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SUPREME AI AGI

Prediction · What changes

A medicine whose target and molecule were found mainly with AI will be approved for patients by a major regulator.

Medium termMedium confidenceOpen

Why we think so

An AI-discovered drug has completed a randomised phase 2a trial with acceptable safety; multi-agent research systems are proposing candidates that pass lab tests. Larger trials take years, so this is a medium-term prediction.

What would prove us wrong

AI-discovered candidates failing in late-stage trials at a higher rate than conventionally discovered ones.

Horizon
Medium term. About 3 to 10 years out.
Confidence
Medium confidence
Status
Open. Not yet decided either way.
Made
21 October 2026
Research programs
Agent societies

The evidence it rests on

Public results from teams around the world. Read the sources and judge for yourself.

  • · Insilico Medicine and collaborators (published in Nature Medicine)

    An AI-discovered drug shows results in a randomised phase 2a trial

    Rentosertib, a drug whose target and molecule were found with generative AI, was tested in 71 patients with idiopathic pulmonary fibrosis. Safety was similar to placebo, and the highest dose showed a lung-function gain, though the trial was small.

    What it means for AGI: AI-designed medicines have reached patient trials. Approval still requires larger trials.

    Source: nature.com(opens external site)

  • · Google researchers (arXiv)

    Co-Scientist: a multi-agent system that proposes research hypotheses

    Specialised agents generate, critique and rank hypotheses in a tournament. Drug-repurposing candidates it proposed for acute myeloid leukaemia were validated in lab (in vitro) experiments.

    What it means for AGI: a team of agents, not a single model, did useful scientific work that was checked in a real lab.

    Source: arxiv.org(opens external site)

  • · Google DeepMind (published in Nature)

    AlphaFold predicts protein structures at near-experimental accuracy

    A deep-learning system predicted the 3D shape of proteins with accuracy close to lab experiments, solving a problem biology had worked on for about 50 years.

    What it means for AGI: AI can make real scientific progress in a narrow field. The open question is whether the same can happen across many fields at once.

    Source: nature.com(opens external site)

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