Artificial Intelligence & Medical Products: How CBER, CDER, CDRH, and OCP Are Working Together

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.