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AAPS J. 2009 Jun;11(2):262-76. doi: 10.1208/s12248-009-9103-6. Epub 2009 Apr 30.

Prediction of hepatic clearance in human from in vitro data for successful drug development.

Author information

1
Department of Preclinical Drug Metabolism and Pharmacokinetics, Tsukuba Research Institute, Banyu Pharmaceutical Co., Ltd., Okubo 3, Tsukuba, Ibaraki, 300-0810, Japan.

Abstract

The in vivo metabolic clearance in human has been successfully predicted by using in vitro data of metabolic stability in cryopreserved preparations of human hepatocytes. In the predictions by human hepatocytes, the systematic underpredictions of in vivo clearance have been commonly observed among different datasets. The regression-based scaling factor for the in vitro-to-in vivo extrapolation has mitigated discrepancy between in vitro prediction and in vivo observation. In addition to the elimination by metabolic degradation, the important roles of transporter-mediated hepatic uptake and canalicular excretion have been increasingly recognized as a rate-determining step in the hepatic clearance. It has been, therefore, proposed that the in vitro assessment should allow the evaluation of clearances for both transporter(s)-mediated uptake/excretion and metabolic degradation. This review first outlines the limited ability of subcellular fractions such as liver microsomes to predict hepatic clearance in vivo. It highlights the advantages of cryopreserved human hepatocytes as one of the versatile in vitro systems for the prediction of in vivo metabolic clearance in human at the early development stage. The following section discusses the mechanisms underlying the systematic underprediction of in vivo intrinsic clearance by hepatocytes. It leads to the proposal for the assessment of hepatic uptake clearance as one of the kinetically important determinants for accurate predictions of hepatic clearance in human. The judicious combination of advanced technologies and understandings for the drug disposition allows us to rationally optimize new chemical entities to the drug candidate with higher probability of success during the clinical development.

PMID:
19408130
PMCID:
PMC2691463
DOI:
10.1208/s12248-009-9103-6
[Indexed for MEDLINE]
Free PMC Article

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