AI is already making calls inside GxP systems.
The validation playbooks haven't caught up.
For three years I kept reaching for a reference that did not exist: one practitioner guide that takes AI and ML validation in regulated pharma from the strategy a board needs in 90 seconds down to something a quality lead can act on Monday morning. So I wrote it.
Validating AI in GxP Environments
The Practitioner Handbook · Sachin Bhandari · PDF edition
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For teams
The book and the toolkit, for your whole team
When more than a few people need the method, two products carry it further than single copies.
Company Edition · from $1,250
A company-named digital edition of Validating AI in GxP with unlimited internal use: your organisation's name on the title page, a licence footer on every page, and no per-seat watermarks. The way institutional buyers from ten-user teams upward have rolled the method out.
Request it via the organisation option above →The Practitioner Pack · $7,500
The working pack behind the book, grown well past what ships inside it: 50 editable templates, 13 SOPs with their operator checklists and RACI matrices, and 19 quick reference guides, every one carrying its worked example, plus an interdependency map of the whole set. It also carries a dated regulatory position note, reissued quarterly, so you can see what is still draft and what has moved since the book went to print. Ready to adapt to your QMS on Monday, licensed to your organisation and watermarked in your name. $7,500 for the pack, or $10,000 with 15 hours of working sessions with the author. Delivered with a one-hour orientation call.
Independent practitioner licensing it for yourself? Write to me about pricing.
See the pack and licence it →Both quotes come back the same day, usually with an invoice you can put straight into procurement. The full menu of services is on the services page.
What readers say
24 verified readers rated this book
Every score comes from a reader who bought the book: most from the feedback form on this site, two who replied to the same question by email with an explicit rating. Nothing is filtered out. The average includes the low scores.
A clear bridge between traditional CSV methods and the additional considerations for systems with AI.
An in depth perspective on AI specific to the GxP domain. Such information is not available anywhere.
A practical and inspection ready framework. The lifecycle approach, governance model and templates can be applied immediately.
More than a handbook. It gives you the mindset to actively shape AI validation instead of simply following it.
How this is measured. Readers rate the book on the feedback form at trustbridge-compliance.com/ask. The scores shown are the plain average of every rating received, including the ones that were not flattering, and including readers who sent their rating by email rather than clicking a star. Quotes appear only where the reader gave permission.
Same book, 332 pages, sold in the shops under its fuller title Validating Artificial Intelligence Frameworks in GxP Environments.
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The copy sold above is personalised to you, arrives within minutes, and comes with the free updated edition when EU GMP Annex 22 is finalised. A shop sale reaches me anonymously, so register a printed copy here and you go on that same list.
Read it before you decide
No sign-up, nothing to pay. Read a complete sample chapter (Chapter 3, why AI breaks the traditional CSV playbook), skim the full contents below, or take the whole table of contents as a PDF.
Read the sample chapter → Download the contents PDFIt works through the real problems of validating AI in GxP, end to end
A working handbook that assumes you already know CSV and GxP, and begins where that training stops: what changes once a system can learn, how to classify and govern it, how to build evidence that holds, and how to keep it valid long after go-live. 19 chapters and 15 appendices across 330 pages.
Getting your bearings
- AI in GxP: the concepts that matter for validation
- The regulatory spine: Annex 11, Draft Annex 22, Part 11 and CSA
- Why AI validation breaks traditional CSV
Classify and govern
- Classification and risk tiering
- The AI governance operating model
- The AI Validation Master Plan
Build the evidence
- Data governance for AI
- Performance acceptance criteria
- Test data and the three independences
- IQ, OQ and PQ redefined for AI/ML
Keep it valid over time
- Ongoing monitoring and drift response
- Explainability and confidence
- Change control and retraining
- AI risk management beyond the tier model
Prove it and scale it
- Inspection readiness
- Generative AI in non-critical GxP use
- Large Language Models in regulated environments
- AI in practice: tools you can use today
- Building the AI programme: the first 100 days
- 28 template skeletons (T01–T28)
- 6 SOP skeletons
- 11 quick reference guides
- Inspection question bank
- Common findings and how to avoid them
- Vendor assessment framework
- A worked evidence pack with an Annex 22 crosswalk
- QMS integration
- SaMD and CDMO appendices
- Glossary
Built to be adapted to your own quality system. If you work best from the tools, start here rather than at chapter one.
Wondering where this book sits against GAMP 5, Annex 22 and the FDA guidance? The reading list on validating AI in GxP places them all in order.