Verification and Validation

What are standards? A standard is a set of technical definitions, instructions, and guidelines for designers, manufacturers, users, inspectors, government agencies, etc., that are used to promote safety, reliability, efficiency, uniformity, and interchangeability for a wide-variety of engineering disciplines.

Verification and Validation (V&V) of Computational Modeling of Medical Devices


V&V 10 – Guide for Verification and Validation in Computational Solid Mechanics

V&V 20 – Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer

These standards provide the engineering and scientific communities with a common language, conceptual framework, and general guidance for implementing the process of verification and validation for computational modeling. Moreover, the concepts and terminology found within these publications are applicable to a wide-variety of applications and industries. These requirements and guidance will enable practitioners to better assess and enhance the credibility of computational models by applying the tools for verification of codes and solutions, simulation validation, and assessment of uncertainties in mathematical models, computational solutions, and experimental data.

V&V 40 Draft on Assessing Credibility of Computational Models through Verification and Validation: Application to Medical Devices is under development and anticipated for publication in late 2017.

This document will provide guidance on ensuring that the V&V activities establish sufficient credibility of the computational models used in the evaluation of medical devices. Given the inherent risk of using a computational model as a basis for predicting device performance, a risk-informed credibility assessment framework centers on ensuring that model credibility is commensurate with the risk associated with the decision made based on the computational model. The use of this document is intended to enable the formation and communication of the V&V activities and the associated model risk and credibility that support the use of a computational model to predict medical device performance.

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