A1048
Title: Optimal dosage justification through model-informed drug development approaches
Authors: Zoey Tang - AstraZeneca (United States) [presenting]
Abstract: Background: Project Optimus has been reforming the dose selection and optimization paradigm in oncology. Semi-mechanistic models have emerged as powerful tools for optimizing dosing strategies in oncology drug development. In the current analysis, virtual trials were simulated using the Tumor Growth Inhibition-Progression-Free Survival (TGI-PFS) model to further investigate the selection of an optimal dose for patients in the context of Project Optimus. Methods: The TGI model described the tumor size as the result of exponential tumor growth, a tumor shrinkage that was driven by pharmacokinetics (PK), and a resistance term. Sequentially, a TGI-PFS model was developed to evaluate the relationship between tumor dynamic metrics and PFS. Virtual trials were simulated to explore efficacy outcomes across dose levels D1, D2, and D3. Results: The simulations demonstrated that AZX1234 administered at dose level D1 leads to superior tumor control and enhanced progression-free survival compared to the outcomes achieved at dose levels D2 and D3.Conclusions: The application of a TGI-PFS modeling framework that integrates drug exposure, tumor shrinkage, and clinical outcomes to guide dose optimization is supported. The importance of integrating advanced modeling techniques into the dose optimization paradigm is underscored, aligning with the principles of Project Optimus to deliver patient-centered therapeutic strategies.
