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Earlier this week, the U.S. Food & Drug Administration (“FDA” or the “Agency”) released its long-anticipated final guidance (the “Guidance”) on predetermined change control plans (“PCCPs”) for devices that utilize artificial intelligence/machine learning (“AI/ML”) software. FDA’s stated goal for the Guidance is to “to provide a forward-thinking approach to promote the development of safe and effective AI-enabled devices,” and it represents notable progress in the Agency’s scramble to keep with – or at least prevent being too far outpaced by – the rapid pace of AI/ML innovation, as used in digital health technology.Continue Reading FDA Releases Long-Anticipated Guidance on Predetermined Change Control Plans for Devices That Utilize AI/ML Software

Last month, the U.S. Department of Justice (“DOJ”) quietly updated its March 2023 guidance on the evaluation of corporate compliance programs.[i] Of course, DOJ did not conduct a major rewrite, but interestingly, the updated guidance emphasizes the impact, and evaluation, of emerging technologies on compliance as well as the importance of data when assessing compliance programs.Continue Reading DOJ Updates Guidance on Evaluation of Corporate Compliance Programs

The US Food and Drug Administration (FDA) published an Action Plan for artificial intelligence (AI) and machine learning (ML) software on January 12, 2021 that provides near-term actions to develop a regulatory framework for AI and ML-based medical devices.  The quick takeaway is that FDA will publish a draft guidance on change control plans, a key concept from its April 2019 discussion paper on AI/ML-based software devices (previously reported here). FDA also will hold a public workshop on algorithm transparency and engage its partners and stakeholders on other key initiatives, such as evaluating bias in algorithms. While the Action Plan proposes a roadmap for advancing a regulatory framework, an operational framework appears to be further down the road.
Continue Reading FDA’s Action Plan for Artificial Intelligence: Highlights and Insights for Developers

On September 26, 2019, the US Food and Drug Administration (FDA) published six guidance documents clarifying its scope of authority and enforcement discretion policies in light of the 21st Century Cures Act (Cures Act). The long-awaited draft guidance on Clinical Decision Support (CDS) software sets forth FDA’s proposed approach to regulating CDS, including software that incorporates machine learning (ML) technology. Companies developing ML software for life science applications should consider reviewing FDA’s planned approach to inform their regulatory strategies.
Continue Reading New Set Of Guidance From FDA Provides Clarity On Digital Health Policies, Machine Learning