Software as medical devices: requirements and regulatory landscape in the United States.

IF 2.7
Shivani Shah, Priyanka Thakor, Aakash Shah, Om V Singh
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Abstract

Introduction: The integration of software into medical devices has profoundly transformed the healthcare landscape, enabling more precise diagnostics, personalized treatment plans, and remote patient monitoring. The rapid pace of software development - especially with emerging technologies like artificial intelligence (AI) and machine learning (ML) - demands specialized regulatory frameworks to ensure patient safety, clinical effectiveness, and product reliability.

Areas covered: Software as a Medical Device (SaMD) refers to software intended for medical purposes that operates independently of a physical medical device. This article traces the historical development of regulatory approaches, deconstructs existing frameworks, analyzes key challenges and influencing factors, presents case studies, and anticipates future trends. A narrative literature search was conducted using PubMed, Google Scholar, FDA.gov, EUR-Lex and IMDRF.org, covering materials published between January 2013 and May 2025.

Expert opinion: The Total Product Lifecycle (TPLC) framework is essential for managing the evolving performance and risks associated with AI/ML-based SaMD. AI/ML-powered SaMD is not merely transforming healthcare delivery, it is challenging and redefining the foundational assumptions of medical regulation. The regulatory systems must evolve ensuring transparency, maintaining public trust, addressing algorithmic bias, and promoting equitable access to the benefits of these advanced technologies. Innovation must be guided by a framework rooted in safety, integrity, and equity.

作为医疗设备的软件:美国的要求和监管环境。
简介:将软件集成到医疗设备中已经深刻地改变了医疗保健领域,实现了更精确的诊断、个性化的治疗计划和远程患者监控。软件开发的快速发展——尤其是人工智能(AI)和机器学习(ML)等新兴技术——需要专门的监管框架来确保患者安全、临床有效性和产品可靠性。涵盖领域:作为医疗设备的软件(SaMD)是指用于医疗目的的独立于物理医疗设备运行的软件。本文追溯了监管方法的历史发展,解构了现有框架,分析了关键挑战和影响因素,提出了案例研究,并预测了未来的趋势。使用PubMed、谷歌Scholar、FDA.gov、EUR-Lex和IMDRF.org进行叙事文献检索,检索时间为2013年1月至2025年5月。专家意见:整个产品生命周期(TPLC)框架对于管理与基于AI/ ml的SaMD相关的不断发展的性能和风险至关重要。人工智能/机器学习驱动的SaMD不仅改变了医疗保健服务,而且正在挑战和重新定义医疗监管的基本假设。监管体系必须不断发展,确保透明度,维护公众信任,解决算法偏见,促进公平获得这些先进技术的好处。创新必须以安全、诚信和公平为基础的框架为指导。
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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