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    A Decade of Food and Drug Administration Medical Device Authorizations (2015–2025): Pathway, Specialty, and Artificial Intelligence/Machine Learning Trends

    Source: Journal of Medical Devices:;2026:;volume( 020 ):;issue:003::page 128
    Author:
    Muthukrishnan, Venkatesan
    ,
    Bastani, Mehrad
    DOI: 10.1115/1.4071334
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. A comprehensive ten-year analysis of U.S. Food and Drug Administration (FDA) medical device authorizations by regulatory pathway, therapeutic specialty, and artificial intelligence/machine learning (AI/ML) status provides a descriptive baseline for understanding how authorization volumes, pathways, and review timelines have evolved over time. This study analyzed U.S. FDA medical device authorizations from January 2015 to June 2025 using public databases. Device submissions were categorized by regulatory pathway (premarket notification (510(k)), premarket approval (PMA), PMA supplement, De Novo), medical specialty, and AI/ML status. Visual summaries of authorization volumes, review times, and specialty distributions were generated. Of 57,641 authorizations during the study period, including both new devices and authorized changes to previously cleared or approved devices—55.7% were via 510(k), 43.1% via PMA supplements, while PMA (0.62%) and De Novo (0.58%) represented a small fraction. Authorization times varied, with PMA taking the longest (median ∼337 days), followed by De Novo (median ∼315 days), 510(k) (median ∼128 days), and PMA supplements (median ∼29 days). AI/ML-enabled device authorizations increased over the study period, predominantly through the 510(k) pathway, with radiology accounting for the largest share. These findings provide a high-level descriptive view of authorization patterns and may support contextual understanding of FDA regulatory pathways and timelines.
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      A Decade of Food and Drug Administration Medical Device Authorizations (2015–2025): Pathway, Specialty, and Artificial Intelligence/Machine Learning Trends

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    contributor authorMuthukrishnan, Venkatesan
    contributor authorBastani, Mehrad
    date accessioned2026-08-23T07:46:33Z
    date available2026-08-23T07:46:33Z
    date copyright2026/06/01
    date issued2026
    identifier issn1932-6181
    identifier othermed-25-1195.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4315585
    description abstractAbstract. A comprehensive ten-year analysis of U.S. Food and Drug Administration (FDA) medical device authorizations by regulatory pathway, therapeutic specialty, and artificial intelligence/machine learning (AI/ML) status provides a descriptive baseline for understanding how authorization volumes, pathways, and review timelines have evolved over time. This study analyzed U.S. FDA medical device authorizations from January 2015 to June 2025 using public databases. Device submissions were categorized by regulatory pathway (premarket notification (510(k)), premarket approval (PMA), PMA supplement, De Novo), medical specialty, and AI/ML status. Visual summaries of authorization volumes, review times, and specialty distributions were generated. Of 57,641 authorizations during the study period, including both new devices and authorized changes to previously cleared or approved devices—55.7% were via 510(k), 43.1% via PMA supplements, while PMA (0.62%) and De Novo (0.58%) represented a small fraction. Authorization times varied, with PMA taking the longest (median ∼337 days), followed by De Novo (median ∼315 days), 510(k) (median ∼128 days), and PMA supplements (median ∼29 days). AI/ML-enabled device authorizations increased over the study period, predominantly through the 510(k) pathway, with radiology accounting for the largest share. These findings provide a high-level descriptive view of authorization patterns and may support contextual understanding of FDA regulatory pathways and timelines.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Decade of Food and Drug Administration Medical Device Authorizations (2015–2025): Pathway, Specialty, and Artificial Intelligence/Machine Learning Trends
    typeJournal Paper
    journal volume20
    journal issue3
    journal titleJournal of Medical Devices
    identifier doi10.1115/1.4071334
    journal fristpage128
    journal lastpage132
    page5
    treeJournal of Medical Devices:;2026:;volume( 020 ):;issue:003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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