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In Silico Trials: Verification, Validation And Uncertainty Quantification Of Predictive Models Used In The Regulatory Evaluation Of Biomedical Products
Methods ( IF 4.8 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.ymeth.2020.01.011
Marco Viceconti 1 , Francesco Pappalardo 2 , Blanca Rodriguez 3 , Marc Horner 4 , Jeff Bischoff 5 , Flora Musuamba Tshinanu 6
Affiliation  

Historically, the evidences of safety and efficacy that companies provide to regulatory agencies as support to the request for marketing authorization of a new medical product have been produced experimentally, either in vitro or in vivo. More recently, regulatory agencies started receiving and accepting evidences obtained in silico, i.e. through modelling and simulation. However, before any method (experimental or computational) can be acceptable for regulatory submission, the method itself must be considered "qualified" by the regulatory agency. This involves the assessment of the overall "credibility" that such a method has in providing specific evidence for a given regulatory procedure. In this paper, we describe a methodological framework for the credibility assessment of computational models built using mechanistic knowledge of physical and chemical phenomena, in addition to available biological and physiological knowledge; these are sometimes referred to as "biophysical" models. Using guiding examples, we explore the definition of the context of use, the risk analysis for the definition of the acceptability thresholds, and the various steps of a comprehensive verification, validation and uncertainty quantification process, to conclude with considerations on the credibility of a prediction for a specific context of use. While this paper does not provide a guideline for the formal qualification process, which only the regulatory agencies can provide, we expect it to help researchers to better appreciate the extent of scrutiny required, which should be considered early on in the development/use of any (new) in silico evidence.

中文翻译:

计算机试验:生物医学产品监管评估中使用的预测模型的验证、确认和不确定性量化

从历史上看,公司向监管机构提供的安全性和有效性证据作为对新医疗产品上市许可请求的支持,都是通过体外或体内实验产生的。最近,监管机构开始接收和接受通过计算机模拟获得的证据,即通过建模和仿真获得的证据。然而,在任何方法(实验或计算)可以接受监管提交之前,该方法本身必须被监管机构视为“合格”。这涉及评估这种方法在为特定监管程序提供具体证据方面的整体“可信度”。在本文中,我们描述了一个方法框架,用于评估使用物理和化学现象的机械知识以及可用的生物学和生理学知识建立的计算模型的可信度;这些有时被称为“生物物理”模型。使用指导性示例,我们探讨了使用环境的定义、可接受阈值定义的风险分析,以及全面验证、确认和不确定性量化过程的各个步骤,最后考虑到预测的可信度用于特定的使用环境。虽然本文没有为只有监管机构才能提供的正式资格认证流程提供指南,
更新日期:2021-01-01
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