Literature DB >> 8058613

Simulation for the analysis of distorted pharmacodynamic data.

Y Hashimoto1, J Ozaki, T Koue, A Odani, M Yasuhara, R Hori.   

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.

Entities:  

Mesh:

Substances:

Year:  1994        PMID: 8058613     DOI: 10.1023/a:1018918600265

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  8 in total

Review 1.  Population pharmacokinetics/dynamics.

Authors:  L B Sheiner; T M Ludden
Journal:  Annu Rev Pharmacol Toxicol       Date:  1992       Impact factor: 13.820

2.  Evaluation of methods for estimating population pharmacokinetic parameters. III. Monoexponential model: routine clinical pharmacokinetic data.

Authors:  L B Sheiner; S L Beal
Journal:  J Pharmacokinet Biopharm       Date:  1983-06

3.  On the solution to the Michaelis-Menten equation.

Authors:  S L Beal
Journal:  J Pharmacokinet Biopharm       Date:  1982-02

4.  Evaluation of methods for estimating population pharmacokinetic parameters. II. Biexponential model and experimental pharmacokinetic data.

Authors:  L B Sheiner; S L Beal
Journal:  J Pharmacokinet Biopharm       Date:  1981-10

5.  A simulation study comparing designs for dose ranging.

Authors:  L B Sheiner; Y Hashimoto; S L Beal
Journal:  Stat Med       Date:  1991-03       Impact factor: 2.373

6.  Nonlinear mixed effect modeling of the pharmacodynamics of natriuretic peptides in rats.

Authors:  Y Hashimoto; S Mori; N Hama; K Nakao; H Imura; M Yamaguchi; M Yasuhara; R Hori
Journal:  J Pharmacokinet Biopharm       Date:  1993-06

7.  Study designs for dose-ranging.

Authors:  L B Sheiner; S L Beal; N C Sambol
Journal:  Clin Pharmacol Ther       Date:  1989-07       Impact factor: 6.875

8.  Evaluation of methods for estimating population pharmacokinetics parameters. I. Michaelis-Menten model: routine clinical pharmacokinetic data.

Authors:  L B Sheiner; S L Beal
Journal:  J Pharmacokinet Biopharm       Date:  1980-12
  8 in total
  4 in total

1.  Nonlinearity detection: advantages of nonlinear mixed-effects modeling.

Authors:  E N Jonsson; J R Wade; M O Karlsson
Journal:  AAPS PharmSci       Date:  2000

2.  Simulation for population pharmacodynamic analysis of dose-ranging trials: usefulness of the mixture model analysis for detecting nonresponders.

Authors:  Takeshi Shiiki; Yukiya Hashimoto; Ken-ichi Inui
Journal:  Pharm Res       Date:  2002-06       Impact factor: 4.200

3.  Simulation for population analysis of Michaelis-Menten elimination kinetics.

Authors:  Y Hashimoto; T Koue; Y Otsuki; M Yasuhara; R Hori; K Inui
Journal:  J Pharmacokinet Biopharm       Date:  1995-04

Review 4.  Penetration of antibacterials into bone: pharmacokinetic, pharmacodynamic and bioanalytical considerations.

Authors:  Cornelia B Landersdorfer; Jürgen B Bulitta; Martina Kinzig; Ulrike Holzgrabe; Fritz Sörgel
Journal:  Clin Pharmacokinet       Date:  2009       Impact factor: 6.447

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.