Description: AI/ML devices pose unique QMS challenges—from data versioning to algorithm retraining and drift detection. This session focuses on how to update your QMS to manage adaptive algorithms in line with FDA’s Predetermined Change Control Plan (PCCP), 21 CFR 820.30, and ISO 13485. We will also map these processes to IMDRF’s SaMD Risk Categorization and postmarket learning principles.
Attendees will learn how to adapt core QMS elements—design control, risk management, and validation—to support dynamic learning models. Special emphasis will be placed on change documentation, model monitoring, and internal audit readiness.
Learning Objectives:
Upon completion, participant will be able to integrate adaptive AI/ML into ISO 13485-compliant QMS structures.
Upon completion, participant will be able to operationalize PCCP and IMDRF guidance within the design control system.
Upon completion, participant will be able to develop monitoring and documentation workflows for model change
