Literature DB >> 31004315

Reproducible pharmacokinetics.

John P A Ioannidis1.   

Abstract

Reproducibility is a highly desired feature of scientific investigation in general, and it has special connotations for research in pharmacokinetics, a vibrant field with over 500,000 publications to-date. It is important to be able to differentiate between genuine heterogeneity in pharmacokinetic parameters from heterogeneity that is due to errors and biases. This overview discusses efforts and opportunities to diminish the latter type of undesirable heterogeneity. Several reporting and research guidance documents and standards have been proposed for pharmacokinetic studies, but their adoption is still rather limited. Quality problems in the methods used and model evaluations have been examined in some empirical studies of the literature. Standardization of statistical and laboratory tools and procedures can be improved in the field. Only a small fraction of pharmacokinetic studies become pre-registered and only 9995 such studies have been registered in ClinicalTrials.gov as of August 2018. It is likely that most pharmacokinetic studies remain unpublished. Publication bias affecting the results and inferences has been documented in case studies, but its exact extent is unknown for the field at-large. The use of meta-analyses in the field is still limited. Availability of raw data, detailed protocols, software and codes is hopefully improving with multiple ongoing initiatives. Several research practices can contribute to greater transparency and reproducibility for pharmacokinetic investigations.

Keywords:  Bias; Data sharing; Heterogeneity; Pharmacokinetics; Reproducibility; Research practices; Trial registration

Mesh:

Year:  2019        PMID: 31004315     DOI: 10.1007/s10928-019-09621-y

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  46 in total

Review 1.  Publication bias on clinical studies of pharmacokinetic interactions between felodipine and grapefruit juice.

Authors:  Y Uesawa; T Takeuchi; K Mohri
Journal:  Pharmazie       Date:  2010-05       Impact factor: 1.267

Review 2.  A guide for reporting the results of population pharmacokinetic analyses: a Swedish perspective.

Authors:  Janet R Wade; Monica Edholm; Tomas Salmonson
Journal:  AAPS J       Date:  2005-10-05       Impact factor: 4.009

3.  PsN-Toolkit--a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM.

Authors:  Lars Lindbom; Pontus Pihlgren; E Niclas Jonsson; Niclas Jonsson
Journal:  Comput Methods Programs Biomed       Date:  2005-09       Impact factor: 5.428

Review 4.  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

Review 5.  Advanced pharmacokinetic models based on organ clearance, circulatory, and fractal concepts.

Authors:  K Sandy Pang; Michael Weiss; Panos Macheras
Journal:  AAPS J       Date:  2007-06-29       Impact factor: 4.009

6.  The appropriateness of asymmetry tests for publication bias in meta-analyses: a large survey.

Authors:  John P A Ioannidis; Thomas A Trikalinos
Journal:  CMAJ       Date:  2007-04-10       Impact factor: 8.262

Review 7.  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

Review 8.  Data sharing for pharmacokinetic studies.

Authors:  Brian J Anderson; Alan F Merry
Journal:  Paediatr Anaesth       Date:  2009-06-25       Impact factor: 2.556

9.  Determining the reporting quality of RCTs in clinical pharmacology.

Authors:  Edward Mills; Yoon K Loke; Ping Wu; Victor M Montori; Daniel Perri; David Moher; Gordon Guyatt
Journal:  Br J Clin Pharmacol       Date:  2004-07       Impact factor: 4.335

Review 10.  Design, analysis, and presentation of crossover trials.

Authors:  Edward J Mills; An-Wen Chan; Ping Wu; Andy Vail; Gordon H Guyatt; Douglas G Altman
Journal:  Trials       Date:  2009-04-30       Impact factor: 2.279

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  2 in total

1.  PK-DB: pharmacokinetics database for individualized and stratified computational modeling.

Authors:  Jan Grzegorzewski; Janosch Brandhorst; Kathleen Green; Dimitra Eleftheriadou; Yannick Duport; Florian Barthorscht; Adrian Köller; Danny Yu Jia Ke; Sara De Angelis; Matthias König
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

Review 2.  Pharmacokinetics of Caffeine: A Systematic Analysis of Reported Data for Application in Metabolic Phenotyping and Liver Function Testing.

Authors:  Jan Grzegorzewski; Florian Bartsch; Adrian Köller; Matthias König
Journal:  Front Pharmacol       Date:  2022-02-25       Impact factor: 5.810

  2 in total

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