FDA Paper on AI Targets 4 Focus Areas
FDA has released a cross-Center paper entitled “Artificial Intelligence (AI) & Medical Products: How CBER, CDER, CDRH, and OCP are Working Together.” The paper, which applies to drugs, devices, biologics, and combination products, says “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.”
The document describes the following four areas of focus regarding the development and use of AI across the medical product life cycle:
Foster Collaboration to Safeguard Public Health
FDA says it plans to solicit input from a range of interested parties to consider “critical aspects of AI use in medical products, such as transparency, explainability, governance, bias, cybersecurity, and quality assurance.” It says it will support educational initiatives to support the safe and responsible use of AI in medical product development and medical products. It will also work closely with global collaborators to promote international cooperation on standards, guidelines, and best practices.
Advance the Development of Regulatory Approaches That Support Innovation
The paper says FDA’s Centers intend to develop policies that provide regulatory predictability and clarity for the use of AI. They will continue to monitor and evaluate trends and emerging issues to detect potential knowledge gaps and opportunities. They intend to support “regulatory science efforts to develop methodology for evaluating AI algorithms, identifying and mitigating bias, and ensuring the robustness and resilience of AI algorithms to withstand changing clinical inputs and conditions,” according to the paper. Additionally, it says guidance will be issued on the use of AI in medical product development and resulting products, including predetermined change control plans for AI-enabled device software functions, life cycle management considerations and premarket submission recommendations for AI-enabled device software functions, and considerations for the use of AI to support regulatory decision-making for drugs and biological products.
Promote the Development of Standards, Guidelines, Best Practices, and Tools for the Medical Product Life Cycle
The paper says the agency is committed to upholding safety and effectiveness standards (Good Machine Learning Practice Guiding Principles) across AI-enabled medical products. It plans to refine and develop considerations for evaluating the safe, responsible, and ethical use of AI in the medical product life cycle. It will also identify best practices for long-term safety and real-world performance monitoring of such products. And it will explore best practices for documenting and ensuring that data used to train and test AI models are fit for use.
Support Research Related to the Evaluation and Monitoring of AI Performance
The paper says the agency plans to support demonstration projects to identify different points where bias can be introduced in the AI development life cycle and how it can be addressed (risk management). It will also “support the monitoring of AI tools in medical product development within demonstration projects to ensure adherence to standards and maintain performance and reliability throughout their life cycle,” the paper says.