A Critical Comparison of Comparators Used to Demonstrate Credibility of Physics-Based Numerical Spine Models.

The ability of new medical devices and technology to demonstrate safety and effectiveness, and consequently acquire regulatory approval, has been dependent on benchtop, in vitro, and in vivo evidence and experimentation. Regulatory agencies have recently begun accepting computational models and simulations as credible evidence for virtual clinical trials and medical device development. However, it is crucial that any computational model undergo rigorous verification and validation activities to attain credibility for its context of use before it can be accepted for regulatory submission.

Possible Contexts of Use for In Silico Trials Methodologies: A Consensus-Based Review.

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process.

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

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.