Consideration of a Credibility Assessment Framework in Model‐Informed Drug Development: Potential Application to Physiologically‐Based Pharmacokinetic Modeling and Simulation

Abstract

The use of computational models in drug development has grown during the past decade. These model‐informed drug development (MIDD) approaches can inform a variety of drug development and regulatory decisions. When used for regulatory decision making, it is important to establish that the model is credible for its intended use. Currently, there is no consensus on how to establish and assess model credibility, including the selection of appropriate verification and validation activities. In this article, we apply a risk‐informed credibility assessment framework to physiologically‐based pharmacokinetic modeling and simulation and hypothesize this evidentiary framework may also be useful for evaluating other MIDD approaches. We seek to stimulate a scientific discussion around this framework as a potential starting point for uniform assessment of model credibility across MIDD. Ultimately, an overarching framework may help to standardize regulatory evaluation across therapeutic products (i.e., drugs and medical devices).

Verifying and Validating Quantitative Systems Pharmacology and In Silico Models in Drug Development: Current Needs, Gaps, and Challenges

“…Of interest is the standard recently published by the American Society of Mechanical Engineers (ASME) on assessment of credibility of computational modeling through Verification and Validation, applied to medical devices (V&V40) 9 . The application of this framework to PBPK modeling was published the same year 10 . In the current situation, a similar initiative oriented to drug development exceeding PBPK would be of great value.…”

“…Lessons learned from regulatory guidelines on QSAR and traditional pharmacometric models reflect the general philosophy that model evaluation starts with the regulatory impact assessment closely related to the context of use 5‐10 . Two important points should be considered: (i) what the impact is of the model prediction on the identification of the appropriate research and development strategy and (ii) what the impact is of the research and development strategy in the regulatory submission.…”

“…Furthermore, academia is the main producer of the data and knowledge on which knowledge‐based models are built. The quality of this production needs to be improved, as shown by the reproducibility crisis, 10 and verified if incorporated in a model. Without hampering innovation and flexibility inherent to academic research, the developed set of guidelines for verification and validation can also be applied to research models published by academia.…”

In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing

“…They justified the unusual theoretical particle size distribution as likely to be the impact of the granulation and disintegration process. Recent publications suggest that the FDA is more prudent regarding the use of modeling and simulation for a regulatory purpose, because of the need to establish the model's "credibility" for its intended use [42].…”

Where Do PBPK Models Stand in Pharmacometrics and Systems Pharmacology?

“…In PBPK best practice, model "qualification" and "verification" terms are used and recently a "credibility" assessment framework is proposed. 9 Qualification generally refers to the process of establishing confidence in a PBPK model to handle and simulate the intended use and verification concerns with the predictive performance of the model for previously unseen scenarios. 10 Nonetheless, in the pharmacometric field, model assessment mainly focuses on goodness-of-fit between the model and the observed data and there is less or no emphasis on predicting unseen scenarios.…”