Literature DB >> 20830811

Comparative assessment of empirical and physiological approaches on predicting human clearances.

Sekihiro Tamaki1, Hiroshi Komura, Motohiro Kogayu, Shizuo Yamada.   

Abstract

The empirical and physiological predictive approaches to human clearance were evaluated using preclinical in vitro and in vivo data of various datasets to establish a methodology for the prediction of clearance. Among the examined empirical approaches, an allometric scaling method with the rule of exponent (ROE), based on the exponent in simple allometry, provided better prediction. The effect of lipophilicity (clog P) and clearance on the predictivity was investigated using the ROE method. High predictivity was found for a low lipophilic compound with clog P < 0 and for a compound with moderate or high clearance. As a physiological approach, the in vitro-in vivo scaling method using metabolic stability in liver microsomes and hepatocytes was evaluated, and the predictivity taking the plasma protein binding and the nonspecific binding in incubation into consideration was compared with the ROE method. The two methods appeared to show comparable predictivity, although the in vitro-in vivo scaling was conducted under limited conditions like the use of physiological scaling factor and lipophilicity-derived nonspecific binding data. The ROE method could be an alternative predictor of the human clearance of compounds to which a physiological approach cannot be applied, in addition to low lipophilic compounds, with acceptable accuracy.
Copyright © 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 20830811     DOI: 10.1002/jps.22321

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


  2 in total

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Authors:  Zhenhua Huang; Heran Li; Qian Zhang; Xiaojuan Tan; Fangzheng Lu; Hongzhuo Liu; Sanming Li
Journal:  Drug Des Devel Ther       Date:  2015-08-05       Impact factor: 4.162

2.  Pre-Clinical Pharmacokinetics, Tissue Distribution and Physicochemical Studies of CLBQ14, a Novel Methionine Aminopeptidase Inhibitor for the Treatment of Infectious Diseases.

Authors:  Oscar Ekpenyong; Xiuqing Gao; Jing Ma; Candace Cooper; Linh Nguyen; Omonike A Olaleye; Dong Liang; Huan Xie
Journal:  Drug Des Devel Ther       Date:  2020-03-30       Impact factor: 4.162

  2 in total

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