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U.S. FDA Releases Artificial Intelligence and Machine Learning Action Plan

In step with the U.S. Food and Drug Administration’s (FDA) commitment to develop and apply innovative approaches to the regulation of medical device software and other digital health technologies, on January 12, 2021, the Agency released their first Artificial Intelligence/Machine Learning (AI/ML) – Based Software as a Medical Device (SaMD) Action Plan.

The AI/ML Action Plan is in 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.”

What Should Medical Device Sponsors Know?
The FDA’s Action Plan describes a multi-pronged approach to advance the Agency’s oversight of AI/ML based-medical software. Specifically, the Plan outlines five actions and goals that the FDA intends to take, including:

  1. Develop an update to the proposed regulatory framework presented in the AI/ML-based SaMD discussion paper, including the issuance of a Draft Guidance on the Predetermined Change Control Plan (for software’s learning over time) and the Algorithm Change Control Protocol (ACP).
  2. Strengthen the FDA’s encouragement of the harmonized development of Good Machine Learning Practice (GMLP) through additional FDA participation in collaborative communities and consensus standards development efforts.
  3. Support a patient-centered approach by continuing to host discussions on the role of transparency to users of AI/ML-based devices. This includes conducting a public workshop on medical device labeling to support transparency to users of AI/ML-based devices; this action builds upon the October 2020 Patient Engagement Advisory Committee (PEAC) Meeting focused on patient trust in AI/ML technologies.
  4. Support regulatory science efforts on methodology development for the evaluation and improvement of machine learning algorithms, including the identification and elimination of bias, and on the robustness and resilience of these algorithms to withstand changing clinical inputs and conditions.
  5. Advance real-world performance pilots in coordination with stakeholders and other FDA programs, to provide additional clarity on what a real-world evidence generation program could look like for AI/ML-based SaMD.

Next Steps
The FDA welcomes continued feedback through public docket FDA-2019-N-1185 at  www.regulations.gov, and looks forward to engaging with stakeholders on these efforts.

How can NAMSA Help?
Does your software product meet FDA’s definition of a medical device? If so, does the software contain AI/ML algorithms? Are the algorithms adaptive or fixed? At NAMSA, our team of regulatory experts have AI/ML experience with a variety of software devices and can guide you through the challenges of this unknown regulatory environment to get your product to market in a timely manner.

NAMSA is the industry leader in driving successful regulatory outcomes through effective interactions with the FDA. In fact, our internal teams of medical device development experts communicate with the FDA nearly every day. From Pre-Submission meetings – to Pre-IDE preparation – and FDA inspection preparation and SAMD/AI/ML reviews, our teams are the most experienced in industry at accelerating regulatory submissions and approvals for device manufacturers. This expertise is proven to save medical device organizations up to $17M in costs and 23 months in development timelines.

If you are interested in speaking with us about FDA-related activities or other global regulatory strategies, please contact us at: https://www.namsa.com/contact-us.

Monica R. Montanez

Monica R. Montanez, MS, RAC, CQA currently serves as NAMSA's Principal Strategy Consultant. Monica has over twenty years’ experience in the medical device industry in Regulatory Affairs and Quality Assurance. Her primary focus is navigating the regulatory pathways for electro-mechanical and software driven medical devices worldwide. She has received clearance of many 510(k)s and approval of new indications for PMA device(s) of which 90% involved software. She has broad regulatory expertise in several areas of digital health, including: Software in a Medical Device (SiMD), Software as a Medical Device (SaMD), mobile medical apps, clinical decision support software, telehealth, artificial intelligence, machine learning, interoperability, cybersecurity and human factors engineering, including wireless medical devices -radio frequency (RF), electromagnetic compatibility (EMC) and electromagnetic interference (EMI). While in industry, she assisted in the development of FDA 510(k) guidance and FDA Software guidance directly with FDA. Monica holds a Masters of Science (MS) degree in Regulatory Science (RS) from the University of Southern California (USC) School of Pharmacy. Currently. she holds Regulatory Affairs Certification (RAC) from the Regulatory Affairs Professionals Society (RAPS) and Certified Quality Auditor (CQA) from the American Society for Quality (ASQ).