Raising the Bar in GxP Compliance – Part 35: AI in CAPA and Deviation Management
Welcome to the thirty-fifth instalment of Raising the Bar in GxP Compliance, Rephine’s expert-led blog series for QA and regulatory professionals. In this edition, we examine how Artificial Intelligence (AI) is being applied to Corrective and Preventive Actions (CAPA) and deviation management in pharma. While AI offers efficiency gains through data analysis, risk prioritisation, and decision support, regulators stress that human oversight and traceability remain essential. Discover how Rephine helps organisations adopt AI responsibly in CAPA systems — embedding Annex 22, Annex 11, QRM, and ALCOA+ principles into robust governance frameworks.
AI can accelerate CAPA and deviation management, but compliance demands balance.
Annex 22 and Annex 11 make it clear: efficiency must go hand in hand with validation, traceability, and human accountability.
AI-Supported Decision Making in CAPA and Deviation Management
The rise of Artificial Intelligence (AI) in GxP environments is transforming how pharmaceutical companies handle Corrective and Preventive Actions (CAPA) and deviation management. While automation and decision support bring clear efficiency gains, regulators stress that human oversight, accountability, and traceability remain non-negotiable.
Why AI in CAPA and Deviation Management Matters
CAPA and deviation systems are at the heart of quality management. Poorly managed investigations or inconsistent decision-making can directly compromise product quality, patient safety, and regulatory trust. AI can help:
- Analyse large datasets from deviations and CAPAs to detect hidden patterns
- Prioritise investigations based on risk severity
- Recommend corrective actions aligned with historical effectiveness
- Support faster closure rates while maintaining compliance
However, without robust governance, AI introduces risks: opaque decisions, lack of explainability, and over-reliance on algorithms.
Annex 22, Annex 11 and QRM Expectations for AI in CAPA
- Annex 22 draft (EMA, 2025): Requires transparency, model validation, and continuous performance monitoring of AI tools.
- Annex 11 (Computerised Systems): Extends lifecycle validation, access control, and audit trail requirements to AI-enabled systems.
- Quality Risk Management (QRM): Must be applied to AI use cases, ensuring risks are identified, mitigated, and monitored.
- ALCOA+: Data integrity principles apply equally to human and AI-assisted decisions.
Challenges of Using AI in Deviation and CAPA Management
- Defining clear human-in-the-loop mechanisms for approvals and escalations
- Ensuring traceability of AI recommendations and final decisions
- Aligning SOPs and training to integrate AI in deviation workflows
- Validating algorithms with representative training data and maintaining them over time
How to Balance AI Efficiency with Compliance Oversight
AI should be positioned as a decision support tool, not a decision maker. The ultimate responsibility must always lie with trained, accountable quality professionals. A risk-based hybrid approach ensures efficiency without compromising compliance.
How Rephine Supports AI in CAPA and Deviation Management
Rephine assists organisations in:
✅ Mapping AI opportunities in deviation and CAPA management
✅ Designing validation and governance strategies for AI tools
✅ Embedding QRM and ALCOA+ principles into AI-enabled processes
✅ Training teams on responsible AI use in quality systems
📅 EMA’s public consultation on Annex 22 runs until 7 October 2025. Now is the time to prepare your organisation for the AI-driven future of quality.
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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.
