The AI-Designed Drug

The promise of AI drug discovery has always run ahead of its evidence. A Chinese company has now produced some of the hardest evidence yet. Insilico Medicine’s rentosertib is a treatment for idiopathic pulmonary fibrosis whose biological target was identified by artificial intelligence and whose molecule was designed by generative AI, and it has been through a real, peer-reviewed clinical trial.^[1]

The Phase IIa study, published in Nature Medicine in 2025, was a randomised, double-blind, placebo-controlled trial across 71 patients at 22 sites in China over twelve weeks.^[1] At the top dose, patients’ lung function improved, a mean change in forced vital capacity of +98 millilitres against −20 for placebo, a genuine, encouraging signal. Insilico has since advanced the drug into Phase III, making it the furthest-progressed fully AI-originated medicine in the world.^[1]

The target was found by an algorithm and the molecule drawn by one. What no algorithm can shortcut is the years of trials that decide whether it works.

Platforms and partners

Insilico is not alone. XtalPi, which pairs AI models with autonomous robotic labs, signed an AI-discovery deal with Eli Lilly worth up to $250 million in 2023, followed by a $345 million bispecific-antibody collaboration in 2025, and has an expanded partnership with Pfizer.^[2][3] For perspective, Western peers are at a similar or earlier stage: Isomorphic Labs, the DeepMind spin-out, was only preparing its first human trials of AI-designed drugs in early 2026.^[4]

The caveats are essential and easy to lose. Rentosertib’s Phase IIa was small and powered mainly for safety, not efficacy; the lung-function result is a promising secondary signal, not proof that the drug works, which only Phase III can establish. And “first AI-designed drug” is a contested label that depends on definitions. The achievement is real; it is not yet a cure.

Why we track this

AI drug discovery is where the gap between narrative and clinical proof is widest, and China now holds one of the field’s most credible, best-documented data points. That makes it a sector to underwrite on evidence rather than platform storytelling: a peer-reviewed trial and a Phase III advance count for more than a press release about billions of simulated molecules. We watch for read-throughs that clear the only bar that matters, late-stage efficacy in humans, and treat Chinese platforms like Insilico and XtalPi as front-runners in capability while pricing the whole category’s core risk honestly: AI can accelerate discovery, but it cannot yet shorten the trials that decide a drug’s fate.