FDA Issues Draft Guidance for AI-Enabled Devices: Key Takeaways

The FDA recently published draft guidance titled Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations. This guidance provides detailed recommendations for the development and marketing of AI-enabled devices, including the information and documentation the FDA requests in marketing submissions. It also offers direction regarding the design, development, deployment, and maintenance of these devices.

Key Takeaways

• Helpful Guideposts: The Draft AI Guidance is intended to provide developers of AI-assisted devices with a better understanding of the information that the agency will find helpful in its review of products and how such information should be presented. While it is unclear in what format the draft guidance will be finalized, it nevertheless provides helpful insight into the agency’s current perspective on what information should be submitted in support of an application, why, and in what context.

• Comprehensive Lifecycle Management Should Be the Norm: The FDA emphasizes a Total Product Lifecycle (TPLC) approach that requires robust risk management, ongoing performance monitoring, and mechanisms to address algorithm updates and data drift. The guidance provides helpful insights into the FDA’s view of AI-enabled devices and strategies to address transparency, bias and other challenges arising in this context.

• Agency Engagement and Documentation: The draft guidance repeatedly encourages early, proactive engagement with the FDA during development of AI-enabled devices, particularly when new and emerging technology is used in the development and design of the device, or when novel methods are used during the validation of a device. Organizations should strategically consider taking advantage of this opportunity to collaborate with the agency.

• Responsible AI Governance: Organizations looking to engage with the FDA relating to AI-powered devices should ensure they have robust AI governance practices in place. While the Draft AI Guidance is most relevant to developers of AI-enabled devices, other health care organizations could benefit from examining the FDA’s recommended approach as many of the recommendations in the Draft AI Guidance have potential application to AI model development, performance validation, and risk mitigation in other contexts as well.

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