CORE-MD临床风险评分用于对基于人工智能的医疗器械软件进行监管评估
Frank E Rademakers1, Elisabetta Biasin2, Nico Bruining3
1Emeritus Professor of Cardiology, KU Leuven, Leuven, Belgium. frank.rademakers@kuleuven.be.
NPJ digital medicine
|February 6, 2025
概括
科尔-MD联盟开发了一个人工智能 (AI) 医疗设备的评分系统. 这一分数指导了在监管批准之前需要进行的临床研究的程度,平衡了市场前和市场后的证据.
科学领域:
- 医疗器械监管法规 医疗器械监管法规
- 医疗保健中的人工智能
- 产生临床证据的临床证据.
背景情况:
- 使用人工智能 (AI) 和机器学习 (ML) 的医疗设备带来了独特的监管挑战.
- 现有的框架可能无法充分解决AI/ML驱动的医疗技术的复杂性.
- 欧洲CORE-MD联盟的目标是通过提出一个新的评分系统来弥补这一差距.
研究的目的:
- 为支持AI/ML的医疗设备引入新的评分系统.
- 为确定监管批准的适当临床证据要求提供一个框架.
- 区分需要广泛的市场前评估和更适合市场后监督的产品.
主要方法:
- 欧洲CORE-MD财团开发了一个评分系统.
- 该得分包括三个关键领域:有效的临床关联,技术性能和临床性能.
- 该系统根据其风险概况和证据需求对设备进行分类.
主要成果:
- 拟议的分数根据所需的临床调查水平对AI/ML医疗器械进行分层.
- 高分数表明需要进行全面的上市前临床研究.
- 较低的分数表明,市场前评估可以与强有力的市场后证据相平衡.
结论:
- CORE-MD评分为AI/ML医疗器械的证据生成提供了一个结构化的方法.
- 这一框架可以帮助监管机构量身定制临床评估要求.
- 它促进了基于风险的方法,以确保创新医疗技术的安全性和有效性.
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