Literature DB >> 3709024

An evaluation of population pharmacokinetics in therapeutic trials. Part I. Comparison of methodologies.

T H Grasela, E J Antal, R J Townsend, R B Smith.   

Abstract

NONMEM, a computer program that uses the method of extended least-squares analysis, has been advocated as a means of obtaining estimates of population pharmacokinetic parameters when only fragmentary information can be obtained from subjects. To assess the performance of this program, we compared NONMEM with traditional methods for the estimation of population pharmacokinetic parameters with data collected during a phase III clinical trial of alprazolam. NONMEM estimates of the population mean clearance and its coefficient of variation were identical to the estimates obtained with traditional pharmacokinetic techniques. Moreover, NONMEM estimates of these parameters remained stable even when a few as three data points were available per subject. NONMEM estimates of the mean volume of distribution and its coefficient of variation appear to be overestimated, apparently because of the sampling scheme used to generate data for the NONMEM analysis. Suggestions for the effective use of NONMEM in clinical trials, to maximize the benefits of this approach, are provided. Our results lend further support for the use of NONMEM to estimate population pharmacokinetic parameters of a drug from data generated during phase III clinical trials.

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Year:  1986        PMID: 3709024     DOI: 10.1038/clpt.1986.107

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  15 in total

1.  Population pharmacokinetics: theory and practice.

Authors:  L Aarons
Journal:  Br J Clin Pharmacol       Date:  1991-12       Impact factor: 4.335

Review 2.  Expanding clinical applications of population pharmacodynamic modelling.

Authors:  C Minto; T Schnider
Journal:  Br J Clin Pharmacol       Date:  1998-10       Impact factor: 4.335

Review 3.  Clinical pharmacokinetics 1990.

Authors:  G R Matzke; W L St Peter
Journal:  Clin Pharmacokinet       Date:  1990-01       Impact factor: 6.447

4.  Do we need full compliance data for population pharmacokinetic analysis?

Authors:  P Girard; L B Sheiner; H Kastrissios; T F Blaschke
Journal:  J Pharmacokinet Biopharm       Date:  1996-06

5.  A comparison of a Bayesian population method with two methods as implemented in commercially available software.

Authors:  J E Bennett; J C Wakefield
Journal:  J Pharmacokinet Biopharm       Date:  1996-08

6.  The population pharmacokinetics of theophylline in neonates and young infants.

Authors:  E S Moore; R G Faix; R C Banagale; T H Grasela
Journal:  J Pharmacokinet Biopharm       Date:  1989-02

Review 7.  Pharmacokinetic drug interactions between digoxin and antiarrhythmic agents and calcium channel blocking agents: an appraisal of study methodology.

Authors:  E M Antman; J M Arnold; P L Friedman; T W Smith
Journal:  Cardiovasc Drugs Ther       Date:  1987-08       Impact factor: 3.727

8.  Effect of misspecification of the absorption process on subsequent parameter estimation in population analysis.

Authors:  J R Wade; A W Kelman; C A Howie; B Whiting
Journal:  J Pharmacokinet Biopharm       Date:  1993-04

9.  Nonparametric approach to population pharmacokinetics in oncology patients receiving aminoglycoside therapy.

Authors:  J F Inciardi; K K Batra
Journal:  Antimicrob Agents Chemother       Date:  1993-05       Impact factor: 5.191

10.  Development of a population pharmacokinetic database for tianeptine.

Authors:  T H Grasela; J B Fiedler-Kelly; C Salvadori; C Marey; R Jochemsen
Journal:  Eur J Clin Pharmacol       Date:  1993       Impact factor: 2.953

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