Raising the Bar in GxP Compliance – Part 29: Integrating AI into QMS under Annex 22
Welcome to the twenty-ninth instalment of Raising the Bar in GxP Compliance, Rephine’s expert-led blog series for QA and regulatory professionals. In this edition, we explore how artificial intelligence (AI) is transforming Quality Management Systems (QMS) in the pharmaceutical industry. With the EMA’s draft Annex 22 recognising AI’s role in regulated processes, companies must ensure its integration aligns with GxP principles. From governance structures and validation protocols to human oversight and ALCOA+ compliance, discover how Rephine helps organisations embed AI into their QMS in a way that strengthens quality, ensures inspection readiness, and safeguards patient trust.
Artificial intelligence is moving into the heart of Quality Management Systems. Annex 22 makes it clear:
pharma companies must integrate AI with governance, validation, and oversight that meet the same high standards as any GxP process. Static quality frameworks are no longer enough—AI-enabled QMS must be transparent, risk-proportionate, and inspection-ready.
With the introduction of Annex 22, the European Medicines Agency (EMA) formally acknowledges the growing role of artificial intelligence (AI) in regulated pharmaceutical processes. This includes not only manufacturing activities, but also quality-related functions, bringing the integration of AI into Quality Management Systems (QMS) to the forefront of GxP compliance discussions.
Why AI in QMS Matters for Pharma Compliance
AI can support quality activities in:
- Deviation detection and classification
- Predictive maintenance and CAPA trend analysis
- Automated quality risk assessments
- Review of batch records, QC data, and digital logbooks
But to benefit from AI while remaining compliant, organisations must implement:
- Defined governance structures and roles for AI in QMS
- Documented intended use and validation of AI tools
- Human oversight and override capabilities
- Alignment with QRM and ALCOA+ principles
Annex 22 Requirements for AI in Quality Management Systems
- AI systems used within QMS must be validated for their intended use
- Training data must be high quality, documented and version controlled
- Outputs from AI must be traceable and auditable
- The human-in-the-loop principle must be preserved in all GxP-relevant decisions
- Change control procedures must apply to AI model updates or re-training
Challenges in Integrating AI into QMS
- Lack of clarity on roles between Quality, IT, and Data Science
- Absence of documented procedures for AI model validation within QMS
- Difficulty ensuring explainability and traceability of AI-generated outputs
- Potential misalignment between AI agility and QMS rigidity
How Rephine Supports Annex 22 AI in QMS Compliance
Rephine supports pharma and biotech companies by:
✅ Defining clear QMS governance structures for AI use
✅ Designing validation protocols and performance metrics
✅ Mapping and mitigating GxP risks associated with AI integration
✅ Supporting regulatory inspection readiness for Annex 22 requirements
📅 EMA’s consultation on Annex 22 is open until 7 October 2025. This article is part of Rephine’s educational content series on the upcoming EU GxP revisions.
Dr. Eduard Cayón
CSO (Chief Scientific Officer)
About the Author:
Dr. Eduard Cayón is the Chief Scientific Officer (CSO) at Rephine, a global leader in GxP compliance and quality assurance.
We don’t just deliver audits or consultancy services — we partner with clients at every stage of their quality journey, offering end-to-end solutions that empower confidence and compliance.
With over 25 years of experience, Rephine has built an enviable reputation as the gold standard in the industry operating from four primary locations: Stevenage in the UK, Barcelona in Spain, India, and Shanghai in China.
Dr. Cayón, who holds a Ph.D. in Organic Chemistry, is a deeply experienced pharmaceutical industry consultant and auditor.
He is dedicated to supporting pharmaceutical, biotech, and medical device companies in meeting the highest standards of manufacturing and supply chain integrity.
