Literature DB >> 16353906

A guide for reporting the results of population pharmacokinetic analyses: a Swedish perspective.

Janet R Wade1, Monica Edholm, Tomas Salmonson.   

Abstract

Population pharmacokinetic analyses are frequently part of regulatory submissions and are mainly used to provide information on special populations (effects of age, renal impairment, etc) and drug-drug interactions. A varying standard of population analysis reports has been received at the Medical Products Agency in Sweden, some very good and some unassessable. In the latter case, it may be that it is a report of an inadequate analysis or may be a report of a perfectly acceptable analysis, but too little detail has been provided in the report for the conclusions reached to be properly assessed. A sufficient level of detail must be present in these reports in order for them to be assessable and to allow the conclusions reached to be incorporated into the summary of product characteristics. The report should specify the goal(s) of the analysis, describe in detail the origin and nature of the data, clearly describe the model-building process, include a range of goodness of fit (GOF) plots to support decisions made during the model-building process, and demonstrate that the final model is a good description of the data. The use of color in GOF plots is encouraged so that key features are easily visible. Covariate effects in the final model should be clearly presented and their clinical relevance discussed. In the case of many covariates in the final model, it may be useful to perform some simulations to illustrate the effect of various covariate combinations for a series of different "typical" subjects.

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Year:  2005        PMID: 16353906      PMCID: PMC2750982          DOI: 10.1208/aapsj070245

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  2 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.  Power, selection bias and predictive performance of the Population Pharmacokinetic Covariate Model.

Authors:  Jakob Ribbing; E Niclas Jonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-04       Impact factor: 2.745

  2 in total
  18 in total

Review 1.  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

Review 2.  Covariate pharmacokinetic model building in oncology and its potential clinical relevance.

Authors:  Markus Joerger
Journal:  AAPS J       Date:  2012-01-25       Impact factor: 4.009

Review 3.  Are population pharmacokinetic and/or pharmacodynamic models adequately evaluated? A survey of the literature from 2002 to 2004.

Authors:  Karl Brendel; Céline Dartois; Emmanuelle Comets; Annabelle Lemenuel-Diot; Christian Laveille; Brigitte Tranchand; Pascal Girard; Céline M Laffont; France Mentré
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

4.  Non-Bayesian knowledge propagation using model-based analysis of data from multiple clinical studies.

Authors:  Jakob Ribbing; Andrew C Hooker; E Niclas Jonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-11-08       Impact factor: 2.745

Review 5.  Overview of model-building strategies in population PK/PD analyses: 2002-2004 literature survey.

Authors:  C Dartois; K Brendel; E Comets; C M Laffont; C Laveille; B Tranchand; F Mentré; A Lemenuel-Diot; P Girard
Journal:  Br J Clin Pharmacol       Date:  2007-08-15       Impact factor: 4.335

6.  Reporting a population pharmacokinetic-pharmacodynamic study: a journal's perspective.

Authors:  Kris M Jamsen; Sarah C McLeay; Michael A Barras; Bruce Green
Journal:  Clin Pharmacokinet       Date:  2014-02       Impact factor: 6.447

7.  Evaluation of different tests based on observations for external model evaluation of population analyses.

Authors:  Karl Brendel; Emmanuelle Comets; Céline Laffont; France Mentré
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-12-23       Impact factor: 2.745

8.  Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions.

Authors:  Radojka M Savic; Mats O Karlsson
Journal:  AAPS J       Date:  2009-08-01       Impact factor: 4.009

Review 9.  Reproducible pharmacokinetics.

Authors:  John P A Ioannidis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-04-19       Impact factor: 2.745

Review 10.  Animal Pharmacokinetic/Pharmacodynamic Studies (APPS) Reporting Guidelines.

Authors:  Jasbir Singh; Fawzy Elbarbry; Ke Lan; Tomasz Grabowski
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2018-10       Impact factor: 2.441

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