Simulation for the Analysis of Distorted Pharmacodynamic Data

Yukiya Hashimoto, Junko Ozaki, Toshiko Koue, Atsuko Odani, Masato Yasuhara*, Ryohei Hori

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

A simulation study was conducted to compare the performance of alternative approaches for analyzing the distorted pharmacodynamic data. The pharmacodynamic data were assumed to be obtained from the natriurertic peptide-type drug, where the diuretic effect arises from the hyperbolic (Emax) dose–response model and is biased by the dose-dependent hypotensive effect. The nonlinear mixed effect model (NONMEM) method enabled assessment of the effects of hemodynamics on the diuretic effects and also quantification of intrinsic diuretic activities, but the standard two-stage (STS) and naive pooled data (NPD) methods did not give accurate estimates. Both the STS and the NONMEM methods performed well for unbiased data arising from a one-compartment model with saturable (Michaelis–Menten) elimination, whereas the NPD method resulted in inaccurate estimates. The findings suggest that nonlinearity and/or bias problems result in poor estimation by NPD and STS analyses and that the NONMEM method is useful for analyzing such nonlinear and distorted pharmacodynamic data.

Original languageEnglish
Pages (from-to)545-548
Number of pages4
JournalPharmaceutical Research
Volume11
Issue number4
DOIs
StatePublished - 1994/04

Keywords

  • Michaelis–Menten kinetics
  • nonlinear mixed effect model (NONMEM)
  • pharmacodynamics
  • population pharmacokinetics
  • statistical simulation

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Medicine
  • Pharmacology
  • Pharmaceutical Science
  • Organic Chemistry
  • Pharmacology (medical)

Fingerprint

Dive into the research topics of 'Simulation for the Analysis of Distorted Pharmacodynamic Data'. Together they form a unique fingerprint.

Cite this