Navigating regulatory and policy challenges for AI enabled combination devices.

IF 2.7 Q3 ENGINEERING, BIOMEDICAL
Frontiers in medical technology Pub Date : 2024-11-28 eCollection Date: 2024-01-01 DOI:10.3389/fmedt.2024.1473350
Snigdha Santra, Preet Kukreja, Kinshuk Saxena, Sanyam Gandhi, Om V Singh
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引用次数: 0

Abstract

In recent years, the Artificial Intelligence (AI) has enabled conventional Combination Devices (CDs) to innovate in healthcare merging with technology sectors. However, the challenges like reliance on predicate devices in US Food and Drug Administration (FDA's 510(k) pathway, especially for perpetually updating AI are stressed. Though the European Union (EU's new Medical Device Regulations address software and AI, fitting adaptive algorithms into conformity assessments remains difficult. The urgent need for frameworks cognizant of AI risks like model degradation and data biases is emphasized. Insights from recalled devices and case studies elucidate challenges in regulatory navigation for manufacturers. Adaptive policy frameworks balancing patient safeguards and rapid innovation are proposed. Recommendations target regulators and policy makers, advocating global standards to enable safe, effective and equitable AI adoption. This article aims to examine AI-enabled combination device regulation, inspecting US and EU strategies as well as obstacles for manufacturers and regulators.

应对人工智能组合设备面临的监管和政策挑战。
近年来,人工智能(AI)使传统组合设备(cd)能够在医疗保健领域与技术领域相结合。然而,美国食品和药物管理局(FDA)的510(k)途径对谓词设备的依赖等挑战,特别是对不断更新的人工智能的依赖,也受到了压力。尽管欧盟的新医疗器械法规涉及软件和人工智能,但将自适应算法应用于符合性评估仍然很困难。强调了迫切需要识别AI风险(如模型退化和数据偏差)的框架。从召回设备和案例研究的见解阐明了制造商在监管导航方面的挑战。提出了平衡患者保障和快速创新的适应性政策框架。建议针对监管机构和政策制定者,倡导全球标准,以实现安全、有效和公平的人工智能采用。本文旨在研究人工智能组合设备监管,检查美国和欧盟的战略以及制造商和监管机构面临的障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
0.00%
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审稿时长
13 weeks
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