Governance · EU GMP Annex 22 and AI
AI is starting to show up in GMP (Good Manufacturing Practice) decisions. The question is not whether AI can give answers, it is whether AI can be controlled, explained, reviewed, and kept in its lane. ChatQP is built with that in mind.
EU GMP Annex 22 is draft guidance following its public consultation; it is not adopted law. ChatQP is built with the draft Annex 22 expectations in mind. It does not claim to be "Annex 22 compliant." ChatQP is not a validated GMP system. It is a private beta tool, built with these expectations in mind.
Why Annex 22 matters
If AI is used in GMP work, the system needs a clear purpose, testing, human review, change control, and control over the data it uses. The European Commission's draft Annex 22 is expected to outline expectations for the use of AI and machine learning in the manufacture of active substances and medicinal products. It covers how the model is chosen and trained, how it is validated, how it is measured, and the quality of the training and test data.
The problem Annex 22 is responding to is not that AI gives answers. It is whether an AI system can be controlled, explained, reviewed, and kept inside a quality system.
What the draft appears to require
Industry commentary also describes expectations around continuous monitoring, change control, model-performance monitoring, and human review.
How ChatQP lines up
| Draft Annex 22 theme | What ChatQP does |
|---|---|
| Intended use | QP (Qualified Person) and QA (Quality Assurance) decision support only. It is not a certification authority. |
| Human oversight | The QP makes the decision. Outputs are there to be reviewed. |
| Validation and performance | Benchmark scenarios and decision tests against constructed cases. |
| Data control | Runs locally and offline. No batch data leaves the machine. |
| Explainability | Outputs cite sources and expose the reasoning path for review. |
| Change control | Versioned corpus, rules, and model setup. |
| Model risk | Hard GMP rules run in code, outside the model. |
Related regulatory grounding
ChatQP's outputs rest on the binding rules and guidance QPs already work to. The FDA also has draft guidance on using AI to support regulatory decision-making for drugs and biological products. It describes a risk-based way to judge whether an AI model is credible enough for the decision it informs. That is not the same context as QP batch certification, but the core idea, credibility proportional to decision risk, fits naturally next to Annex 22.
What ChatQP does not claim
ChatQP is not a validated GMP system out of the box. It is not "Annex 22 compliant," and it does not make regulatory decisions. Using it in a regulated setting would need local validation, SOPs, access control, control of the data, change control, and user training.