Anthropic now runs its own biolab, a demonstration of how broad its ambitions have become, and on Wednesday it published its first discovery. About 950 Claude agents spent 21 hours going through more than 200,000 reverse transcriptases in public genome data. They flagged 3,500 candidate systems and wrote reports on the 20 strongest. One agent noticed a line of evenly spaced DNA repeats beside an enzyme in a virus that infects bacteria. That arrangement looks like CRISPR. Anthropic has called the system ART. Its human scientists have shown that the repeat array is converted into short RNAs, but nobody yet knows what ART does.
Anthropic's scientists decide which of Claude's ideas go to the bench.
The approach is interesting in itself. Anthropic has not given Claude control of lab robots. Claude reads data at large scale and proposes hypotheses, and people at the bench test the few that make it through. The team also records which of Claude's ideas its scientists decide to pursue. Those decisions are then used to shape how Claude ranks future ideas. The company is trying to reproduce scientific judgement, which is the skill every lab has least of.
“Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today.”
Anthropic reported a weakness in the method itself. The team ran ten more campaigns with the same setup, and none found the ART array again. None of the later agents looked at the right stretch of DNA. The discovery depended on a choice made by a single agent. For now, running more agents mainly increases the chance that one of them looks in the right place.
Many readers will be uneasy that a company warning about AI-enabled bioweapons now runs its own biology lab. That concern is reasonable. Anthropic turned on its strictest safeguards for Claude Opus 4 because it could not rule out that the model might help someone with basic scientific training build a biological weapon. The new lab works only at biosafety levels 1 and 2 and handles no human pathogens. Dario Amodei has said Claude may one day run experiments itself "with appropriate safeguards". Anthropic has not yet described those safeguards in public. The bigger risk comes from the skills the lab is building. Searching genomes for unusual systems and designing proteins that bind to specific targets can help medicine, and the same skills can be misused.
Anthropic is one of several groups building AI-driven labs, and each has made a different bet on where science is slowest:
- Edison Scientific runs no lab at all. Spun out of the non-profit FutureHouse in 2025 with $70 million, it sells Kosmos, an AI scientist that reads around 1,500 papers and writes tens of thousands of lines of analysis code in a single run. Its bet is that most of the answers are already in published work and in the data that drug companies hold.
- Lila Sciences, launched by Flagship Pioneering, the firm that created Moderna, is building fully automated labs across biology, chemistry and materials, where AI designs and runs the experiments and learns from the results. It has raised about $550 million and describes its goal as scientific superintelligence.
- Periodic Labs was founded last year by Liam Fedus, one of the creators of ChatGPT, and Ekin Doğuş Çubuk, who led materials discovery at Google DeepMind, with a $300 million first round. Its founders argue that the data needed to teach a model physics and chemistry does not exist online and can only come from running experiments. One early target is superconductors that work at higher temperatures.
- Isomorphic Labs, spun out of Google DeepMind and led by Demis Hassabis, works only on medicines. It raised $2.1 billion in May, partners with Novartis, Eli Lilly and Johnson & Johnson, and expects its first AI-designed drugs to reach clinical trials by the end of this year, a year later than first planned.
Anthropic sits between Edison and the automated labs. AI does the searching at huge scale, and people do the lab work.
Across all of these approaches, finding candidates is getting cheaper and understanding them is not. ART took less than a day to find, and working out its function will take months of lab work. Organisations that can pay for hundreds of millions of tokens and experienced scientists to review the results will move ahead. At Harvard, every student and member of faculty can request up to $2,500 a month of Claude, even as the university's research funding is under threat and it lays off staff.
Takeaways: Anthropic's lab has shown that AI agents can find new biology in data that people have already studied closely. So far this happens unreliably, and humans still do every experiment. The open questions are who checks the findings, how quickly the checks can be done, and what protects the process from misuse. Answers to those questions will decide who benefits from AI-driven biology, more than the number of discoveries does.