Review highlights modeling and simulation to enhance dosage selection in oncology, suggesting improved benefit-risk profiles.
Applying model-based approaches to leverage clinical and non-clinical data can support the identification of optimized dosage(s) for oncology products and allow for a better benefit-risk balance. In oncology, conventional dose-finding studies may lead to the selection of a poorly optimized dosage into subsequent studies, including those designed to demonstrate safety and efficacy in support of a marketing application. As a result, the clinical data obtained may be insufficient to optimize the benefit-risk profile of the drug without postmarketing studies. Model-informed drug development (MIDD), which includes modeling and simulation (e.g., quantitative system pharmacology, empirical or mechanistic pharmacokinetic/pharmacodynamic models), and integrative exposure-response analysis, can significantly enhance dosage selection and optimization. This review provides an update on the recent utilization and unique challenges of MIDD for dosage optimization in oncology drug development.
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Xiong et al. (2026) studied this question.
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