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使用基于风险的框架评估计算模型可信度:在离心式血泵中的溶血应用。

Assessing Computational Model Credibility Using a Risk-Based Framework: Application to Hemolysis in Centrifugal Blood Pumps.

机构信息

From the U.S. Food and Drug Administration, Silver Spring, Maryland.

Baxter Healthcare Corporation, Round Lake, Illinois.

出版信息

ASAIO J. 2019 May/Jun;65(4):349-360. doi: 10.1097/MAT.0000000000000996.

Abstract

Medical device manufacturers using computational modeling to support their device designs have traditionally been guided by internally developed modeling best practices. A lack of consensus on the evidentiary bar for model validation has hindered broader acceptance, particularly in regulatory areas. This has motivated the US Food and Drug Administration and the American Society of Mechanical Engineers (ASME), in partnership with medical device companies and software providers, to develop a structured approach for establishing the credibility of computational models for a specific use. Charged with this mission, the ASME V&V 40 Subcommittee on Verification and Validation (V&V) in Computational Modeling of Medical Devices developed a risk-informed credibility assessment framework; the main tenet of the framework is that the credibility requirements of a computational model should be commensurate with the risk associated with model use. This article provides an overview of the ASME V&V 40 standard and an example of the framework applied to a generic centrifugal blood pump, emphasizing how experimental evidence from in vitro testing can support computational modeling for device evaluation. Two different contexts of use for the same model are presented, which illustrate how model risk impacts the requirements on the V&V activities and outcomes.

摘要

医疗器械制造商在使用计算模型来支持其设备设计时,传统上一直遵循内部制定的建模最佳实践。由于缺乏对模型验证的证据标准的共识,这阻碍了更广泛的接受,特别是在监管领域。这促使美国食品和药物管理局(FDA)和美国机械工程师协会(ASME)与医疗器械公司和软件提供商合作,为确定特定用途的计算模型的可信度制定了一种结构化方法。为此,ASME V&V 40 医疗器械计算模型验证与确认小组委员会制定了一个风险知情的可信度评估框架;该框架的主要原则是,计算模型的可信度要求应与模型使用相关的风险相称。本文概述了 ASME V&V 40 标准,并举例说明了该框架在通用离心血泵中的应用,重点介绍了体外测试的实验证据如何支持用于设备评估的计算模型。本文还介绍了同一模型的两种不同使用情境,说明了模型风险如何影响对验证与确认活动和结果的要求。

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