AI helped a small team design scorpion-toxin binders

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 1:39:35

   You know, this is going to change the world at record speed. So here's our first story related. Anthropic is using Claude to come up with scorpion anti-venom. So scorpions sting at least a million people per year. They killed 3,000 people, mostly children, in places with limited medical care. Today's anti-venoms are made from animals like horses. They're slow to produce, expensive. Each one only works on a certain species.

2. 1:40:03

   And because there's little money in this area, almost nobody develops new ones. So Anthropic tried something. Working with Citrini Research, it asked its internal CLAWD model to design tiny proteins called binders that grab onto the scorpion toxins and hold them tight. The hope of future anti-venom. CLAWD worked for 64 hours, mostly on its own. it designed more than 318,000 candidate proteins and picked the best 211. The result, 17 of the 211 worked and two grabbed their toxins extremely tightly. And then Anthropic open sourced all of this to allow labs to play with it, design, and actually produce these anti-venoms. I found this extraordinary and it's just the beginning of what we're going to see here. Alex?

3. 1:40:56

   Yeah, I would say there are a few levels of this. So first, get the obvious out of the way. Neurotoxins are cooked. It's over. It's almost over, I should say. The scorpions cooked. I mean, I don't want to cook scorpions, but let's say the neurotoxins from scorpions are cooked. I think biology overall, molecular biology, has been cooking, present continuous tense, since at least alpha-fold version 3, when arguably structural biology was solved almost overnight.

4. 1:41:29

   And I think in light of Anthropic opening up their own wet lab and also partnering, I think we are going to see more and more of these sorts of... It's not quite correct to call these rare, and it's not a disease, but anthropic stated strategy for the problems that they want to bulk solve in biology are, call them underfunded or underappreciated problems. It's rather difficult, my understanding is, to put together, scrape money for, say, antivenoms against scorpion or other neurotoxins.

5. 1:42:01

   It's not, say, as lucrative as GLP-1s or Wegovi. But nonetheless, it's a very real problem. And I view this as an early case study of what a frontier lab can do to bulk solve entire classes of problems in medicine and physiology. What anybody could do, it's where you point superintelligence. Your child just got injured by something, point superintelligence there. You know, your family has an issue, point superintelligence there.

6. 1:42:29

   The other... Really weird thing I have to point out, and this might have been below everyone's radar. The name, Cintrini Research, does that sound familiar to you? Anyone remember, like, awfully familiar name? Ring any bells? Wait, wait for it. Cintrini Research, remember, this was the... Tell me, Peter. This is... God, which sci-fi movie? No, no, no. These are the ones who are releasing this as an industry analyst that our friend Dylan Patel Semi-Analysis acquired.

7. 1:43:06

   This is an industry analyst for the broader IT industry that set up a therapeutic, my understanding is, that set up a therapeutics outfit, Citrini Therapeutics, that just decided, oh, we're going to go work with Anthropic and we're going to solve neurotoxins. This is unheard of. You don't have some random industry analyst decide, oh, we're going to solve the problem of scorpion neurotoxins, so let's just use Claude to design binders.

8. 1:43:35

   Clearly, one of them got bitten. Maybe. But I think this is the height of, I'm hesitant to call it casual grand challenge problem solving, but this is basically, as far as I can tell, casual grand challenge problem solving from an industry analyst. And we should ask Dylan about that. That's really important. Let's get the podcast team to research that and write it up because that, that should, like Peter, you're about to say, that should totally inspire people.

9. 1:44:01

   I've seen this over and over again. If you get inside the building at Anthropic or OpenAI or Google, no matter who you are and what you know, you come out successful. You just have to get in there. This would be the ultimate case study if, you know, IT consultants go and solve biology. But AI enables stuff like that. I mean, this is what I'm talking about entrepreneurs out there to kids out there to everybody out there.

10. 1:44:22

    Listen, whatever you thought you could do, blow the ceiling off it. Go 10 times bigger. What is a problem? Find a great problem and solve it. That's the world we're living in. I do want to read just a bit because this is indeed the case. Like literally, Dave, as you said, a bunch of IT analysts decide they're just going to solve grand challenge in biology. I'll read from Citrini Research's website.

11. 1:44:44

    Quote, why don't we try to use AI to create a new drug? Five of us, three with no background whatsoever in science, and two with a little, but who weren't exactly veteran drug developers, would see if this was possible. And they go and they solve scorpion neurotoxins. That's the age that we live in now. This is the age of abundance. This is optimism, everybody. This is why we're so excited.