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. Several recently published numerical models of the human spine were considered for their implementation of various comparators as a means of model validation. The comparators used in each published model were examined and classified as either an engineering or natural comparator. Further, a method of scoring the comparators was developed based on guidelines from ASME V&V40 and the draft guidance from the US FDA, and used to evaluate the pertinence of each comparator in model validation. Thus, this review article aimed to score the various comparators used to validate numerical models of the spine in order to examine the comparator's ability to lend credibility towards computational models of the spine for specific contexts of use.

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. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative.

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. 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.