Literature DB >> 10320948

Software for population pharmacokinetics and pharmacodynamics.

L Aarons1.   

Abstract

Pharmacokinetic-pharmacodynamic modelling is being used increasingly as a tool in drug development because often in phase III clinical trials only sparse data are available for analysis and so a nonlinear mixed effects modelling approach has to be adopted. Specialist data analytical techniques and software are required to analyse such data. This article reviews some of the software currently available for performing nonlinear mixed effects modelling. A questionnaire was devised and sent to a number of software producers and the findings are presented and discussed in this paper. The programs could be grouped into 3 main categories: parametric and nonparametric maximum likelihood and Bayesian. It was apparent from the questionnaire that software development for population data analysis is a very active area of investigation. The implementation of methodologies varied widely between the packages: some were self-contained programs, whereas others were written within another application, usually a statistical package. They also varied with respect to their ease of use and level of support offered by the software producers. Although robustness and reliability are important concerns, they were not addressed in the present review. Most of the programs surveyed are in continual development.

Mesh:

Year:  1999        PMID: 10320948     DOI: 10.2165/00003088-199936040-00001

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  9 in total

1.  Nonlinear mixed effects models for repeated measures data.

Authors:  M L Lindstrom; D M Bates
Journal:  Biometrics       Date:  1990-09       Impact factor: 2.571

2.  Mixed-effects nonlinear regression for unbalanced repeated measures.

Authors:  E F Vonesh; R L Carter
Journal:  Biometrics       Date:  1992-03       Impact factor: 2.571

3.  Population pharmacokinetics: theory and practice.

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

4.  Comparison of population pharmacokinetic modeling methods using simulated data: results from the Population Modeling Workgroup.

Authors:  D J Roe
Journal:  Stat Med       Date:  1997-06-15       Impact factor: 2.373

5.  Estimation of population characteristics of pharmacokinetic parameters from routine clinical data.

Authors:  L B Sheiner; B Rosenberg; V V Marathe
Journal:  J Pharmacokinet Biopharm       Date:  1977-10

6.  Pharmacokinetics of quinidine in male patients. A population analysis.

Authors:  C N Verme; T M Ludden; W A Clementi; S C Harris
Journal:  Clin Pharmacokinet       Date:  1992-06       Impact factor: 6.447

7.  A two-step iterative algorithm for estimation in nonlinear mixed-effect models with an evaluation in population pharmacokinetics.

Authors:  F Mentré; R Gomeni
Journal:  J Biopharm Stat       Date:  1995-07       Impact factor: 1.051

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

Authors:  S L Beal
Journal:  Drug Metab Rev       Date:  1984       Impact factor: 4.518

9.  Population approaches in drug development. Report on an expert meeting to discuss population pharmacokinetic/pharmacodynamic software.

Authors:  L Aarons; L P Balant; F Mentré; P L Morselli; M Rowland; J L Steimer; S Vozeh
Journal:  Eur J Clin Pharmacol       Date:  1994       Impact factor: 2.953

  9 in total
  17 in total

1.  Impact of pharmacokinetic-pharmacodynamic model linearization on the accuracy of population information matrix and optimal design.

Authors:  Y Merlé; M Tod
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-08       Impact factor: 2.745

2.  Bayesian analysis of population PK/PD models: general concepts and software.

Authors:  David J Lunn; Nicky Best; Andrew Thomas; Jon Wakefield; David Spiegelhalter
Journal:  J Pharmacokinet Pharmacodyn       Date:  2002-06       Impact factor: 2.745

3.  Optimization of individual and population designs using Splus.

Authors:  Sylvie Retout; France Mentré
Journal:  J Pharmacokinet Pharmacodyn       Date:  2003-12       Impact factor: 2.745

Review 4.  Interpreting population pharmacokinetic-pharmacodynamic analyses - a clinical viewpoint.

Authors:  Stephen B Duffull; Daniel F B Wright; Helen R Winter
Journal:  Br J Clin Pharmacol       Date:  2011-06       Impact factor: 4.335

5.  Prediction discrepancies for the evaluation of nonlinear mixed-effects models.

Authors:  France Mentré; Sylvie Escolano
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-11-13       Impact factor: 2.745

Review 6.  A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples.

Authors:  Robert J Bauer; Serge Guzy; Chee Ng
Journal:  AAPS J       Date:  2007-03-02       Impact factor: 4.009

7.  Pharmacokinetics and toxicity of idarubicin in the rat.

Authors:  O Kuhlmann; S Hofmann; M Weiss
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2001 Oct-Dec       Impact factor: 2.441

8.  How many subjects are necessary for population pharmacokinetic experiments? Confidence interval approach.

Authors:  Kayode Ogungbenro; Leon Aarons
Journal:  Eur J Clin Pharmacol       Date:  2008-05-16       Impact factor: 2.953

Review 9.  The role of population PK-PD modelling in paediatric clinical research.

Authors:  Roosmarijn F W De Cock; Chiara Piana; Elke H J Krekels; Meindert Danhof; Karel Allegaert; Catherijne A J Knibbe
Journal:  Eur J Clin Pharmacol       Date:  2010-03-26       Impact factor: 2.953

Review 10.  Fundamentals of Population Pharmacokinetic Modelling : Modelling and Software.

Authors:  Tony K L Kiang; Catherine M T Sherwin; Michael G Spigarelli; Mary H H Ensom
Journal:  Clin Pharmacokinet       Date:  2012-08       Impact factor: 6.447

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