AI/ML Systems Validation in Regulated Environments
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In This E-Book You Will Learn
How FDA CSA, NIST AI RMF, IMDRF GMLP, and the EU AI Act apply to regulated AI/ML systems
How to classify AI use cases from GxP decision support to automated control to medical device functionality
How to define performance requirements, data governance, and model versioning for regulatory defensibility
How to maintain human oversight and build monitoring plans that satisfy inspectors
Trusted By Industry Leaders
AI Validation Guide
Make AI Defensible Under GxP
AI and ML are entering regulated environments faster than most validation frameworks can keep up. This chapter provides a practical validation model for AI/ML tools used in GxP contexts; covering intended use classification, performance boundaries, training data governance, model versioning, change control triggers, and the human oversight requirements that regulators will scrutinise most.
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