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On January 12, 2021, the U.S. Food and Drug Administration (FDA) released the Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan (Action Plan). The Action Plan expresses that the “FDA’s vision is that, with appropriately tailored total product lifecycle-based regulatory oversight, AI/ML-based Software as a Medical Device (SaMD) will deliver safe and effective software functionality that improves the quality of care that patients receive.”
The FDA currently regulates and has approved “locked” SaMD utilizing AI/ML, but has struggled to determine the appropriate regulatory approach for “adapting” AI/ML SaMD that learns and evolves using real world inputs over time. The Action Plan is the FDA’s step forward to address this challenge.
FDA publishes Action Plan to regulate AI and ML based products
The FDA has advanced an Action Plan focussed on possible means and methods of regulating AI/ML based products
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The Action Plan furthers and builds on concepts covered in a discussion paper released in April 2019
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On 12 January 2021, the US Food and Drug Administration (FDA) published a five part action plan which provides short-term actions to regulate products that incorporate artificial intelligence and/or machine learning (AI/ML). This Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device Action Plan was released by the Digital Health Centre of Excellence (DCE). The DCE launched on 22 September 2020 and exists within the FDA s Centre for Devices and Radiological Health. The DCE s aim is to further the FDA s overarching dedication to the advancement of digital health technology.
Disclosure statement
Tiberio Caetano is Chief Scientist of Gradient Institute. Gradient Institute is an independent non-profit and registered charity that researches, designs and develops ethical AI systems, and provides training in how to build accountability and transparency into machine learning systems. Gradient Institute receives funding from IAG and support from University of Sydney and ANU. The work referred to in this article was partly funded by a grant from the Consumer Policy Research Centre administered through the Australian Human Rights Commission.
Bill Simpson-Young is Chief Executive of Gradient Institute. Gradient Institute is an independent non-profit and registered charity that researches, designs and develops ethical AI systems, and provides training in how to build accountability and transparency into machine learning systems. Gradient Institute receives funding from IAG and support from University of Sydney and ANU. The work referred to in this article was par
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