The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

Abstract Artificial intelligence (AI) and Machine learning (ML) systems in medicine are poised to significantly improve health care, for example, by offering earlier diagnoses of diseases or recommending optimally individualized treatment plans. However, the emergence of AI/ML in medicine also creat...

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Autores principales:	Sara Gerke, Boris Babic, Theodoros Evgeniou, I. Glenn Cohen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/71fe73e8f86343b4ab6486b9125a611b
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spelling	oai:doaj.org-article:71fe73e8f86343b4ab6486b9125a611b2021-12-02T18:15:35ZThe need for a system view to regulate artificial intelligence/machine learning-based software as medical device10.1038/s41746-020-0262-22398-6352https://doaj.org/article/71fe73e8f86343b4ab6486b9125a611b2020-04-01T00:00:00Zhttps://doi.org/10.1038/s41746-020-0262-2https://doaj.org/toc/2398-6352Abstract Artificial intelligence (AI) and Machine learning (ML) systems in medicine are poised to significantly improve health care, for example, by offering earlier diagnoses of diseases or recommending optimally individualized treatment plans. However, the emergence of AI/ML in medicine also creates challenges, which regulators must pay attention to. Which medical AI/ML-based products should be reviewed by regulators? What evidence should be required to permit marketing for AI/ML-based software as a medical device (SaMD)? How can we ensure the safety and effectiveness of AI/ML-based SaMD that may change over time as they are applied to new data? The U.S. Food and Drug Administration (FDA), for example, has recently proposed a discussion paper to address some of these issues. But it misses an important point: we argue that regulators like the FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective—from a product view to a system view—is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies like the FDA who are used to regulating products, not systems. We offer several suggestions for regulators to make this challenging but important transition.Sara GerkeBoris BabicTheodoros EvgeniouI. Glenn CohenNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 3, Iss 1, Pp 1-4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Sara Gerke Boris Babic Theodoros Evgeniou I. Glenn Cohen The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
description	Abstract Artificial intelligence (AI) and Machine learning (ML) systems in medicine are poised to significantly improve health care, for example, by offering earlier diagnoses of diseases or recommending optimally individualized treatment plans. However, the emergence of AI/ML in medicine also creates challenges, which regulators must pay attention to. Which medical AI/ML-based products should be reviewed by regulators? What evidence should be required to permit marketing for AI/ML-based software as a medical device (SaMD)? How can we ensure the safety and effectiveness of AI/ML-based SaMD that may change over time as they are applied to new data? The U.S. Food and Drug Administration (FDA), for example, has recently proposed a discussion paper to address some of these issues. But it misses an important point: we argue that regulators like the FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective—from a product view to a system view—is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies like the FDA who are used to regulating products, not systems. We offer several suggestions for regulators to make this challenging but important transition.
format	article
author	Sara Gerke Boris Babic Theodoros Evgeniou I. Glenn Cohen
author_facet	Sara Gerke Boris Babic Theodoros Evgeniou I. Glenn Cohen
author_sort	Sara Gerke
title	The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
title_short	The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
title_full	The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
title_fullStr	The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
title_full_unstemmed	The need for a system view to regulate artificial intelligence/machine learning-based software as medical device
title_sort	need for a system view to regulate artificial intelligence/machine learning-based software as medical device
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/71fe73e8f86343b4ab6486b9125a611b
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The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

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