How the FDA Regulates AI

Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the “stethoscope of the 21st century” for its potential to revolutionize...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Academic radiology 2020-01, Vol.27 (1), p.58-61
Hauptverfasser: Harvey, H. Benjamin, Gowda, Vrushab
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 61
container_issue 1
container_start_page 58
container_title Academic radiology
container_volume 27
creator Harvey, H. Benjamin
Gowda, Vrushab
description Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the “stethoscope of the 21st century” for its potential to revolutionize diagnostic precision, provider workflow, and healthcare expenditure. Partially owing to AI's unique characteristics, and partially due to its novelty, existing regulatory paradigms are not well suited to balancing patient safety with furthering the growth of this new sector. The current review examines the historic, current, and proposed regulatory treatment of AI-empowered medical devices by the US Food and Drug Administration (FDA). An innovative framework proposed by the FDA seeks to address these issues by looking to current good manufacturing practices (cGMP) and adopting a total product lifecycle (TPLC) approach. If brought into force, this may reduce the regulatory burden incumbent on developers, while holding them to rigorous quality standards, maximizing safety, and permitting the field to mature.
doi_str_mv 10.1016/j.acra.2019.09.017
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2323481619</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1076633219304507</els_id><sourcerecordid>2323481619</sourcerecordid><originalsourceid>FETCH-LOGICAL-c356t-cdb8195865d44cc1868e2d102b8fbc190e0dec93c764e660eed232b98e18e7e33</originalsourceid><addsrcrecordid>eNp9kEFLw0AQRhdRbK3exYPk6CVxJ5vsTsBLqdYWCoLoeUl2p5qSNnU3Ufz3bmn1KAzMHN73wTzGroAnwEHerpLSuDJJORQJDwPqiA0BFcYZz-RxuLmSsRQiHbAz71ecQy5RnLKBAAQUqIbsctZ-Rd07RdP7cfRMb31TduSj8fycnSzLxtPFYY_Y6_ThZTKLF0-P88l4ERuRyy42tkIocpS5zTJjACVSaoGnFS4rAwUnbskUwiiZkZScyKYirQokQFIkxIjd7Hu3rv3oyXd6XXtDTVNuqO29DrTIECQUAU33qHGt946Weuvqdem-NXC9M6JXemdE74xoHgZUCF0f-vtqTfYv8qsgAHd7gMKXnzU57U1NG0O2dmQ6bdv6v_4fZzxunw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2323481619</pqid></control><display><type>article</type><title>How the FDA Regulates AI</title><source>ScienceDirect Journals (5 years ago - present)</source><creator>Harvey, H. Benjamin ; Gowda, Vrushab</creator><creatorcontrib>Harvey, H. Benjamin ; Gowda, Vrushab</creatorcontrib><description>Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the “stethoscope of the 21st century” for its potential to revolutionize diagnostic precision, provider workflow, and healthcare expenditure. Partially owing to AI's unique characteristics, and partially due to its novelty, existing regulatory paradigms are not well suited to balancing patient safety with furthering the growth of this new sector. The current review examines the historic, current, and proposed regulatory treatment of AI-empowered medical devices by the US Food and Drug Administration (FDA). An innovative framework proposed by the FDA seeks to address these issues by looking to current good manufacturing practices (cGMP) and adopting a total product lifecycle (TPLC) approach. If brought into force, this may reduce the regulatory burden incumbent on developers, while holding them to rigorous quality standards, maximizing safety, and permitting the field to mature.</description><identifier>ISSN: 1076-6332</identifier><identifier>EISSN: 1878-4046</identifier><identifier>DOI: 10.1016/j.acra.2019.09.017</identifier><identifier>PMID: 31818387</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Artificial intelligence ; FDA ; Medical Device ; Policy ; Radiology ; Regulation</subject><ispartof>Academic radiology, 2020-01, Vol.27 (1), p.58-61</ispartof><rights>2019 The Association of University Radiologists</rights><rights>Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-cdb8195865d44cc1868e2d102b8fbc190e0dec93c764e660eed232b98e18e7e33</citedby><cites>FETCH-LOGICAL-c356t-cdb8195865d44cc1868e2d102b8fbc190e0dec93c764e660eed232b98e18e7e33</cites><orcidid>0000-0001-9550-1876</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.acra.2019.09.017$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31818387$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Harvey, H. Benjamin</creatorcontrib><creatorcontrib>Gowda, Vrushab</creatorcontrib><title>How the FDA Regulates AI</title><title>Academic radiology</title><addtitle>Acad Radiol</addtitle><description>Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the “stethoscope of the 21st century” for its potential to revolutionize diagnostic precision, provider