GMLP readiness in Life Sciences

A GxP AI governance framework based on Good Machine Learning Practice (GMLP) is designed to capture compliance evidence throughout development rather than reconstructing it after a prototype is completed. Each AI use case follows four governed stages—ideation, project, model version, and bundle—with recorded sign-offs required before progressing, while risk tier and residual risk are tracked from the outset. Independent validators must approve every model version, providing separation between development and validation, and the same adaptable process covers both conventional machine-learning models and autonomous agents. After deployment, centralized records of sign-offs, changes, and versions support inspection readiness, while daily production metrics and defined thresholds enable continuous monitoring, drift detection, and revalidation.

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