ASAIO Journal · 2019 · 60 citations · 12 references
EngineeringBioengineeringBiomedical EngineeringHealth Technology AssessmentMethod ValidationRisk AssessmentMedical Device AssessmentMedical Device EvaluationMedical Device SafetyModel EvaluationModel ValidationSafety EvaluationComputational Model CredibilityComputational Prediction ModelsDesign ValidationDevice Safety EvaluationEquipment VerificationModel RiskModel Risk QuantificationVerification And Validation
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.
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