Literature DB >> 23994235

Tissue-to-blood distribution coefficients in the rat: utility for estimation of the volume of distribution in man.

Paulo Paixão1, Natália Aniceto, Luís F Gouveia, José A G Morais.   

Abstract

A compilation of rat tissue-to-blood partition coefficient data obtained both in vitro and in vivo in thirteen different tissues for a total of 309 different drugs is presented. An evaluation of the relationship between several fundamental physicochemical molecular descriptors and these distribution parameters was made. In addition, the ability to predict the Human Volume of distribution by regression analysis and by a Physiologically-based approach was also tested. Results have shown different trends between the drug classes and tissues, consistent with earlier described relationships between physicochemical properties and pharmacokinetic behavior. It was also possible to conclude for the acceptable ability to predict the volume of distribution in Humans by both regression and mechanistic approaches, which suggests that this type of data represents a convenient tool to describe the drug distribution on a new drug development context. These observations and analyses, along with the large database of rat tissue distribution data, should enable future efforts aimed toward developing a full in silico quantitative structure-pharmacokinetic relationships and improving our understanding of the correlations between fundamental chemical characteristics and drug distribution.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Animal extrapolations; In vitro and in vivo methods for drug distribution; Tissue-to-blood partition coefficient; Trend analysis of distribution; Volume of distribution

Mesh:

Substances:

Year:  2013        PMID: 23994235     DOI: 10.1016/j.ejps.2013.08.020

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  2 in total

1.  Prediction of drug distribution in rat and humans using an artificial neural networks ensemble and a PBPK model.

Authors:  Paulo Paixão; Natália Aniceto; Luís F Gouveia; José A G Morais
Journal:  Pharm Res       Date:  2014-05-28       Impact factor: 4.200

2.  Linear Relationships between Partition Coefficients of Different Organic Compounds and Proteins in Aqueous Two-Phase Systems of Various Polymer and Ionic Compositions.

Authors:  Nuno R da Silva; Luisa A Ferreira; Pedro P Madeira; José A Teixeira; Vladimir N Uversky; Boris Y Zaslavsky
Journal:  Polymers (Basel)       Date:  2020-06-29       Impact factor: 4.329

  2 in total

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