LIVE WEBINAR

Using EU GMP Annex 22 as the Framework for

Governing AI Systems, Validation Traceability, and Data Integrity Controls

ABOUT THE COURSE

Organizations deploying AI in GMP operations must determine how model behavior, training data, system changes, and human decisions remain controlled over time. This session structures governance, validation traceability, data integrity, performance monitoring, retraining controls, supplier oversight, and lifecycle evidence for AI-enabled systems.

The discussion progresses from AI system classification and intended use through training data, traceability, output verification, and electronic records. It then addresses model monitoring, drift, retraining, change management, third-party oversight, human accountability, and the documentation needed to support inspection readiness.

Designed for professionals responsible for evaluating, implementing, validating, reviewing, or governing AI-enabled activities within regulated operations.

KEY AREAS COVERED

AI system classification and risk-based oversight
Validation traceability across the AI lifecycle
Training data governance and source reliability
Output verification and human accountability
Audit trails and electronic record controls
Model monitoring, drift, and performance degradation
Retraining controls and change management
Supplier qualification and inspection documentation

Course Director

Charles H. Paul

Charles H. Paul brings more than 30 years of experience across GMP compliance, validation programs, computerized systems oversight, technical documentation, risk management, and regulatory remediation. His work connecting emerging technologies with established quality system practices provides relevant operational perspective on Annex 22 governance, AI validation traceability, data integrity, lifecycle control, and inspection readiness.

FDB1608

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