AI in Drug Discovery: What a Model Can Move and What It Cannot

This page is about method, not about any particular medicine, and nothing here is medical advice. It is written to answer one question: when a company says a drug was discovered with AI, which part of a decade-long process is that sentence about? The pipeline, and where the years go Roughly, and with enormous variation: pick a target, find molecules that do something to it, optimise those molecules into something drug-like, test in animals and in safety assays, then run the clinical stages — first for safety in a small number of people, then for efficacy in patients, then in a large confirmatory trial — and then apply to a regulator. Start to finish is usually over a decade. Two facts about that pipeline determine everything else on this page. The first is that the calendar and the money are dominated by the clinical stages, not the discovery ones. The second is that failure is the normal outcome, and it is concentrated where the drug first meets human biology: a candidate can be a beautiful molecule, hit its target exactly as designed, and still not help anyone, because the target was the wrong thing to hit. Where models are genuinely used Application Description Virtual screening Score enormous make-on-demand chemical libraries against a target site far faster than physics-based docking can. The output is a shortlist to synthesise and assay, and it replaces a search, not an experiment. Generative chemistry Propose molecules conditioned on a target, a scaffold or a set of property constraints, rather than picking from a catalogue. Whether the molecule can be made at all is a separate model. Property prediction Solubility, permeability, metabolic stability, cardiac ion channel liability. These filter a list early and cheaply. They are trained on assay data and inherit its coverage: they are most reliable on chemistry that resembles what has been tested. Retrosynthesis Plan a route from purchasable starting materials. This is the application closest to a solved probl