ARTICLE
19 November 2019

Adapting To FDA's Proposal For Diagnosis Support Software

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Sheppard Mullin Richter & Hampton

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With the rise of artificial intelligence and machine learning, clinical decision support, or CDS, software presents a novel opportunity to analyze immensely large amounts of data for patterns or ...
United States Food, Drugs, Healthcare, Life Sciences

With the rise of artificial intelligence and machine learning, clinical decision support, or CDS, software presents a novel opportunity to analyze immensely large amounts of data for patterns or other information that may be relevant to a particular patient's diagnosis or health care options.

In late September, the U.S. Food and Drug Administration published a draft guidance on clinical decision support software that sets forth the agency's proposed approach to regulating CDS, including CDS that incorporates machine learning technology.

Companies developing CDS software for life science or other medical applications should review the FDA's planned approach, and the numerous examples provided, to understand how the FDA intends to regulate their software. Making adjustments to the software — for example, by adding transparency to the end user — could shift the regulatory profile of the software.

Click here for the full article: Adapting To FDA's Proposal For Diagnosis Support Software

*This article was originally posted in Law360 on November 4, 2019

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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