The U.S. Food and Drug Administration (FDA), Health Canada, and the United Kingdom's Medicines and Healthcare products Regulatory Agency (MHRA) have jointly identified 10 guiding principles that can inform the development of Good Machine Learning Practice (GMLP). These guiding principles will help promote safe, effective, and high-quality medical devices that use artificial intelligence and machine learning (AI/ML). Artificial intelligence and machine learning technologies have the potential to transform health care by deriving new and important insights from the vast amount of data generated during the delivery of health care every day. They use software algorithms to learn from real-world use and in some situations may use this information to improve the product's performance. But they also present unique considerations due to their complexity and the iterative and data-driven nature of their development.

The U.S. Food and Drug Administration released a list of "guiding principles" this week aimed at helping promote the safe and effective development of medical devices that use artificial intelligence and machine learning. The FDA, along with its U.K. and Canadian counterparts, said the principles are intended to lay the foundation for Good Machine Learning Practice. "As the AI/ML medical device field evolves, so too must GMLP best practice and consensus standards," said the agency regarding the principles. As the FDA notes, AI and ML technologies have the potential to radically expand the healthcare industry – but their complexity also presents unique considerations. The 10 guiding principles identify points at which international standards organizations and other collaborative bodies, including the International Medical Device Regulators Forum, could work to advance GMLP.