Validating AI Use in Quality Systems
Practical CSV and CSA Approaches for FDA Inspection Readiness
Why take this course?
AI tools are entering GxP quality systems through document drafting, summarization, analytical support, and other quality-related workflows. The challenge is that AI does not behave like traditional deterministic software. Outputs can be variable and context-dependent, making legacy CSV methods difficult to apply without creating either excessive documentation or insufficient control. That gap becomes visible when organizations cannot explain intended use, risk level, verification expectations, or human accountability.
This program focuses on practical validation and control of AI use through established CSV thinking and modern CSA principles. It addresses how intended use is defined, how AI-assisted activities are bounded, and how use cases are classified by impact on product quality, patient safety, and data integrity. The emphasis is on inspection-ready control: clear responsibilities, risk-based verification, traceable decisions, and documented oversight.
Key Areas Covered
Carolyn Troiano
Carolyn Troiano has more than 30 years of computer system validation experience across FDA-regulated industries and advises companies on CSV and large-scale IT implementations. She developed validation programs when FDA’s early CSV guidance emerged and collaborated with FDA and industry representatives on 21 CFR Part 11, directly supporting this topic’s focus on AI validation, control, and inspection readiness.
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