Practical AI in Regulated Labs
Practical AI in Regulated Labs is a knowledge article that explains how to apply AI/ML in QC and R&D labs in a compliant, inspection-ready way. It highlights real use cases (e.g., deviation triage, trend detection, OOS/OOT risk signals, document automation, instrument data review), along with key requirements like validation approach, audit trails, data integrity (ALCOA+), model governance, and change control - so teams can adopt AI safely without disrupting GxP compliance.
