In a development that will shock absolutely no one with a passing familiarity with either biology or hype cycles, an investment research firm has learned that an unreleased version of Anthropic's Claude cannot, in fact, conjure a working scorpion antivenom out of thin air. Citrini Research, the firm behind the experiment, teamed up with Anthropic to test whether AI could revolutionize drug development. It could not. It produced some promising starting points and precisely zero actual drugs, experts told The Verge.
Citrini, by its own admission, went in with essentially no relevant expertise, conceding that "none of us could claim to know anything about AI as it related to biology." Undeterred, the firm pressed on, eventually publishing a blog post titled "We Wanted to Use Claude to Create a New Drug. Here's What Happened." The account featured rhetorical questions like "Why don't we try to use AI to create a new drug?", a blow-by-blow of its amateur scientific adventures, and a quote from Charles Darwin - because nothing says rigorous pharmaceutical research like a 19th-century naturalist dropped in for gravitas.
If Citrini sounds familiar, it's because the firm previously circulated a piece of fiction imagining an AI-induced economic catastrophe that went viral on social media and rattled real-world markets. It also claims to have visited the Strait of Hormuz in April to get a firsthand perspective on the volatile region. For its latest venture, Citrini enlisted Anthropic, which - mere weeks out from its hotly anticipated IPO - has several reasons to talk up AI's potential in drug development and the life sciences, two areas it's actively pursuing.
The collaboration began after Citrini tripped over Claude's biosecurity guardrails while trying to get the model to research drug candidates. The post's author said they "spam called anyone in my contact list who worked at an AI lab," eventually finding a willing partner in Anthropic. The AI lab agreed to drop the restrictions and grant access to a more advanced, unreleased model on the condition that the team work from its offices. Conveniently, Anthropic also agreed to foot the compute and token bill, which came just shy of $50,000.
After weighing a few options, the team settled on scorpion antivenom, a costly treatment that's difficult to produce and often involves injecting venom into horses. The goal was to use Claude to design proteins that could bind to the toxins in scorpion venom. Armed with a 35-page prompt, they set the AI to work, unleashing some 300 subagents to hunt for suitable proteins.
In its own more sober account, Anthropic said Claude generated nearly 320,000 candidates, whittling them down to 180 designs after discarding those resembling known toxins or existing proteins. The whole process took 64 hours. Anthropic said the team worked "with Claude" to add another 31 designs, bringing the total to 211.
Citrini then shipped the designs to two outside laboratories - Swiss biotech company Adaptyv Bio and US-based Twist Biosciences - to test whether the proteins could actually bind to their intended targets, a key step toward an effective antivenom. That cost another $150,000, give or take. It's unclear why Anthropic couldn't have run these tests in-house at its biology wet lab in California. Seventeen proteins passed muster, collectively binding to four of the five scorpion toxins the team had hoped to target. Not one of the proteins bound to more than a single toxin, Citrini said.
Even had they managed that, Citrini would still be a very long way from a working antivenom. Binding to a toxin does not mean a protein can neutralize it, let alone serve as a safe and effective treatment. Citrini acknowledges as much, noting that "no experiment has yet tested whether they actually stopped the toxin working."
In other words, the experiment did not succeed. Citrini set out to make a new drug and, according to experts who spoke with The Verge, accomplished only the relatively "easy" part of the process. "It is easy-ish to discover a good binder against snake and scorpion toxins," said Andreas Hougaard Laustsen-Kiel, a professor of antibody technologies at the Technical University of Denmark. "The hard part is to translate it into a medicine."
Melisa Benard Valle, an assistant professor, and Anne Ljungars, a senior researcher, both at the Technical University of Denmark, agreed. "The results are technically promising, but some of the excitement is premature," they wrote in a joint email, describing the findings as "far from a medicine and hyped." Much remains unknown about the proteins Claude designed, they said, including their safety, stability, behavior in the body, and whether they can be developed into viable treatments. "Translating these binders into an actual medicine is likely still a long and challenging process."
The most novel aspect of Citrini's experiment, they said, was the "autonomous discovery process rather than the biological results." AI has huge potential to accelerate discovery, they added, but warned that "turning promising molecules into effective medicines remains a much greater challenge."
Nor is the underlying approach particularly new. Andreas Bender, a professor of machine learning in medicine at Khalifa University in Abu Dhabi and a visiting professor at the University of Cambridge, told The Verge that existing methods like high-throughput screening "are often able to find a multitude of hits at manageable cost," even without any AI. Designing proteins that bind to targets is "kind of" a solved problem, Bender said. The much harder challenge is turning those results into treatments that work in living systems. "It's exactly this translation that lacks."
While it failed to make a drug, Citrini declared the experiment a success of sorts, arguing it offers a glimpse into the investment opportunities emerging in the coming era of AI-enabled drug discovery. As for why it didn't take the research further? Citrini accused critics of "nitpick[ing]" and added, "Not to beat a dead horse, but we are an investment research firm - not a biotech startup." Citrini and Anthropic did not respond to requests for comment.
It still made a bullish case for companies that might benefit. Naturally, the specifics were reserved for paying subscribers, though Bloomberg reports the firm highlighted companies involved in the testing side of drug development, including Charles River Laboratories, which supplies primates for animal research. In a video discussing the experiment, Citrini described the AI portion as "free," conveniently overlooking the tab picked up by Anthropic.