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Title: A semi-mechanistic dose-finding design in oncology using pharmacokinetic/pharmacodynamic modeling Authors:  Yisheng Li - The University of Texas MD Anderson Cancer Center (United States) [presenting]
Xiao Su - Non-affiliated (United States)
Peter Mueller - UT Austin (United States)
Kim-Anh Do - The University of Texas MD Anderson Cancer Center (United States)
Abstract: While a number of phase I dose-finding designs in oncology exist, the commonly used ones are either algorithmic or empirical model-based. Other statistical designs that incorporate pharmacokinetic (PK) data mainly focus on summary PK information (such as the area under the concentration-time curve [AUC] or maximum serum concentration [Cmax]). We aim to: 1) propose an extended framework for modeling the dose-toxicity relationship, by incorporating dynamic PK and pharmacodynamic (PD) information via PK/PD modeling; and 2) apply this modeling framework in the design of phase I trials. The proposed modeling framework naturally incorporates the information on the impact of dose, schedule and method of administration (e.g., drug formulation and route of administration) on toxicity. We conduct extensive simulation studies to evaluate the performance of the proposed design and compare it with existing designs. We illustrate the proposed design by applying it to the setting of a phase I trial of a $\gamma$-secretase inhibitor in metastatic or locally advanced solid tumors. We also provide an R package to implement the proposed design.