Mining the first fruits of AI drug discovery from patents

After several years of “talking the talk” AI-centric drug discovery companies (AIDDCS) are now “walking the walk” by not only progressing lead molecules to clinical trials but also disclosing novel chemical series for drug targets in published patents. This presentation outlines mining these documents using open sources to provide a valuable snapshot of what data AIDDCs are actually generating. Example filings include WO2022106857 from Exscientia (targeting MALT1), WO2020039209, BenevolentAI (TRK), WO2021155253, Atomwise (ANAT) and WO2021219089, Insilico Medicine (Cov2 M-protease). This presentation will show how open extraction resources were used to map selected AI generated compounds into PubChem to explore the novelty of their chemical and target neighbourhoods