| Literature DB >> 16913403 |
Toshiro Niwa1, Kenji Tabata, Jiro Kimura, Mamoru Kamada, Yasuo Noda, Akira Takagi.
Abstract
We developed a new software (Ver. 2.0) based on the Bayesian estimation utilized in the therapeutic drug monitoring (TDM) of teicoplanin, a glycopeptide antibiotic, for the estimation of individual pharmacokinetic parameters. Individual pharmacokinetic parameters were calculated by a least squares methods, MULTI2 (BAYES), and a two-compartment model with population pharmacokinetic parameters in adult patients in Japan was adopted. The predicted teicoplanin concentrations in patients were similar to the observed concentrations, suggesting that the software predicts with acceptable precision. This new software is now available in clinical practice.Entities:
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Year: 2006 PMID: 16913403
Source DB: PubMed Journal: Jpn J Antibiot ISSN: 0368-2781