AI in GxP: Validation and Compliance December 2026

Artificial Intelligence (AI) is increasingly being adopted across regulated pharmaceutical, biotechnology, and medical device environments. However, traditional Computer Systems Validation (CSV) approaches were not designed for data-driven, probabilistic, and evolving AI systems. Regulators now expect organizations to apply risk-based, lifecycle-oriented assurance that demonstrates AI systems are fit for their intended GxP use.

This course provides a practical, regulatory-aligned framework for validating and governing AI applications in GxP environments, consistent with FDA and EMA expectations. This AI in GxP course incorporates regulatory expectations for risk-based computer system validation and compliance for AI applications used in GxP environment. It aligns with industry-wide standards, such as those defined by GAMP and PIC/S.

Participants will learn how to apply CSV / CSA principles to AI systems, define appropriate Context of Use, assess AI-specific risks, establish credibility and validation evidence, and maintain compliance throughout the AI lifecycle.

Our Approach to AI in GxP Training

Our experienced computer system validation consultants have designed a concise, yet thorough course to equip you with the information you need to validate AI based applications. A mixture of instructor lectures, class activities, and real-world examples will keep you engaged. And there will be plenty of opportunities to get answers to your company-specific questions.

What You Get

By the end of this course, participants will be able to:

• Understand how FDA and EMA view AI systems in regulated GxP use cases
• Differentiate AI validation from traditional deterministic software validation
• Define AI Context of Use (COU) and link it to regulatory decision-making
• Perform AI-specific risk assessments, including data, model, and transparency risks
• Apply FDA’s AI credibility assessment lifecycle to real GxP scenarios
• Design risk-based validation strategies aligned with CSV / CSA principles
• Establish governance, documentation, and lifecycle controls for AI systems
• Prepare AI systems for regulatory inspection and audit readiness

Key Topics Covered

• Regulatory landscape for AI in GxP (FDA, EMA)
• AI system types and glossary: deterministic vs non-deterministic, static vs adaptive, ML and GenAI
• Mapping AI systems to GxP impact and risk categories
• FDA AI Credibility Framework: Steps 1–7 applied to CSV
• Data integrity, dataset adequacy, bias, and representativeness
• Model transparency, explainability, and human oversight
• Validation evidence for AI: performance, robustness, and reliability
• Change control, monitoring, and lifecycle management for AI
• Inspection-ready documentation and compliance strategies

Who Should Attend?

This course is designed for:

• IT Personnel and Managers
• CSV Personnel and Managers
• Quality Personnel and Managers
• Auditors
• AI Users
• AI Developers
• Data Analysts and Science Leaders
• Vendors and solution providers of GxP AI systems

Materials Provided:
Course binder, example AI validation package, Training Certificate

This class consists of 3 five-hour sessions, 11:00 AM CDT to 4:00 PM CDT. (Including breaks)