Literature DB >> 14695034

Comparative pharmacokinetic analysis by standard two-stage method versus nonparametric population modeling.

Vincent H Tam1, Sandra L Preston, George L Drusano.   

Abstract

STUDY
OBJECTIVE: To compare the two-stage method, a widely used analytical method in pharmacokinetic studies, with nonparametric population modeling by using the same data set for determining the oral bioavailability of ribavirin.
DESIGN: Pharmacokinetic analysis. Clinical research center. MATERIAL: Oral bioavailability data of ribavirin determined previously in six healthy adults. INTERVENTION: After 13C3-ribavirin 150 mg intravenously and unlabeled ribavirin 400 mg orally had been given 1 hour apart, serial serum and urine samples were obtained for up to 169 hours. Concentrations of 13C3-ribavirin and unlabeled ribavirin in serum and urine were determined by a high-performance liquid chromatography tandem mass spectrometric method.
MEASUREMENTS AND MAIN RESULTS: Serum and urine concentration-time profiles were comodeled with a three-compartment model. The analysis was performed again by using the nonparametric population analysis technique. Serum ribavirin concentrations underwent Monte Carlo simulation for 1000 subjects receiving a single 600-mg oral dose. Both methods were similar in determining the mean +/- SD bioavailability (51.8 +/- 21.8% by the two-stage method vs 54.8 +/- 16.4% by nonparametric modeling, p=0.79). However, the estimates of dispersion of model parameters and simulated drug exposures were substantially reduced by the population-modeling technique, as it takes into account covariance among model parameters and intersubject variability.
CONCLUSION: Although the study sample was small, our parallel analyses of the same data set clearly demonstrated that more precise parameter estimates are likely to result with the population-modeling technique. Having accurate and precise estimation of population pharmacokinetic parameters and their true variances is crucial, as, at any dose, there'will be a lower probability of encountering a concentration-driven toxicity because of fewer outliers as the variance associated with the parameters decreases.

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Year:  2003        PMID: 14695034     DOI: 10.1592/phco.23.15.1545.31969

Source DB:  PubMed          Journal:  Pharmacotherapy        ISSN: 0277-0008            Impact factor:   4.705


  3 in total

1.  Impact of sample size on the performance of multiple-model pharmacokinetic simulations.

Authors:  Vincent H Tam; Samer Kabbara; Rosa F Yeh; Robert H Leary
Journal:  Antimicrob Agents Chemother       Date:  2006-09-05       Impact factor: 5.191

2.  Pharmacodynamic variability beyond that explained by MICs.

Authors:  Rachel L Soon; Neang S Ly; Gauri Rao; Lance Wollenberg; Kuo Yang; Brian Tsuji; Alan Forrest
Journal:  Antimicrob Agents Chemother       Date:  2013-01-28       Impact factor: 5.191

3.  Successful treatment of parainfluenza virus 3 pneumonia with oral ribavirin and methylprednisolone in a bone marrow transplant recipient.

Authors:  Takahiro Shima; Goichi Yoshimoto; Atsushi Nonami; Shuro Yoshida; Kenjiro Kamezaki; Hiromi Iwasaki; Katsuto Takenaka; Toshihiro Miyamoto; Naoki Harada; Takanori Teshima; Koichi Akashi; Koji Nagafuji
Journal:  Int J Hematol       Date:  2008-08-19       Impact factor: 2.490

  3 in total

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