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categories: ["foundations", "longevity"]categories: ["foundations", "longevity"]tags: ["machine learning", "drug development", "generative chemistry", "target discovery", "clinical trials", "pharmacology"]tags: ["machine learning", "drug development", "generative chemistry", "target discovery", "clinical trials", "pharmacology"]summary: "The use of machine learning to select drug targets, generate candidate molecules and predict failure, so far demonstrably faster at making compounds than at making medicines."summary: "The use of machine learning to select drug targets, generate candidate molecules and predict failure, so far demonstrably faster at making compounds than at making medicines."updated: "2026-08-22"updated: "2026-10-27"humanEvidence: "AI-derived small molecules have reached phase 1 and 2 trials, with a first phase 3 begun in 2026; sponsors of an mRNA therapy built on algorithm-selected neoantigens report a phase 3 in melanoma met its endpoints, and no drug from either route is approved."humanEvidence: "AI-derived small molecules have reached phase 1 and 2 trials, with a first phase 3 begun in 2026; sponsors of an mRNA therapy built on algorithm-selected neoantigens report a phase 3 in melanoma met its endpoints, and no drug from either route is approved."access: "Platforms are proprietary to pharmaceutical companies or licensed to them, and some models and datasets are public; no molecule designed this way is available outside a trial, though AI-suggested uses of approved drugs are."access: "Platforms are proprietary to pharmaceutical companies or licensed to them, and some models and datasets are public; no molecule designed this way is available outside a trial, though AI-suggested uses of approved drugs are."reversibility: "context"reversibility: "context"lines 69–75 → 69–7854 unchanged lines not shown
**Structure and synthesis.** Protein structure prediction, covered under [[ai-protein-design]],**Structure and synthesis.** Protein structure prediction, covered under [[ai-protein-design]],opened pocket-based design to proteins with no experimental structure, though benchmark studies ofopened pocket-based design to proteins with no experimental structure, though benchmark studies ofdocking have found predicted structures to perform worse than experimental ones. Retrosynthesisdocking have found predicted structures to perform worse than experimental ones. The companybuilt most directly on AlphaFold is [[isomorphic-labs|Isomorphic Labs]], the Alphabet spin-out fromDeepMind that co-developed AlphaFold 3; despite partnerships with three large drug companies, noneof its molecules had entered a human trial as of October 2026. Retrosynthesismodels propose routes, sometimes coupled to automated synthesis platforms so that design, make andmodels propose routes, sometimes coupled to automated synthesis platforms so that design, make andtest run as a closed loop.test run as a closed loop. removed, struck through added, underlinedLine numbers count the serialised markdown of each revision, frontmatter included.
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