FDA and International Counterparts Release Best Practices for Machine Learning in Medical Device Development

This week the U.S. Food and Drug Administration (FDA), along with Health Canada and the United Kingdom’s Medicines and Healthcare Products Regulatory Agency (MHRA), identified 10 guiding principles to inform the development of Good Machine Learning Practice (GMLP) and promote safe and effective medical devices that use artificial intelligence and machine learning (AI/ML).  The guiding principles “identify areas where the International Medical Device Regulators Forum (IMDRF), international standards organizations, and other collaborative bodies could work to advance GMLP,” including creation of educational tools and resources, international harmonization, and consensus standards.

Good Machine Learning

The guiding principles reflect some of the focus topics articulated in FDA’s Transparency of AI/ML-Enabled Medical Devices Virtual Workshop.  For example, the guiding principles recommend that “users are provided clear, essential information,” emphasizing the importance of providing clear, contextually relevant information about the device to the intended audience.  The principles also include requirements that “testing demonstrates device performance during clinically relevant conditions,” and “deployed models are monitored for performance and re-training risks are managed.”

FDA welcomes feedback through the public docket at Regulations.gov (FDA-2019-N-1185) and may be contacted directly at Digitalhealth@fda.hhs.gov.  Health Canada and the UK’s MHRA may be contacted directly at mddpolicy-politiquesdim@hc-sc.gc.ca and software@mhra.gov.uk respectively.

For questions on any of the topics discussed at this meeting, please contact the authors or a member of MoFo’s FDA Regulatory + Compliance practice.