workflow, and healthcare expenditure. Partially owing to AI's unique characteristics, and partially due to its novelty, existing regulatory paradigms are not well suited to balancing patient safety with furthering the growth of this new sector. The current review examines the historic, current, and proposed regulatory treatment of AI-empowered medical devices by the US Food and Drug Administration (FDA). An innovative framework proposed by the FDA seeks to address these issues by looking to current good manufacturing practices (cGMP) and adopting a total product lifecycle (TPLC) approach. If brought into force, this may reduce the regulatory burden incumbent on developers, while holding them to rigorous quality standards, maximizing safety, and permitting the field to mature.</description><subject>Artificial intelligence</subject><subject>FDA</subject><subject>Medical Device</subject><subject>Policy</subject><subject>Radiology</subject><subject>Regulation</subject><issn>1076-6332</issn><issn>1878-4046</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kEFLw0AQRhdRbK3exYPk6CVxJ5vsTsBLqdYWCoLoeUl2p5qSNnU3Ufz3bmn1KAzMHN73wTzGroAnwEHerpLSuDJJORQJDwPqiA0BFcYZz-RxuLmSsRQiHbAz71ecQy5RnLKBAAQUqIbsctZ-Rd07RdP7cfRMb31TduSj8fycnSzLxtPFYY_Y6_ThZTKLF0-P88l4ERuRyy42tkIocpS5zTJjACVSaoGnFS4rAwUnbskUwiiZkZScyKYirQokQFIkxIjd7Hu3rv3oyXd6XXtDTVNuqO29DrTIECQUAU33qHGt946Weuvqdem-NXC9M6JXemdE74xoHgZUCF0f-vtqTfYv8qsgAHd7gMKXnzU57U1NG0O2dmQ6bdv6v_4fZzxunw</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Harvey, H. Benjamin</creator><creator>Gowda, Vrushab</creator><general>Elsevier Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9550-1876</orcidid></search><sort><creationdate>202001</creationdate><title>How the FDA Regulates AI</title><author>Harvey, H. Benjamin ; Gowda, Vrushab</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-cdb8195865d44cc1868e2d102b8fbc190e0dec93c764e660eed232b98e18e7e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Artificial intelligence</topic><topic>FDA</topic><topic>Medical Device</topic><topic>Policy</topic><topic>Radiology</topic><topic>Regulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Harvey, H. Benjamin</creatorcontrib><creatorcontrib>Gowda, Vrushab</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Academic radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Harvey, H. Benjamin</au><au>Gowda, Vrushab</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>How the FDA Regulates AI</atitle><jtitle>Academic radiology</jtitle><addtitle>Acad Radiol</addtitle><date>2020-01</date><risdate>2020</risdate><volume>27</volume><issue>1</issue><spage>58</spage><epage>61</epage><pages>58-61</pages><issn>1076-6332</issn><eissn>1878-4046</eissn><abstract>Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the “stethoscope of the 21st century” for its potential to revolutionize diagnostic precision, provider workflow, and healthcare expenditure. Partially owing to AI's unique characteristics, and partially due to its novelty, existing regulatory paradigms are not well suited to balancing patient safety with furthering the growth of this new sector. The current review examines the historic, current, and proposed regulatory treatment of AI-empowered medical devices by the US Food and Drug Administration (FDA). An innovative framework proposed by the FDA seeks to address these issues by looking to current good manufacturing practices (cGMP) and adopting a total product lifecycle (TPLC) approach. If brought into force, this may reduce the regulatory burden incumbent on developers, while holding them to rigorous quality standards, maximizing safety, and permitting the field to mature.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>31818387</pmid><doi>10.1016/j.acra.2019.09.017</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0001-9550-1876</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1076-6332
ispartof Academic radiology, 2020-01, Vol.27 (1), p.58-61
issn 1076-6332
1878-4046
language eng
recordid cdi_proquest_miscellaneous_2323481619
source ScienceDirect Journals (5 years ago - present)
subjects Artificial intelligence
FDA
Medical Device
Policy
Radiology
Regulation
title How the FDA Regulates AI
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T05%3A28%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=How%20the%20FDA%20Regulates%20AI&rft.jtitle=Academic%20radiology&rft.au=Harvey,%20H.%20Benjamin&rft.date=2020-01&rft.volume=27&rft.issue=1&rft.spage=58&rft.epage=61&rft.pages=58-61&rft.issn=1076-6332&rft.eissn=1878-4046&rft_id=info:doi/10.1016/j.acra.2019.09.017&rft_dat=%3Cproquest_cross%3E2323481619%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2323481619&rft_id=info:pmid/31818387&rft_els_id=S1076633219304507&rfr_iscdi=true