U.S. Food and Drug Administration01.13.21
The U.S. Food and Drug Administration released the agency’s first Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan. This action plan describes a multi-pronged approach to advance the Agency’s oversight of AI/ML-based medical software.
“This action plan outlines the FDA’s next steps towards furthering oversight for AI/ML-based SaMD,” said Bakul Patel, director of the Digital Health Center of Excellence in the Center for Devices and Radiological Health (CDRH). “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.”
The AI/ML-Based Software as a Medical Device Action Plan outlines five actions that the FDA intends to take, including:
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 FDA welcomes continued feedback in this area and looks forward to engaging with stakeholders on these efforts. The agency will also continue to collaborate across the FDA to build a coordinated approach in areas of common focus related to AI/ML.
Launched in September of 2020, the CDRH Digital Health Center of Excellence is committed to strategically advancing science and evidence for digital health technologies within the framework of the FDA’s regulatory and oversight role. The goal of the Center is to empower stakeholders to advance health care by fostering responsible and high-quality digital health innovation.
“This action plan outlines the FDA’s next steps towards furthering oversight for AI/ML-based SaMD,” said Bakul Patel, director of the Digital Health Center of Excellence in the Center for Devices and Radiological Health (CDRH). “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.”
The 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 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.
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 FDA welcomes continued feedback in this area and looks forward to engaging with stakeholders on these efforts. The agency will also continue to collaborate across the FDA to build a coordinated approach in areas of common focus related to AI/ML.
Launched in September of 2020, the CDRH Digital Health Center of Excellence is committed to strategically advancing science and evidence for digital health technologies within the framework of the FDA’s regulatory and oversight role. The goal of the Center is to empower stakeholders to advance health care by fostering responsible and high-quality digital health innovation.
