Artificial intelligence (AI) has the potential to revolutionize health care by advancing medical product development, improving patient care, and augmenting the capabilities of health care practitioners. Aligned with its mission of protecting, promoting, and advancing public health, and building on the Agency’s longstanding commitment to support innovative work in the development and regulation of medical products, the Food and Drug Administration’s (FDA’s) Center for Biologics Evaluation and Research (CBER), Center for Drug Evaluation and Research (CDER), Center for Devices and Radiological Health (CDRH), and Office of Combination Products (OCP) are jointly publishing this paper to provide greater transparency regarding how FDA’s medical product Centers are collaborating to safeguard public health while fostering responsible and ethical innovation.
The complex and dynamic processes involved in the development, deployment, use, and maintenance of AI technologies benefit from careful management throughout the medical product life cycle. Specifically, end-to-end management of AI applications is an iterative process that starts from ideation and design and progresses through data acquisition; preparation; model development and evaluation; deployment; monitoring; and maintenance.
This approach can help address ongoing model performance, risk management, and regulatory compliance of AI systems in real-world applications.
Importantly, AI management requires a risk-based regulatory framework built on robust principles, standards, best practices, and state-of-the-art regulatory science tools that can be applied across AI applications and be tailored to the relevant
medical product.
This paper describes four areas of focus for CBER, CDER, CDRH, and OCP regarding the development and use of AI across the medical product life cycle