There’s been a big increase in artificial intelligence (AI) within digital health technologies. The cross between medical technology and AI requires that products be evaluated in accordance with domestic and international regulations. These technologies include interacting hybrids of software and hardware, stand-alone software, and software as a medical device interfacing with medical administrative systems.

The FDA’s Digital Health Department recommends using digital health criteria and traditional software guidance to carry out specific design approaches as needed per the technology. Both the FDA and the Medicine and Healthcare products Regulation Agency (MHRA) have expressed the need for machine-learning transparency and further explanation of validating an algorithm that is continually learning, changing, and improving itself.

With an evolving regulatory environment and an ever-expanding digital health market, there’s a need to find new approaches to address compliance around AI software.¹ This wouldn’t exclude the need to ensure compliance to computer software regulations such as 21 CFR Part 11 and Annex 11 for audit trails, electronic records, and signatures.

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