FDA’s Artificial Intelligence/Machine Learning Software

FDA's Artificial Intelligence/Machine Learning Software

On January 12, the U.S. Food and Drug Administration released the first FDA’s 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.”

AI and ML Technologies

Artificial intelligence (AI)- and machine learning (ML)-based technologies have the potential to transform healthcare by deriving new and important insights from the vast amount of data generated during the delivery of healthcare every day. Example high-value applications include earlier disease detection, more accurate diagnosis, identification of new observations or patterns on human physiology, and development of personalized diagnostics and therapeutics.

One of the greatest benefits of AI/ML in software resides in its ability to learn from real-world use and experience, and its capability to improve its performance. The ability for AI/ML software to learn from real-world feedback (training) and improve its performance (adaptation) makes these technologies uniquely situated among software as a medical device (SaMD) and a rapidly expanding area of research and development.

Our vision is that with appropriately tailored regulatory oversight, AI/ML-based SaMD will deliver safe and effective software functionality that improves the quality of care that patients receive.

To date, FDA has cleared or approved several AI/ML-based SaMD. Typically, these have only included algorithms that are “locked” prior to marketing, where algorithm changes likely require FDA premarket review for changes beyond the original market authorization.

However, not all AI/ML-based SaMD are locked; some algorithms can adapt over time. The power of these AI/ML-based SaMD lies within the ability to continuously learn, where the adaptation or change to the algorithm is realized after the SaMD is distributed for use and has “learned” from real-world experience. Following distribution, these types of continuously learning and adaptive AI/ML algorithms may provide a different output in comparison to the output initially cleared for a given set of inputs.

FDA’s Artificial Intelligence Action Plan

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.

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.

“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,” – the FDA said.

Anastasia Kovalenko

Anastasia has an experience of creating articles for about 5 years. Topics of those articles included health, overall wellness, pharmacies and new pharmaceutical products. Wishes to learn more and improve her experience in medical field. Considers archaeology to be the most interesting and exciting hobby among others.

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