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FDA Outlines Plan for AI and Machine Learning-Based Software

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The AI/ML Action Plan is a response to stakeholder feedback received from the April 2019 discussion paper.

FDA has released its holistic approach toward giving guidance for artificial intelligence and machine learning solutions.

The federal agency’s first AI/ML-Based Software as a Medical Device Action Plan outlines five actions that the FDA intends to take, including: 

  • Further developing the proposed regulatory framework, including through the issuance of draft guidance on a predetermined change control plan (for software’s learning over time); 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; and 
  • Advancing real-world performance monitoring pilots. 

“This action plan outlines the FDA’s next steps towards furthering oversight for AI/ML-based SaMD,” Bakul Patel, director of the Digital Health Center of Excellence in the Center for Devices and Radiological Health said in a release. “The plan outlines a holistic approach based on total product lifecycle 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. To stay current and address patient safety and improve access to these promising technologies, we anticipate that this action plan will continue to evolve over time.”

FDA said the AI/ML Action Plan is a response to stakeholder feedback received from the April 2019 discussion paper, Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device.

The agency said it will still receive continued feedback in this area.

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