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FDA Issues Artificial Intelligence/Machine Learning Action Plan

On January 12, 2021, the US Food and Drug Administration (FDA) released its Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan. The Action Plan outlines five actions that FDA intends to take to further its oversight of AI/ML-based SaMD:

  1. Further develop the proposed regulatory framework, including through draft guidance on a predetermined change control plan for “learning” ML algorithms
    • FDA intends to publish the draft guidance on the predetermined change control plan in 2021 in order to clarify expectations for SaMD Pre-Specifications (SPS), which explain what “aspects the manufacturer changes through learning,” and Algorithm Change Protocol (ACP), which explains how the “algorithm will learn and change while remaining safe and effective.” The draft guidance will focus on what should be included in an SPS and ACP in order to ensure safety and effectiveness of the AI/ML SaMD algorithms. Other areas of focus include identification of modifications appropriate under the framework and the submission and review process.
  2. Support development of good machine learning practices (GMLP) to evaluate and improve ML algorithms
    • GMLPs are critical in guiding product development and oversight of AI/ML products. FDA has developed relationships with several communities, including the Institute of Electrical and Electronics Engineers P2801 Artificial Intelligence Medical Device Working Group, the International Organization for Standardization/ Joint Technical Committee 1/ SubCommittee 42 (ISO/ IEC JTC 1/SC 42) – Artificial Intelligence, and the Association for the Advancement of Medical Instrumentation/British Standards Institution Initiative on AI in medical technology. FDA is focused on working with these communities to come to a consensus on GMLP requirements.
  3. Foster a patient-centered approach, including transparency
    • FDA would like to increase patient education to ensure that users have important information about the benefits, risks and limitations of AI/ML products. To that end, FDA held a Patient Engagement Advisory meeting in October 2020, and the agency will use input gathered during the meeting to help identify types of information that it will recommend manufacturers include in AI/ML labeling to foster education and promote transparency.
  4. Develop methods to evaluate and improve ML algorithms
    • To address potential racial, ethical or socio-economic bias that may be inadvertently introduced into AI/ML systems that are trained using data from historical datasets, FDA intends to collaborate with researchers to improve methodologies for the identification and elimination of bias, and to improve the algorithms’ robustness to adapt to varying clinical inputs and conditions.
  5. Advance real world performance monitoring pilots
    • FDA states that gathering real world performance data on the use of the SaMD is an important risk-mitigation tool, as it may allow manufacturers to understand how their products are being used, how they can be improved, and what safety or usability concerns manufacturers need to address. To provide clarity and direction related to real world performance data, FDA supports the piloting of real world performance monitoring. FDA will develop a framework for gathering, validating and evaluating relevant real world performance parameters [...]

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Is Your Software a Medical Device? FDA Issues Six Digital Health Guidance Documents

The 21st Century Cures Act, enacted in December 2016, amended the definition of “medical device” in section 201(h) of the Federal Food, Drug, and Cosmetic Act (FDCA) to exclude five distinct categories of software or digital health products. In response, the US Food and Drug Administration (FDA) issued new digital health guidance and revised several pre-existing medical device guidance documents. FDA also stated that it would continue to assess how to update and revise these guidance documents as its thinking evolved.

Late last week, FDA issued five final guidance documents and re-issued a draft guidance document to better reflect FDA’s current thinking on software as a medical device (SaMD) and other digital health products:

Most of the guidance documents reflect modest changes to prior draft guidance documents that describe categories of low-risk health and wellness devices that FDA does not intend to regulate. FDA’s new draft Clinical Decision Support (CDS) Software guidance, however, provides a new and more detailed analysis of risk factors that FDA will apply to determine whether a CDS tool is a medical device. FDA updated its previously issued draft CDS guidance without finalizing it. Although the new guidance does not explain why FDA is reissuing the CDS guidance in draft, the new draft guidance seems to reflect the agency’s attempt to better align its definition of non-device software with the often misunderstood and misinterpreted statutory definition of CDS in section 520(o)(1)(E) of the Cures Act. The chart below summarizes the key provisions and changes to these guidance documents.

Digital health products can present a particular challenge for developers and regulators in assessing the appropriate regulatory pathways for a new product. The updated guidance documents reflect the need for a more flexible, risk-based approach to regulation that accommodates a rapidly evolving technological landscape. These documents also reflect what appears to be the new normal for digital health regulation—the need for iterative thinking and ongoing revisions to interpretive guidance documents to keep pace with a constantly changing marketplace.

Click here to read the full client alert on this issue. 




Recycle, Recycle, Recycle: Key Considerations for Research, Medical Education, and Other Secondary Uses of Data

The digitization of health care and the proliferation of electronic medical records is happening rapidly, generating large quantities of data with potential to provide valuable insights into disease and wellness and help solve challenging public health problems.

There is tremendous enthusiasm over the possibilities of leveraging this data for secondary use–i.e., a use of data that is distinct from the purpose for which it was originally collected. However, such secondary use is often subject to intersecting legal and regulatory regimes–including HIPAA, the Common Rule, and the Federal Food, Drug, and Cosmetic Act and its implementing regulations–that are not fully harmonized.  This lack of harmonization in requirements, coupled with the wide range of industry players involved–including regulators, academic medical centers, health systems, payers, technology companies, manufacturers and industry entities, research institutions, registries, and professional societies, to name a few– presents challenges that require careful planning and implementation. While regulators have recently taken significant steps to reconcile the differences among these laws and provide a path forward for harnessing the potential of big data, some specific requirements within these individual regulations continue to present challenges.

It is critical for academic medical centers and teaching hospitals, which stand at the intersection of government-funded research and industry-sponsored research, and are also paving the way in partnerships with non-traditional health care players—to understand the evolving legal framework and business and compliance imperatives behind the quest for digital health information.

During the AHLA Annual Meeting on Tuesday, June 26, McDermott partner Jiayan Chen will review trends and the value proposition relating to secondary use, with a particular focus on challenges presented by secondary use in the precision medicine and digital health context.  Along with co-presenter Leah Voigt, she will explore key regulatory and sub-regulatory developments relating to the secondary use of data under FDA regulations, the Common Rule, and HIPAA, and will also use case studies to explore, in a practical context, the challenges and ambiguities that remain when pursuing internal secondary use initiatives and external collaborations, including implementation and contracting tips, insights, and strategies.

Recycle, Recycle, Recycle: Key Considerations for Research, Medical Education, and Other Secondary Uses of Data
AHLA Annual Meeting, Chicago, IL | June 26, 2018 | 9:45 – 10:45 am | Registration and program details.

McDermott’s Cocktail Reception during the AHLA Annual Meeting
The Art Institute of Chicago | June 26, 2018 | 6:00 – 8:00 pm
Following the programming on Tuesday, we invite you to join us for our annual cocktail reception at The Art Institute of Chicago. We look forward to an evening of networking, cocktails and private gallery tours with our colleagues, friends and fellow AHLA members. RSVP today!




New York AG Settlement with App Developers Serves as a Warning for the Need for Evidence-Backed Commercial Claims

On March 23, 2017, the New York Attorney General’s office announced that it has settled with the developers of three mobile health (mHealth) applications (apps) for, among other things, alleged misleading commercial claims. This settlement highlights for mHealth app developers the importance of systematically gathering sufficient evidence to support their commercial claims.

Read the full article.




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