Literature DB >> 12559691

Utility of physiologically based pharmacokinetic models to drug development and rational drug discovery candidate selection.

Frank-Peter Theil1, Theodor W Guentert, Sami Haddad, Patrick Poulin.   

Abstract

The present paper proposes a modeling and simulation strategy for the prediction of pharmacokinetics (PK) of drug candidates by using currently available in silico and in vitro based prediction tools for absorption, distribution, metabolism and excretion (ADME). These methods can be used to estimate specific ADME parameters (such as rate and extent of absorption into portal vein, volume of distribution, metabolic clearance in the liver). They can also be part of a physiologically based pharmacokinetic (PBPK) model to simulate concentration-time profiles in tissues and plasma resulting from the overall PK after intravenous or oral administration. Since the ADME prediction tools are built only on commonly generated in silico and in vitro data, they can be applied already in early drug discovery, prior to any in vivo study. With the suggested methodology, the following advantages of the mechanistic PBPK modeling framework can now be utilized to explore potential clinical candidates already in drug discovery: (i) prediction of plasma (blood) and tissue PK of drug candidates prior to in vivo experiments, (ii) supporting a better mechanistic understanding of PK properties, as well as helping the development of more rationale PK-PD relationships from tissue kinetic data predicted, and hence facilitating a more rational decision during clinical candidate selection, and (iii) the extrapolation across species, routes of administration and dose levels.

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Year:  2003        PMID: 12559691     DOI: 10.1016/s0378-4274(02)00374-0

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  36 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.  Model-based drug development: the road to quantitative pharmacology.

Authors:  Liping Zhang; Vikram Sinha; S Thomas Forgue; Sophie Callies; Lan Ni; Richard Peck; Sandra R B Allerheiligen
Journal:  J Pharmacokinet Pharmacodyn       Date:  2006-06-13       Impact factor: 2.745

3.  A novel strategy for physiologically based predictions of human pharmacokinetics.

Authors:  Hannah M Jones; Neil Parrott; Karin Jorga; Thierry Lavé
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

4.  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

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

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

6.  Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes.

Authors:  Marylore Chenel; François Bouzom; Leon Aarons; Kayode Ogungbenro
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-01-07       Impact factor: 2.745

7.  Physiologically based pharmacokinetic modeling of drug disposition in rat and human: a fuzzy arithmetic approach.

Authors:  Kok-Yong Seng; Ivan Nestorov; Paolo Vicini
Journal:  Pharm Res       Date:  2008-03-25       Impact factor: 4.200

Review 8.  Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels.

Authors:  Kyoung Ah Min; Xinyuan Zhang; Jing-yu Yu; Gus R Rosania
Journal:  Biopharm Drug Dispos       Date:  2013-12-10       Impact factor: 1.627

9.  Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.

Authors:  Sven Björkman
Journal:  J Pharmacokinet Pharmacodyn       Date:  2003-08       Impact factor: 2.745

10.  Incorporation of ABCB1-mediated transport into a physiologically-based pharmacokinetic model of docetaxel in mice.

Authors:  Susan F Hudachek; Daniel L Gustafson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-04-25       Impact factor: 2.745

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