Literature DB >> 14982153

Predicting human pharmacokinetics from preclinical data.

Italo Poggesi1.   

Abstract

Approaches used for the prediction of pharmacokinetics in relevant populations of human patients mostly rely on in vivo data from animals, using allometric scaling or time-invariant methods. The growth of in vitro and, more recently, in silico screens for evaluating pharmaceutical, pharmacokinetic and toxicity properties can also be used to predict complex in vivo behavior in humans. In most cases, careful and educated application of available approaches provides predictions of pharmacokinetic parameters within 2- or 3-fold of that observed. Attention should now be directed toward integrating information from different sources to increase the precision and accuracy of these pharmacokinetic predictions and to enable a better understanding of the processes underlying ADME behavior in humans.

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Year:  2004        PMID: 14982153

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  4 in total

1.  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

Review 2.  Integrated pharmacokinetics and pharmacodynamics in drug development.

Authors:  Jasper Dingemanse; Silke Appel-Dingemanse
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

3.  Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models.

Authors:  Norman C Ledonne; Kevin Rissolo; James Bulgarelli; Leonard Tini
Journal:  J Cheminform       Date:  2011-02-07       Impact factor: 5.514

Review 4.  Protein Binding in Translational Antimicrobial Development-Focus on Interspecies Differences.

Authors:  Hifza Ahmed; Felix Bergmann; Markus Zeitlinger
Journal:  Antibiotics (Basel)       Date:  2022-07-08
  4 in total

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