The FDA has released its first Artificial Intelligence/Machine Learning-Based Software as a Medical Device (SaMD) Action Plan to monitor the safety and effectiveness of AI and ML-based medical software modifications.

“The plan outlines a holistic approach based on total product life cycle oversight to further the enormous potential that these technologies have to improve patient care while delivering safe and effective software functionality that improves the quality of care that patients receive,” said Bakul Patel, director of the Digital Health Center of Excellence in the Center for Devices and Radiological Health (CDRH), in a statement.

The plan is based on stakeholder feedback to a discussion paper released in April 2019, Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device. The paper described the foundations of a potential approach by the FDA when conducting premarket reviews of modifications made in AI and ML software.

The multi-pronged approach in the plan stems from a desire to specifically assess AI and ML solutions and open up access to them for patients. It includes five actions that the FDA will perform:

• Further developing the proposed regulatory framework, including through issuance of draft guidance on a predetermined change control plan (for software’s learning over time)
• Supporting the development of good machine learning practices to evaluate and improve machine learning algorithms
• Fostering a patient-centered approach, including device transparency to users
• Developing methods to evaluate and improve machine learning algorithms
• Advancing real-world performance monitoring pilots

The predetermined change control plan will explain what types of modifications a manufacturer intends to make in their software and how the algorithms would learn and change while still being safe and effective. It would be included in premarket submissions, with the FDA expecting manufacturers to be transparent so the agency could evaluate and monitor a software solution from its premarket development through postmarket performance.

“We acknowledge that AI/ML-based SaMD is a rapidly progressing field, and we anticipate that this Action Plan will continue to evolve as we pursue these activities and seek to provide additional clarity in this space,” said the agency.

Healthcare industry analyst Shane Walker, senior director of Vamstar and founder of Village Intelligence Corp., says that trust in AI is growing and that the FDA's plan offers standardization that will push efficiency and research development. He does, however, see challenges in working with stakeholders piloting the real-world performance (RWP) process for AI/ML-based SaMD.

"Details on how to go about doing this remain unclear," he told HCB News. "This includes understanding what type of reference data is appropriate in the field, how much oversight from stakeholders is needed, and incorporating feedback from users in the training and evaluation of the algorithms. For now, the FDA is working with stakeholders on a voluntary basis."

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