On November 17, 2023, FDA published a new guidance document titled “Assessing the Credibility of Computational Modeling and Simulation in Medical Device Submissions”. Within this context, credibility is defined as “the trust in the predictive capability of a computational model.” Computational Modeling and Simulation (CM&S) is becoming more and more prevalent within various submission types including 510(k)s, Premarket Approval (PMA) Applications, Humanitarian Device Exemption (HDE) Applications, Investigational Device Exemption (IDE) Applications, and De Novo classification requests, as well as Medical Device Development Tools (MDDTs). Consequently, consistency and transparency in the ways CM&S is performed, utilized, and documented is essential to increase the likelihood of a seamless and efficient FDA review process.
FDA recognizes that computational models can be used in a variety of ways in medical device regulatory submissions, including but not limited to: (i) In silico device testing, (ii) CM&S used within medical device software, (iii) In silico clinical trials, and (iv) CM&S-based qualified tools. Documentation must clearly address model credibility. Demonstrating credibility involves various activities that include verification, validation, uncertainty quantification, applicability analysis, as well as adequacy assessment, all of which are explained within the guidance document. FDA further stipulates that “for in silico device testing and in silico clinical trials, final simulation results should be submitted to FDA with supporting credibility evidence so that FDA can assess the credibility of those simulation results. For CM&S in medical device software and MDDTs, example simulation results should be submitted to FDA with supporting credibility evidence so that FDA can assess if future simulations (to be performed post-market or post-tool qualification) are expected to be credible.”
To clearly demonstrate the credibility of a computational model, FDA recommends the following:
- Describe the question(s) of interest to be addressed in the regulatory submission that will be informed by the computational model.
- Define the context of use (COU) of the computational model.
- Determine the model risk.
- Identify and categorize the credibility evidence, either previously generated or planned, which will support credibility of the computational model for the COU.
- Define credibility factors for the proposed credibility evidence. For prospectively planned activities, set prospective credibility goals for each credibility factor, with a plan to achieve these goals. For previously generated data, assess the credibility levels achieved.
- Perform prospective adequacy assessment: if the credibility goals are achieved, will the credibility evidence be sufficient to support using the model for the COU given the risk assessment?
- Generate the credibility evidence by executing the proposed study(ies) and/or analyzing previously generated data.
- Determine if credibility goals were met and perform post-study adequacy assessment: does the credibility evidence support using the model for the COU given the risk assessment?
- Prepare a CM&S credibility assessment report for inclusion in the regulatory submission.
The 42-page guidance document provides very detailed information, illustrations/flow-charts, and examples relating to each of these steps, as well as definitions of all applicable terms. Medical device manufacturers should be sure to carefully review the guidance document and ensure not only a thorough and complete understanding of all recommendations but also a clear and effective approach for implementation.
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