Literature DB >> 17191947

Development and application of physiologically based pharmacokinetic-modeling tools to support drug discovery.

Christian Lüpfert1, Andreas Reichel.   

Abstract

Physiologically based pharmacokinetic (PBPK) modeling integrates physicochemical (PC) and in vitro pharmacokinetic (PK) data using a mechanistic framework of principal ADME (absorption, distribution, metabolism, and excretion) processes into a physiologically based whole-body model. Absorption, distribution, and clearance are modeled by combining compound-specific PC and PK properties with physiological processes. Thereby, isolated in vitro data can be upgraded by means of predicting full concentration-time profiles prior to animal experiments. The integrative process of PBPK modeling leads to a better understanding of the specific ADME processes driving the PK behavior in vivo, and has the power to rationally select experiments for a more focussed PK project support. This article presents a generic disposition model based on tissue-composition-based distribution and directly scaled hepatic clearance. This model can be used in drug discovery to identify the critical PK issues of compound classes and to rationally guide the optimization path of the compounds toward a viable development candidate. Starting with a generic PBPK model, which is empirically based on the most common PK processes, the model will be gradually tailored to the specifics of drug candidates as more and more experimental data become available. This will lead to a growing understanding of the 'drug in the making', allowing a range of predictions to be made for various purposes and conditions. The stage is set for a wide penetration of PK modeling and simulations to form an intrinsic part of a project starting from lead discovery, to lead optimization and candidate selection, to preclinical profiling and clinical trials.

Mesh:

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Year:  2005        PMID: 17191947     DOI: 10.1002/cbdv.200590119

Source DB:  PubMed          Journal:  Chem Biodivers        ISSN: 1612-1872            Impact factor:   2.408


  11 in total

1.  Lumping of physiologically-based pharmacokinetic models and a mechanistic derivation of classical compartmental models.

Authors:  Sabine Pilari; Wilhelm Huisinga
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-07-27       Impact factor: 2.745

2.  Physiologically based pharmacokinetic modelling: a sub-compartmentalized model of tissue distribution.

Authors:  Max von Kleist; Wilhelm Huisinga
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-09-25       Impact factor: 2.745

3.  Evaluation of a generic physiologically based pharmacokinetic model for lineshape analysis.

Authors:  Sheila Annie Peters
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

4.  A physiologically based in silico kinetic model predicting plasma cholesterol concentrations in humans.

Authors:  Niek C A van de Pas; Ruud A Woutersen; Ben van Ommen; Ivonne M C M Rietjens; Albert A de Graaf
Journal:  J Lipid Res       Date:  2012-09-29       Impact factor: 5.922

5.  A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways.

Authors:  André Dallmann; Ibrahim Ince; Katrin Coboeken; Thomas Eissing; Georg Hempel
Journal:  Clin Pharmacokinet       Date:  2018-06       Impact factor: 6.447

6.  Risk assessment in extrapolation of pharmacokinetics from preclinical data to humans.

Authors:  Zvi Teitelbaum; Thierry Lave; Jan Freijer; Adam F Cohen
Journal:  Clin Pharmacokinet       Date:  2010-09       Impact factor: 6.447

7.  Early identification of drug-induced impairment of gastric emptying through physiologically based pharmacokinetic (PBPK) simulation of plasma concentration-time profiles in rat.

Authors:  Sheila Annie Peters; Leif Hultin
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-10-26       Impact factor: 2.745

8.  Identification of intestinal loss of a drug through physiologically based pharmacokinetic simulation of plasma concentration-time profiles.

Authors:  Sheila Annie Peters
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

9.  Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis.

Authors:  Andrea N Edginton; Stefan Willmann
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

10.  Use of physiologically based biokinetic (PBBK) modeling to study estragole bioactivation and detoxification in humans as compared with male rats.

Authors:  Ans Punt; Alicia Paini; Marelle G Boersma; Andreas P Freidig; Thierry Delatour; Gabriele Scholz; Benoît Schilter; Peter J van Bladeren; Ivonne M C M Rietjens
Journal:  Toxicol Sci       Date:  2009-05-15       Impact factor: 4.849

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