of the big market that everyone's going after uh in in the AI and the ML space as well. The tech space is going to go conquer biology as much as it has in other places. But I would say also that pharma and biotech very much have a seat at the table. Our academic researchers have a seat at the table there. And it's really about bringing the two domains together that are going to be critical. One of them is not going to go it alone uh without the other. Tell us more. I need more tech.

How much did you raise? How much did you raise?

Raised $40 million this time. Yeah, we hadn't raised any money.

We kick off. Thanks, man. Congratulations. Appreciate that.

We've been working hard to build a real business. So, yeah, this is been a long haul for us.

This is our series E. I'm a little old, but back when I was a child, when I was a baby investing 25 years ago, I uh I learned that you it's okay to just letter your rounds just like normal. Our last round was in 2022.

Yeah.

Yeah. I'm kind of old school in that way. So in 2022, we did a round and uh between then and now we really laid down the infrastructure so that we had operations across uh 17 time zones. Now we're operating the United States, Japan,

the UK. Um we have an incredible uh group that's actually working in the GCC right now in the Middle East. Obviously, there's a lot going on there that's uh that's creating a bit of a headwind, but we're very bullish on the work we're doing in Saudi Arabia, UAE, Riyad, and Doha and uh and and over in Abu Dhabi. So, yeah, bringing all this stuff together has been really important for us and just our view is you stitch together the supply chain of innovation, you link it to great world uh real world data and you bring a lot of AI and ML in there and we're going to really accelerate the pace of drug discovery and development.