IMDRF publishes two final documents

The International Medical Device Regulators Forum (IMDRF) on has finalised two technical documents detailing guiding principles for good machine learning practices (GMLP) and risk characterization for medical device software.

The final IMDRF GMLP document lists ten guiding principles for good machine learning practices. The principles include understanding the product’s intended use; implementing good software, design, and security practices; using population-representative datasets during clinical evaluation; and training the datasets independently of test sets. An overarching theme in the principles is to take a total product lifecycle (TPLC) approach to the products so that they not only meet premarket regulatory needs but are monitored after they’re allowed on the are allowed on the market.

“These practices help support the rights, safety, and welfare of patients, including through the ethical use of patient data,” explains the final document.

The IMDRF final document on risk characterization for medical device software contains numerous revisions to the draft version released in January 2024. One of the changes is a reminder that software may change throughout a product’s service life, and that risk characterization should be revisited accordingly as software is updated. The document also notes that the considerations listed within “are not intended to be used by stakeholders as a checklist or prescriptive means of medical device software characterization or determining software-specific device risks.”

Additionally, IMDRF stresses that the document is not intended to replace its 2014 document, “Software as a Medical Device: Possible Framework for Risk Categorization and Corresponding Considerations”, but rather to serve as a supplement to the framework presented in that document.