Literature DB >> 22228149

Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?

François Bouzom1, Kathryn Ball, Nathalie Perdaems, Bernard Walther.   

Abstract

In 2005, a survey compared a number of commercial PBPK software available at the time, mainly focusing on 'ready to use' modelling tools. Since then, these tools and software have been further developed and improved to allow modellers to perform WB-PBPK modelling including ADME processes at a high level of sophistication. This review presents a comparison of the features, values and limitations of both the 'ready to use' software and of the traditional user customizable software that are frequently used for the building and use of PBPK models, as well as the challenges associated with the various modelling approaches regarding their current and future use. PBPK models continue to be used more and more frequently during the drug development process since they represent a quantitative, physiologically realistic platform with which to simulate and predict the impact of various potential scenarios on the pharmacokinetics and pharmacodynamics of drugs. The 'ready to use' PBPK software has been a major factor in the increasing use of PBPK modelling in the pharmaceutical industry, opening up the PBPK approach to a broader range of users. The challenge is now to educate and to train scientists and modellers to ensure their appropriate understanding of the assumptions and the limitations linked both to the physiological framework of the 'virtual body' and to the scaling methodology from in vitro to in vivo (IVIVE).
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 22228149     DOI: 10.1002/bdd.1767

Source DB:  PubMed          Journal:  Biopharm Drug Dispos        ISSN: 0142-2782            Impact factor:   1.627


  20 in total

Review 1.  Physiologically based pharmacokinetic modelling of drug penetration across the blood-brain barrier--towards a mechanistic IVIVE-based approach.

Authors:  Kathryn Ball; François Bouzom; Jean-Michel Scherrmann; Bernard Walther; Xavier Declèves
Journal:  AAPS J       Date:  2013-06-20       Impact factor: 4.009

2.  Ethnic-specific in vitro-in vivo extrapolation and physiologically based pharmacokinetic approaches to predict cytochrome P450-mediated pharmacokinetics in the Chinese population: opportunities and challenges.

Authors:  Guo-Fu Li; Guo Yu; Hong-Xia Liu; Qing-Shan Zheng
Journal:  Clin Pharmacokinet       Date:  2014-02       Impact factor: 6.447

3.  A physiome interoperability roadmap for personalized drug development.

Authors:  Simon Thomas; Katherine Wolstencroft; Bernard de Bono; Peter J Hunter
Journal:  Interface Focus       Date:  2016-04-06       Impact factor: 3.906

4.  Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA.

Authors:  Marios Spanakis; Eleftherios Kontopodis; Sophie Van Cauter; Vangelis Sakkalis; Kostas Marias
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-09-19       Impact factor: 2.745

Review 5.  Challenges of using in vitro data for modeling P-glycoprotein efflux in the blood-brain barrier.

Authors:  Noora Sjöstedt; Hanna Kortejärvi; Heidi Kidron; Kati-Sisko Vellonen; Arto Urtti; Marjo Yliperttula
Journal:  Pharm Res       Date:  2014-01       Impact factor: 4.200

6.  Quantitative Systems Pharmacology: A Framework for Context.

Authors:  Ioannis P Androulakis
Journal:  Curr Pharmacol Rep       Date:  2016-04-08

7.  Characterization of Pharmacokinetics in the Göttingen Minipig with Reference Human Drugs: An In Vitro and In Vivo Approach.

Authors:  Floriane Lignet; Eva Sherbetjian; Nicole Kratochwil; Russell Jones; Claudia Suenderhauf; Michael B Otteneder; Thomas Singer; Neil Parrott
Journal:  Pharm Res       Date:  2016-07-28       Impact factor: 4.200

Review 8.  Mechanisms underlying food-drug interactions: inhibition of intestinal metabolism and transport.

Authors:  Christina S Won; Nicholas H Oberlies; Mary F Paine
Journal:  Pharmacol Ther       Date:  2012-08-04       Impact factor: 12.310

9.  Predicting topical drug clearance from the skin.

Authors:  Maria Alice Maciel Tabosa; Magdalena Hoppel; Annette L Bunge; Richard H Guy; M Begoña Delgado-Charro
Journal:  Drug Deliv Transl Res       Date:  2020-11-08       Impact factor: 4.617

Review 10.  Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

Authors:  C Anthony Hunt; Ryan C Kennedy; Sean H J Kim; Glen E P Ropella
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-06-04
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