Scientific and regulatory evaluation of empirical pharmacometric models: An application of the risk informed credibility assessment framework

Empirical pharmacometric models are part of practically every regulatory submission for a new drug. The use of the models often exceeds descriptory roles and this change in their context of use increase the requirements on the evidence to support that they are credible. However, when it comes to assessing the trust in a model for a specific application, current tools are skewed to technical aspects and guidance documents often focused on model reporting or the iterative learning loops of model informed drug development (MIDD). There is an unmet need for a holistic tool that provide an end-to-end link from the initial question to the model-informed decision. We suggest the risk-informed credibility framework can be used for this purpose and offers strong support for the pharmacometrics models. We also introduce two tables for explicit description of key attributes of the model evaluation to facilitate and streamline the communication between stakeholders.