Validating Artificial Intelligence Frameworks in GxP Environments: A Practitioner's Handbook

Your AI model is already making GxP decisions. Can you prove it should?

Machine learning has walked straight onto the manufacturing floor, and the first GMP enforcement actions naming AI are already on the record. The old comfort question, is the software installed correctly, won't save you now. Inspectors want to see that a model does what you claim, holds its nerve as the data shifts under it, and leaves a trail they can follow line by line. Most quality systems can't show that yet. This book teaches you how.

This is the playbook. It bolts a disciplined AI layer onto the CSV and CSA foundation you already run, puts risk in charge of every decision instead of paperwork, and walks one real system from intended use all the way to inspection-ready evidence. No theory dumps, no hand-waving, a method you can put to work Monday morning.

What you get:

A four-tier risk model that tells you exactly how hard to validate, so you stop gold-plating the trivial and stop gambling on the dangerous IQ, OQ and PQ rebuilt for both static and self-learning AI 28 ready-to-run templates and a complete AI Validation Master Plan Data drift, retraining governance and decision integrity, made practical and defensible A draft Annex 22 crosswalk, a 120-question inspection bank, and a fully worked evidence pack Written for QA and Quality leaders, IT compliance practitioners, regulatory peers, and the executives who sign off on the risk. Grounded in ICH Q9, EU Annex 11, 21 CFR Part 11, FDA Computer Software Assurance, the EU AI Act, and the draft Annex 22.

Sachin Bhandari has spent more than 25 years in pharmaceutical Quality IT and validation, and has carried AI-supported quality systems through health-authority inspection with zero compliance findings.

AI has already reached your GxP floor. This is how you stay in control of it.