Literature DB >> 6745081

Population pharmacokinetic data and parameter estimation based on their first two statistical moments.

S L Beal.   

Abstract

A statistical model is set forth that can be taken as a very general description of most data sets that arise from population pharmacokinetic studies. A (nontraditional) method for estimating the parameters of the model--called the NONMEM method in previously published papers--is described. This method involves a linearization of the model. An investigation of the effect of this linearization is reported. This investigation is an empirical one, based on the simulation of data from special cases of the model and the application of a few different estimation methods to these data. From the limited evidence in this investigation it appears that the linearization per se does not significantly adversely affect the estimates.

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Year:  1984        PMID: 6745081     DOI: 10.3109/03602538409015064

Source DB:  PubMed          Journal:  Drug Metab Rev        ISSN: 0360-2532            Impact factor:   4.518


  30 in total

1.  Assessment of actual significance levels for covariate effects in NONMEM.

Authors:  U Wählby; E N Jonsson; M O Karlsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-06       Impact factor: 2.745

2.  Software for population pharmacokinetics and pharmacodynamics.

Authors:  L Aarons
Journal:  Clin Pharmacokinet       Date:  1999-04       Impact factor: 6.447

3.  Assessment of type I error rates for the statistical sub-model in NONMEM.

Authors:  Ulrika Wählby; M René Bouw; E Niclas Jonsson; Mats O Karlsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2002-06       Impact factor: 2.745

4.  Smooth nonparametric maximum likelihood estimation for population pharmacokinetics, with application to quinidine.

Authors:  M Davidian; A R Gallant
Journal:  J Pharmacokinet Biopharm       Date:  1992-10

5.  Evaluation of type I error rates when modeling ordered categorical data in NONMEM.

Authors:  Ulrika Wählby; Katalin Matolcsi; Mats O Karlsson; E Niclas Jonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-02       Impact factor: 2.745

6.  Response to "An evaluation of point and interval estimates in population pharmacokinetics using NONMEM analysis" by White et al.

Authors:  K F Phillips
Journal:  J Pharmacokinet Biopharm       Date:  1992-08

Review 7.  Mean time parameters in pharmacokinetics. Definition, computation and clinical implications (Part II).

Authors:  P Veng-Pedersen
Journal:  Clin Pharmacokinet       Date:  1989-12       Impact factor: 6.447

8.  Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.

Authors:  Aida Bustad; Dimiter Terziivanov; Robert Leary; Ruediger Port; Alan Schumitzky; Roger Jelliffe
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

9.  Twitch potentiation influences the time course of twitch depression in muscle relaxant studies: a pharmacokinetic-pharmacodynamic explanation.

Authors:  Douglas J Eleveld; Johannes H Proost; J Mark K H Wierda
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-10-12       Impact factor: 2.745

10.  Assessment of pharmacokinetic interaction between rilotumumab and epirubicin, cisplatin and capecitabine (ECX) in a Phase 3 study in gastric cancer.

Authors:  Yilong Zhang; Mita Kuchimanchi; Min Zhu; Sameer Doshi; Tien Hoang; Sreeneeranj Kasichayanula
Journal:  Br J Clin Pharmacol       Date:  2016-12-13       Impact factor: 4.335

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