AI in GxP: Validation and Compliance
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 3:30 PM CDT. Each session will include a 30 minute break.