Literature DB >> 9145383

Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs.

T Lave1, S Dupin, C Schmitt, R C Chou, D Jaeck, P Coassolo.   

Abstract

In this study, we investigated rational and reliable methods of using animal data to predict in humans the clearance of drugs which are mainly eliminated through hepatic metabolism. For 10 extensively metabolized compounds, adjusting the in vivo clearance in the different animal species for the relative rates of metabolism in vitro dramatically improved the predictions of human clearance compared to the approach in which clearance is directly extrapolated using body weight. Using hepatocyte data to normalize the in vivo clearances led to lower median deviations between the observed and predicted clearances in man compared to the approach normalizing data with brain weight (30-40% vs 60-80%, respectively). In addition, the approach integrating in vitro data appeared to be superior with respect to the range of deviations: approximately 2-fold underestimation, in the worst case, was observed by using in vitro data, whereas normalizing data by brain weight led to up to 10-fold underestimation of clearance in man. In addition, the integration of in vitro data provides a more rational basis to predict the metabolic clearance in man and may be applicable to compounds undergoing phase I and phase II metabolism as well.

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Year:  1997        PMID: 9145383     DOI: 10.1021/js960440h

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  25 in total

Review 1.  Prediction of hepatic metabolic clearance: comparison and assessment of prediction models.

Authors:  J Zuegge; G Schneider; P Coassolo; T Lavé
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

2.  Allometric scaling of xenobiotic clearance: uncertainty versus universality.

Authors:  T M Hu; W L Hayton
Journal:  AAPS PharmSci       Date:  2001

3.  The use of in vitro metabolic stability for rapid selection of compounds in early discovery based on their expected hepatic extraction ratios.

Authors:  Yan Yi Lau; Gopal Krishna; Nathan P Yumibe; Diane E Grotz; Elpida Sapidou; Laura Norton; Inhou Chu; Cliff Chen; A D Soares; Chin-Chung Lin
Journal:  Pharm Res       Date:  2002-11       Impact factor: 4.200

Review 4.  Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations.

Authors:  T Lavé; P Coassolo; B Reigner
Journal:  Clin Pharmacokinet       Date:  1999-03       Impact factor: 6.447

Review 5.  Applications of human pharmacokinetic prediction in first-in-human dose estimation.

Authors:  Peng Zou; Yanke Yu; Nan Zheng; Yongsheng Yang; Hayley J Paholak; Lawrence X Yu; Duxin Sun
Journal:  AAPS J       Date:  2012-03-10       Impact factor: 4.009

6.  Metabolic assessment in liver microsomes by co-activating cytochrome P450s and UDP-glycosyltransferases.

Authors:  Z Yan; G W Caldwell
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2003 Jul-Sep       Impact factor: 2.441

7.  Comparison of the use of liver models for predicting drug clearance using in vitro kinetic data from hepatic microsomes and isolated hepatocytes.

Authors:  Kiyomi Ito; J Brian Houston
Journal:  Pharm Res       Date:  2004-05       Impact factor: 4.200

8.  A semiphysiologically based pharmacokinetic modeling approach to predict the dose-exposure relationship of an antiparasitic prodrug/active metabolite pair.

Authors:  Grace Zhixia Yan; Claudia N Generaux; Miyoung Yoon; Rachel B Goldsmith; Richard R Tidwell; James E Hall; Carol A Olson; Harvey J Clewell; Kim L R Brouwer; Mary F Paine
Journal:  Drug Metab Dispos       Date:  2011-09-27       Impact factor: 3.922

Review 9.  To scale or not to scale: the principles of dose extrapolation.

Authors:  Vijay Sharma; John H McNeill
Journal:  Br J Pharmacol       Date:  2009-06-05       Impact factor: 8.739

10.  Prediction of drug clearance in humans from laboratory animals based on body surface area.

Authors:  X D Liu; J Chen
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2001 Oct-Dec       Impact factor: 2.441

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