Using EU GMP Annex 22 as the Framework for Governing AI Systems, Validation Traceability, and Data Integrity Controls

Artificial Intelligence is transforming how regulated organizations manage quality systems, manufacturing operations, compliance activities, and business processes. AI-enabled technologies now support activities ranging from document generation and data analysis to predictive maintenance, process optimization, quality investigations, and decision support. As adoption accelerates, regulatory expectations regarding governance, validation, traceability, and data integrity continue to evolve.

This webinar examines the practical implications of EU GMP expectations as they relate to AI systems operating within regulated environments. Participants will explore how traditional GMP principles intersect with emerging AI technologies and how organizations can establish governance structures that maintain compliance while supporting innovation.

The session focuses on the unique challenges associated with validating AI-enabled systems. Unlike traditional software applications, AI models may demonstrate adaptive behavior, rely on large training datasets, generate probabilistic outputs, and require ongoing monitoring throughout their operational lifecycle. Participants will learn how validation traceability can be established and maintained despite these complexities and how organizations can create evidence demonstrating continued fitness for intended use.

Special attention will be given to data integrity considerations, including training data governance, source data reliability, auditability, model transparency, output verification, electronic records management, and change control requirements.

The webinar will also address governance structures necessary to support AI implementation, including roles and responsibilities, lifecycle management practices, risk assessment methodologies, performance monitoring programs, retraining controls, and inspection readiness activities.

Code: FDB1608