Bayesian Adaptive Designs Using Pharmacokinetic-Pharmcodynamic Modeling for Early Phase Clinical Trials

Xiao Su, The University of Texas School of Public Health

Abstract

In oncology field, early phase clinical trial designs have attracted the interest of clinicians and biostatisticians. There are several standard phase I and phase I/II designs that have been proposed and widely used for dosing strategy in medical practice. ^ Motivated by the translational methods which try to incorporate the biological knowledge from preclinical studies, this dissertation includes three adaptive Bayesian designs for dosing strategy using PK-PD modeling. It includes three specific designs: (1) proposed a design for phase I trials to recommend MTD for each schedule; (2) proposed a design for phase I/II to recommend biological optimal dosing regimen; (3) proposed a design for phase I/II to recommend biological optimal dosing regimen in population level and allocate patients to the subject-specific optimal dosing regimen accounting for the between-subject-variation. ^ To evaluate the operating characteristics, extensive simulation studies have been carried out. The results demonstrate the performance of the proposed designs is superior to current methods and nonparametric benchmark in various practical scenarios.^

Subject Area

Biostatistics

Recommended Citation

Su, Xiao, "Bayesian Adaptive Designs Using Pharmacokinetic-Pharmcodynamic Modeling for Early Phase Clinical Trials" (2017). Texas Medical Center Dissertations (via ProQuest). AAI10257969.
http://digitalcommons.library.tmc.edu/dissertations/AAI10257969

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