Bayesian estimation in pharmacokinetics/pharmicodynamics using regenerative sampling-based methods

Author

Kang, Dongwoo ; D´Argenio, David Z.

Author_Institution

Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA

Volume

2

fYear

1999

fDate

36434

Abstract

Bayesian estimation methods are applied to pharmacokinetic/pharmacodynamic (PK/PD) modeling problems, incorporating prior information on parameters with available data from an individual. The regenerative independence Metropolis-Hastings algorithm was used to generate samples from the posterior distribution of model parameters for the drugs busulfan and warfarin. Estimates for the posterior means and associated confidence intervals were calculated using ratio estimators and central limit theorem, respectively

Keywords

Bayes methods; Markov processes; biochemistry; importance sampling; maximum likelihood estimation; modelling; Bayesian estimation methods; Markov chain Monte Carlo; busulfan; central limit theorem; confidence intervals; drugs; error analysis; likelihood distribution; model parameters; pharmacodynamic modeling; pharmacokinetic modeling; prior information; ratio estimators; regenerative independence Metropolis-Hastings algorithm; regenerative sampling-based methods; warfarin; Bayesian methods; Biomedical measurements; Error analysis; Maximum likelihood estimation; Microwave integrated circuits; Monte Carlo methods; Parameter estimation; Robustness; Sampling methods; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint

Conference_Location

Atlanta, GA

ISSN

1094-687X

Print_ISBN

0-7803-5674-8

Type

conf

DOI

10.1109/IEMBS.1999.804141

Filename

804141