These principles are intended to lay the foundation for
developing good machine learning practices (GMLP) and will help
guide future growth in this rapidly progressing field.
Through international regulatory collaboration we have identified
and co-published 10 guiding principles that should be addressed
when medical devices use artificial intelligence or machine
learning software. These principles are intended to lay the
foundation for developing good machine learning practices (GMLP)
and will help guide future growth in this rapidly progressing
field.
They cover key elements of GMLP, for example: having an in-depth
understanding of a model’s intended integration into clinical
workflow, and the desired benefits and associated patient risks
as well as selecting and maintaining training and datasets to be
appropriately independent of each other. We envision these
guiding principles may be used to:
- adopt good practices that have been proven in other sectors
- tailor practices from other sectors so they are applicable to
medical technology and the health care sector
- create new practices specific for medical technology and the
health care sector
These guiding principles further identify areas where the
International Medical Device Regulators Forum (IMDRF),
international standards organizations and other collaborative
bodies could work together to advance GMLP. Areas of
collaboration include research; creating educational tools and
resources; regulatory policies and regulatory guidelines;
international harmonization; and consensus standards.
We know that strong international partnerships will be essential
part of empowering the wider sector to advance responsible
innovations. We look forward to our continued collaborative work
and engagement with the FDA and Health Canada and wider
international health partners in this area.
Read the 10 guiding principles in
full.
