FDA is issuing this draft guidance to further develop a regulatory approach tailored to artificial intelligence/machine learning (AI/ML)-enabled devices to increase patients’ access to safe and effective AI/ML-enabled devices, in order to protect and promote public health.
This draft guidance describes a least burdensome approach to support the iterative improvement of machine learning-enabled device software functions (ML-DSF) while continuing to assure their safety and effectiveness, as described in FDA’s 2019 AI/ML Discussion Paper and 2021 AI/ML Action Plan.
The draft guidance provides recommendations on the information to be included in a Predetermined Change Control Plan (PCCP) that may be provided in a marketing submission for ML-DSF. The PCCP mechanism includes the planned ML-DSF modifications, the associated methodology to implement and validate those modifications, and an assessment of the impact of those modifications.
Since the introduction of the PCCP concept, there has been significant interest in using this mechanism for AI/ML-enabled medical devices. FDA continues to receive an increasing number of marketing submissions and pre-submissions for AI/ML-enabled medical devices, which can have a significant positive impact on healthcare, and the Agency expects this to increase over time.
The guidance builds on FDA’s longstanding commitment to develop and apply innovative approaches to the regulation of medical device software and other digital health technologies to assure their safety and effectiveness. The recommendations in this guidance apply to the device constituent part of a combination product, such as drug-device and biologic-device combination products, when the device constituent part includes an ML-DSF.