Optimal design of mixed-effects PK/PD models based on differential equations

Yi Wang, Kent M. Eskridge, Saralees Nadarajah

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

There is a vast literature on the analysis of optimal design of nonlinear mixed-effects models (NLMMs) described by ordinary differential equations (ODEs) with analytic solution. However, much less has been published on the design of trials to fit such models with nonanalytic solution. In this article, we use the direct method to find parameter sensitivities, which are required during the optimization of models defined as ODEs, and apply them to find D-optimal designs for various specific situations relevant to population pharmacokinetic studies using a particular model with first-order absorption and elimination. In addition, we perform two simulation studies. The first one aims to show that the criterion computed from the development of the Fisher information matrix expression is a good measure to compare and optimize population designs, thus avoiding a large number of simulations; In the second one, a sensitivity analysis with respect to parameter misspecification allows us to compare the robustness of different population designs constructed in this article.

Original languageEnglish (US)
Pages (from-to)180-205
Number of pages26
JournalJournal of Biopharmaceutical Statistics
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2012

Keywords

  • D-optimal designs
  • Nonlinear mixed-effects models
  • PK/PD

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

Fingerprint Dive into the research topics of 'Optimal design of mixed-effects PK/PD models based on differential equations'. Together they form a unique fingerprint.

  • Cite this