AI lets chemists design molecules by simply describing them

EPFL's Synthegy framework, published in Matter, combines LLM-based reasoning with traditional retrosynthetic search algorithms, enabling chemists to guide molecule synthesis planning via natural language prompts rather than rigid rule-based filters. The system positions LLMs as evaluators scoring candidate pathways against user-defined chemical strategies. Medicinal and process chemists iterating on complex synthetic routes should prioritize evaluation, as this replaces brittle heuristic filters with flexible semantic reasoning. Prior tools like ASKCOS required explicit programmatic constraints; Synthegy's natural language interface directly lowers that barrier.