Application/System GxP Audit: AI Vs Non AI

What’s Different?

As AI systems increasingly enter regulated pharma environments, auditing them requires more than CSV checklists. Here's how AI system audits differ from traditional GxP application audits—step by step:
·       Context of Use for predictive models
·       Explain ability (e.g. SHAP, LIME, model cards)
·       Risk-based validation for drift, bias & retraining
·       Continuous performance monitoring
·       Change control for model retraining
·       Data lineage from training to inference

Traditional GxP Audits Focus On:
·       Static functional specs & validation (IQ/OQ/PQ)
·       Audit trails, SOP compliance, configuration control
·       Deterministic behavior (no learning/adaptation)

Both require strong Part 11 compliance, access control, and traceability—but AI systems demand an evolving approach to risk and lifecycle governance.

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