Webinar: ORS: FDA – Assessing the Predictive Capability of Computational Modeling for Medical Device Submissions

Webinar: ORS: FDA – Assessing the Predictive Capability of Computational Modeling for Medical Device Submissions

Posted by: Sarah Hollely Date: 07/06/17

The Center for Devices and Radiological Health is committed to advancing regulatory science with computational modeling.

This presentation will cover the new standard from the ASME Verification and Validation (V&V 40) subcommittee on Computational Modeling for Medical Devices.

Computational modeling can be used throughout the product life cycle to provide information about the technical performance, safety, and effectiveness of medical devices. Computational models can also be used to assess aspects of in vivo performance without subjecting patients to potential harm or unnecessary risk.

Establishing the credibility of a computational model to assess in vivo performance is important because of the inherent risk. Model credibility can be established through verification and validation (V&V) activities. Although methods for V&V are well-established, guidance is lacking on assessing the adequacy of the V&V activities for computational models used to support medical device development and evaluation.

Given the inherent risk of using a computational model as a basis for predicting medical device performance, a risk-informed credibility assessment framework has been developed. The framework centers on establishing that model credibility is commensurate with the risk associated with decisions influenced by the computational model. Thus, the intent of this standard is to provide guidance on how to establish risk-informed credibility goals, which are used in the development of the V&V plan, and then determine and communicate the credibility of computational models used in the evaluation of medical devices.

This seminar is hosted by the Orthopaedic Research Society.

For more details and to register visit: https://www.imagwiki.nibib.nih.gov/webinars/ors-fda-assessing-predictive-capability-computational-modeling-medical-device-submissions