Literature DB >> 28258394

Fundamentals of Population Pharmacokinetic Modelling : Modelling and Software.

Tony K L Kiang1, Catherine M T Sherwin2, Michael G Spigarelli2, Mary H H Ensom3.   

Abstract

Population pharmacokinetic modelling is widely used within the field of clinical pharmacology as it helps to define the sources and correlates of pharmacokinetic variability in target patient populations and their impact upon drug disposition. This review focuses on the fundamentals of population pharmacokinetic modelling and provides an overview of the commonly available software programs that perform these functions.This review attempts to define the common, fundamental aspects of population pharmacokinetic modelling through a discussion of the literature describing the techniques and placing them in the appropriate context. An overview of the most commonly available software programs is also provided.Population pharmacokinetic modelling is a powerful approach where sources and correlates of pharmacokinetic variability can be identified in a target patient population receiving a pharmacological agent. There is a need to further standardize and establish the best approaches in modelling so that any model created can be systematically evaluated and the results relied upon. Various nonlinear mixed-effects modelling methods, packaged in a variety of software programs, are available today. When selecting population pharmacokinetic software programs, the consumer needs to consider several factors, including usability (e.g. user interface, native platform, price, input and output specificity, as well as intuitiveness), content (e.g. algorithms and data output) and support (e.g. technical and clinical).

Entities:  

Year:  2012        PMID: 28258394     DOI: 10.1007/BF03261928

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


  18 in total

1.  Population pharmacokinetics/pharmacodynamics modeling: parametric and nonparametric methods.

Authors:  R Jelliffe; A Schumitzky; M Van Guilder
Journal:  Ther Drug Monit       Date:  2000-06       Impact factor: 3.681

Review 2.  A regulatory perspective on pharmacokinetic/pharmacodynamic modelling.

Authors:  S G Machado; R Miller; C Hu
Journal:  Stat Methods Med Res       Date:  1999-09       Impact factor: 3.021

Review 3.  Pharmacokinetic software for the health sciences: choosing the right package for teaching purposes.

Authors:  B G Charles; S B Duffull
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

Review 4.  Population pharmacokinetics II: estimation methods.

Authors:  Ene I Ette; Paul J Williams
Journal:  Ann Pharmacother       Date:  2004-09-14       Impact factor: 3.154

Review 5.  Population pharmacokinetics I: background, concepts, and models.

Authors:  Ene I Ette; Paul J Williams
Journal:  Ann Pharmacother       Date:  2004-08-24       Impact factor: 3.154

6.  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

Review 7.  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

Review 8.  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 9.  Some comments and suggestions concerning population pharmacokinetic modeling, especially of digoxin, and its relation to clinical therapy.

Authors:  Roger W Jelliffe
Journal:  Ther Drug Monit       Date:  2012-08       Impact factor: 3.681

Review 10.  Computers in pharmacokinetics. Choosing software for clinical decision making.

Authors:  D E Buffington; V Lampasona; M H Chandler
Journal:  Clin Pharmacokinet       Date:  1993-09       Impact factor: 6.447

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  19 in total

Review 1.  The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections.

Authors:  T Tängdén; V Ramos Martín; T W Felton; E I Nielsen; S Marchand; R J Brüggemann; J B Bulitta; M Bassetti; U Theuretzbacher; B T Tsuji; D W Wareham; L E Friberg; J J De Waele; V H Tam; Jason A Roberts
Journal:  Intensive Care Med       Date:  2017-04-13       Impact factor: 17.440

2.  Disease pharmacokinetic-pharmacodynamic modelling in acute intermittent porphyria to support the development of mRNA-based therapies.

Authors:  Zinnia P Parra-Guillen; Antonio Fontanellas; Lei Jiang; Daniel Jericó; Paolo Martini; Diego Vera-Yunca; Marjie Hard; Lin T Guey; Iñaki F Troconiz
Journal:  Br J Pharmacol       Date:  2020-04-14       Impact factor: 8.739

Review 3.  Enhancing population pharmacokinetic modeling efficiency and quality using an integrated workflow.

Authors:  Henning Schmidt; Andrijana Radivojevic
Journal:  J Pharmacokinet Pharmacodyn       Date:  2014-07-24       Impact factor: 2.745

4.  Population pharmacokinetics analysis of olanzapine for Chinese psychotic patients based on clinical therapeutic drug monitoring data with assistance of meta-analysis.

Authors:  Anyue Yin; Dewei Shang; Yuguan Wen; Liang Li; Tianyan Zhou; Wei Lu
Journal:  Eur J Clin Pharmacol       Date:  2016-04-27       Impact factor: 2.953

5.  The Impact of Smoking, Sex, Infection, and Comedication Administration on Oral Olanzapine: A Population Pharmacokinetic Model in Chinese Psychiatric Patients.

Authors:  Yan-Nan Zang; Fang Dong; An-Ning Li; Chuan-Yue Wang; Gui-Xin Guo; Qian Wang; Yan-Fang Zhang; Lei Zhang; Jose de Leon; Can-Jun Ruan
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2021-03-06       Impact factor: 2.441

6.  Population Pharmacokinetic Modeling of Olmesartan, the Active Metabolite of Olmesartan Medoxomil, in Patients with Hypertension.

Authors:  Devender Kodati; Harish Kaushik Kotakonda; Narsimhareddy Yellu
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-08       Impact factor: 2.441

7.  Population pharmacokinetics of valproic acid in adult Chinese patients with bipolar disorder.

Authors:  Yan-Nan Zang; Wei Guo; Meng-Xi Niu; Shuang Bao; Qian Wang; Yan Wang; Fang Dong; An-Ning Li; Can-Jun Ruan
Journal:  Eur J Clin Pharmacol       Date:  2021-12-02       Impact factor: 2.953

8.  Modeling and Simulation for Individualized Therapy of Amisulpride in Chinese Patients with Schizophrenia: Focus on Interindividual Variability, Therapeutic Reference Range and the Laboratory Alert Level.

Authors:  Shanqing Huang; Lu Li; Zhanzhang Wang; Tao Xiao; Xiaolin Li; Shujing Liu; Ming Zhang; Haoyang Lu; Yuguan Wen; Dewei Shang
Journal:  Drug Des Devel Ther       Date:  2021-09-14       Impact factor: 4.162

9.  Population Pharmacokinetics of Mycophenolic Acid: An Update.

Authors:  Tony K L Kiang; Mary H H Ensom
Journal:  Clin Pharmacokinet       Date:  2018-05       Impact factor: 6.447

10.  Population pharmacodynamic model for low molecular weight heparin nadroparin in morbidly obese and non-obese patients using anti-Xa levels as endpoint.

Authors:  Jeroen Diepstraten; Esther J H Janssen; Christian M Hackeng; Eric P A van Dongen; René J Wiezer; Bert van Ramshorst; Catherijne A J Knibbe
Journal:  Eur J Clin Pharmacol       Date:  2014-10-12       Impact factor: 2.953

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