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Generative chemistry platform behind the first AI-discovered drug to reach phase 2, plus oncology candidates.
Chemistry42 and the wider Pharma.AI suite from Insilico Medicine are generative models for target discovery, molecule generation and trial outcome prediction, used to propose new drug targets and design small molecules against them. The platform's clinical validation comes from rentosertib, a TNIK inhibitor for idiopathic pulmonary fibrosis (IPF) that reported phase 2a results in 2025 and is described as the first AI-discovered drug to reach phase 2. Oncology programmes include ISM3091, a USP1 inhibitor licensed to Exelixis, and ISM5411. The oncology assets are early, so whether the platform's speed translates into approved cancer drugs remains open, as does how much of each programme is attributable to the AI rather than conventional chemistry. For a newcomer: Insilico's software proposes both the target and the molecule, and one of its drugs has reached mid-stage trials.
Generative models for target discovery, molecule generation and trial outcome prediction.
Query for this technology: (TITLE:"Chemistry42 and Pharma.AI" OR ABSTRACT:"Chemistry42 and Pharma.AI" OR TITLE:"Insilico" OR ABSTRACT:"Insilico") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Chemistry42 and Pharma.AI (Insilico), not a curated reading list.
Shares Insilico Medicine, Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow and the tag ai.
Shares AI-driven drug & target discovery and the tag ai.
Shares AI-driven drug & target discovery and the tag ai.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares AI-driven drug & target discovery and the tag ai.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.
Shares Drug discovery roadmap: screening in mice → maps of dependency → designing in silico, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI-driven drug & target discovery.