Design Evaluation and Optimization of Population Pharmacokinetics Model Using an R Package PopED

Howon Ryu () and Weng Kee Wong
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Howon Ryu: Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
Weng Kee Wong: Department of Biostatistics, University of California, Los Angeles, CA 90095, USA

Mathematics, 2023, vol. 11, issue 21, 1-15

Abstract: The rising cost in drug development has led to continuous calls for more efficient and powerful design optimization and analysis tools for pkpd studies. More sophisticated models are increasingly used to reflect reality, and current models invariably include non-linear mixed effects models that frequently require specialized computational tools for the design and analysis of the study. Population PK analysis employs non-linear mixed effects models and evaluates designs and optimizes them via a specialized yet versatile software package called PopED (version 0.6.0) in programming language R (version 4.2.2) for pharmacometrics analyses. We demonstrate the utilities of the package when different models and statistical criteria are used in real settings to determine the optimal sampling times and optimal dose levels for the subjects. We provide two applications; the first is illustrative and the second is a new application on developing an optimal dosing scheme for a two-compartment PK model with perturbation. Our target audiences are mathematicians and statisticians who are not aware of this useful and powerful analytic tool.

Keywords: design optimization; pharmacokinetics; R; PopED; non-linear mixed effects model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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