AI Drug Discovery Lab

Overview

AI Drug Discovery Lab is a SOC 2, GxP, and ISO 27001-aligned healthcare AI template that gives discovery researchers a transparent triage workbench — compound library with rule-based Lipinski Rule of Five and Veber druglikeness, property-window target screening, grounded literature synthesis with citations, and AI-drafted compound rationales. The druglikeness verdict, target screen filter, and literature retrieval are deterministic and reproducible; AWS Bedrock and Pinecone (with RDKit chemistry under the hood) draft only the prose rationale, never an affinity number. Real molecular docking, ML affinity prediction, and IND workflows are honestly disclosed as production integrations rather than simulated. The template ships a three-role RBAC console (researcher, lead, admin) with candidate shortlist, target profiles, druglikeness analytics, and an immutable audit log. Customize inside VertiComply, generate the full React + FastAPI + Postgres stack with GxP-aware scaffolding, then export to GitHub. No platform lock-in.