The U.S. Food and Drug Administration (FDA), Health Canada, and the U.K.'s Medicines and Healthcare products Regulatory Agency (MHRA) have jointly issued a list of guiding principles for developers of medical devices based on artificial intelligence (AI) and machine learning.
The 10 principles include the following:
- Multidisciplinary expertise is leveraged throughout the total product life cycle
- Good software engineering and security practices are implemented
- Clinical study participants and datasets are representative of the intended patient population
- Training datasets are independent of test sets
- Selected reference datasets are based upon best available methods
- Model design is tailored to the available data and reflects the intended use of the device
- Focus is placed on the performance of the human-AI team
- Testing demonstrates device performance during clinically relevant conditions
- Users are provided clear, essential information
- Deployed models are monitored for performance and retraining risks are managed
"These 10 guiding principles are intended to lay the foundation for developing Good Machine Learning Practice that addresses the unique nature of these products," the FDA wrote. "They will also help cultivate future growth in this rapidly progressing field.
The FDA envisions that 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 healthcare sector; and create new practices specific for medical technology and the healthcare sector.
