Literature DB >> 22139680

Approaches for predicting human pharmacokinetics using interspecies pharmacokinetic scaling.

Hee Eun Kang1, Myung Gull Lee.   

Abstract

Reliably predicting pharmacokinetic behavior in humans from preclinical data is an important aspect of drug development. The most widely used technique in this regard is allometric scaling. In this review, various approaches developed for predicting pharmacokinetic parameters in humans using interspecies scaling are introduced and discussed. Methods to predict plasma concentration-time profiles in humans after intravenous and oral administration are also reviewed. The reliable prediction of human pharmacokinetics with regard to investigational drugs is aimed, ultimately, at selecting the first in-human dose with which to begin clinical studies. Approaches for the selection of the first in-human dose are also reviewed. Although there have been many trials to compare and optimize interspecies scaling methods, no firm conclusions have been reached. Because interspecies scaling methods are still highly empirical, further effort is needed to improve the reliability of predicting human pharmacokinetics by interspecies scaling.

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Year:  2011        PMID: 22139680     DOI: 10.1007/s12272-011-1101-4

Source DB:  PubMed          Journal:  Arch Pharm Res        ISSN: 0253-6269            Impact factor:   4.946


  3 in total

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Authors:  Y Zhang; S Doshi; M Zhu
Journal:  Br J Clin Pharmacol       Date:  2015-05-26       Impact factor: 4.335

Review 2.  Prediction of pharmacokinetics and drug-drug interactions when hepatic transporters are involved.

Authors:  Rui Li; Hugh A Barton; Manthena V Varma
Journal:  Clin Pharmacokinet       Date:  2014-08       Impact factor: 6.447

3.  Pharmacokinetics of β-Lactam Antibiotics: Clues from the Past To Help Discover Long-Acting Oral Drugs in the Future.

Authors:  Paul W Smith; Fabio Zuccotto; Robert H Bates; Maria Santos Martinez-Martinez; Kevin D Read; Caroline Peet; Ola Epemolu
Journal:  ACS Infect Dis       Date:  2018-09-10       Impact factor: 5.084

  3 in total

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