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FDA Releases Framework for AI-Based Software as a Medical Device


The proposed framework describes the FDA’s foundations for an approach to premarket review for AI and machine learning-driven software modifications.

artificial intelligence

Last week, the U.S. Food and Drug Administration (FDA) released a proposed regulatory framework to describe the potential approach to premarket review for artificial intelligence (AI) and machine learning-driven software as a medical device.

The discussion paper, “Proposed Framework for Modifications to AI/Machine Learning-Based Software as a Medical Device,” is built around the fact that machine learning techniques are used to design and train software algorithms to learn from and act on data.

The agency is considering a total product lifecycle-based framework for AI and machine learning technologies that would allow for modifications to be made for real-world learning and adaptation, while ensuring the safety and effectiveness of the device is maintained.

AI and machine learning technologies have the potential to adapt and optimize device performance in real-time to continuously improve healthcare for patients.

The proposed framework describes the FDA’s foundations for an approach to premarket review for AI and machine learning-driven software modifications.

The agency introduces a “predetermined change control plan” in premarket submissions that would include the types of anticipated modifications and the associated methods being used to implement those changes in a way that limits risks to patients.

The FDA and manufacturers could evaluate and monitor a software product from its premarket development to its postmarket performance.

Software modifications that might require a premarket submission include a change that introduces a new risk or modifies and existing risk that could result in significant harm, a change to risk controls to prevent significant harm and a change that significantly affects clinical functionality or performance specifications of the device.

The ideas in the paper leverage practices from the FDA’s current premarket programs and rely on the International Medical Device Regulators Forum risk categorization principles, the FDA’s benefit-risk framework, risk management principles described in the software modifications guidance and the organization-based total product lifestyle approach.

“Our vision is that with appropriately tailored regulatory oversight, AI/ (machine learning)-based (software as a medical device) will deliver safe and effective software functionality that improves the quality of care that patients receive,” the FDA wrote.

Individuals can submit comments on the discussion paper by June 3, 2019.

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