Optimal design in population kinetic experiments by set-valued methods

Peter Gennemark, Alexander Danis, Joakim Nyberg, Andrew C. Hooker, Warwick Tucker

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1 Citation (Scopus)

Abstract

We propose a new method for optimal experimental design of population pharmacometric experiments based on global search methods using interval analysis; all variables and parameters are represented as intervals rather than real numbers. The evaluation of a specific design is based on multiple simulations and parameter estimations. The method requires no prior point estimates for the parameters, since the parameters can incorporate any level of uncertainty. In this respect, it is similar to robust optimal design. Representing sampling times and covariates like doses by intervals gives a direct way of optimizing with rigorous sampling and dose intervals that can be useful in clinical practice. Furthermore, the method works on underdetermined problems for which traditional methods typically fail.

Original languageEnglish
Pages (from-to)495-507
Number of pages13
JournalThe AAPS Journal
Volume13
Issue number4
DOIs
Publication statusPublished - 1 Dec 2011
Externally publishedYes

Keywords

  • interval analysis
  • optimal experimental design
  • set-values methods

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