| dc.description.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. | |
