The Medical Imaging & Technology Alliance (MITA)—a trade association representing manufacturers of medical imaging equipment, radiopharmaceuticals, contrast media, and focused ultrasound therapeutic devices—submitted comments to the U.S. FDA’s Digital Health Center of Excellence (DHCoE) concerning the Good Machine Learning Practice for Medical Device Development: Guiding Principles.

Jointly published by the FDA, Health Canada, and the United Kingdom’s Medicines and Healthcare products Regulatory Agency, these principles aim to promote safe, effective, and high-quality medical devices that use artificial intelligence (AI) and machine learning.

“MITA and its members applaud the work of the FDA and its counterparts in Canada and the UK for their collective work in this area, which hastens patient access to innovative technologies and improved care,” says Patrick Hope, MITA executive director. “We look forward to working with the FDA on how to best operationalize these guidelines.”

In its submitted comments, MITA asked FDA to engage industry stakeholders and work collectively to:

  • Clarify what are the relevant characteristics that ensure Clinical Study Participants are representative of the target patient population (principle No. 3).
  • Clarify the “known risks” referenced in principle No. 6 to ensure that developers and regulators have a common understanding of the risks related to model design and development.
  • Explore what information is the most appropriate for user labelling and what information is most appropriate for regulatory submissions (principle No. 9).
  • Clarify that assessing whether a device is fit for use by its intended population is part of the regulatory review process.

To read MITA’s full comment letter, click here.