On October 24, the FDA, Health Canada, and the U.K.’s Medicines and Healthcare Products Regulatory Agency (MHRA) jointly published “Predetermined Change Control Plans for Machine Learning-Enabled Medical Devices: Guiding Principles.” Troy Tazbaz, Director of the Digital Health Center of Excellence, FDA CDRH, noted that “These guiding principles are intended to lay the foundation for PCCPs for machine learning-enabled medical devices and encourage international harmonization.”
The goal of the collaboration is to optimize the benefits of PCCPs by supporting predictability and harmonizing regulatory considerations across jurisdictions. “Collaboration also encourages stakeholder consensus on the core concepts of PCCPs. Ultimately, this consensus helps put safe and effective advancements in the hands of healthcare providers and users faster, increasing the pace of medical device innovation in the United States and enabling more personalized medicine,” said Tazbaz.
According to the guiding principles document, the foundational characteristics of PCCPs relate to being focused, risk-based and evidence-based, as well as having a high degree of transparency and considering total product lifecycle management. These key characteristics help to support safe and effective implementation of PCCPs for machine learning-enabled medical devices.
The document complements the FDA’s recent efforts related to the amendment of the Federal Food, Drug, and Cosmetic Act by the Food and Drug Omnibus Reform Act (FDORA) of 2022, providing the FDA with express authority to authorize PCCPs, including the FDA’s draft guidance on PCCPs in AI/ML issued in April. “While these Guiding Principles consider specifically the best practices for PCCPs for AI/ML-enabled medical devices, these principles may be helpful to consider for the application of PCCPs more broadly,” said Tazbaz.