Literature DB >> 27101423

Prediction of Metabolic Clearance for Low-Turnover Compounds Using Plated Hepatocytes with Enzyme Activity Correction.

Bennett Ma1, Roy Eisenhandler2, Yuhsin Kuo2, Paul Rearden2, Ying Li3, Peter J Manley4, Sheri Smith2, Karsten Menzel2.   

Abstract

BACKGROUND AND OBJECTIVES: Prediction of metabolic clearance has been a challenge for compounds exhibiting minimal turnover in typical in vitro stability experiments. The aim of the current study is to evaluate the utilization of plated human hepatocytes to predict intrinsic clearance of low-turnover compounds.
METHODS: The disappearance of test compounds was determined for up to 48 h while enzyme activities in plated hepatocytes were monitored concurrently in a complimentary experiment.
RESULTS: Consistent with literature reports, marked time-dependent loss of cytochrome P450 (CYP) enzyme activities was observed during the 48-h incubation period. To account for the loss of enzyme activities, a term "fraction of activity remaining" was calculated based on area-under-the-curve derived from the average rate of activity loss (k avg), and then applied as a correction factor for intrinsic clearance determination. Twelve compounds were selected in this study to cover phase I and phase II biotransformation pathways, with in vivo intrinsic clearance values, representing metabolic clearance only, ranging from 0.66 to 47 ml/min/kg. Determination of in vitro intrinsic clearance using three individual preparations of hepatocytes revealed a reasonably good agreement (generally within threefold) between the predicted and the observed metabolic clearance for all 12 compounds tested.
CONCLUSIONS: The current results indicated that plated hepatocytes can be utilized to provide clearance predictions for compounds with low-turnover in humans when corrected for the loss in enzyme activities.

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Year:  2017        PMID: 27101423     DOI: 10.1007/s13318-016-0336-3

Source DB:  PubMed          Journal:  Eur J Drug Metab Pharmacokinet        ISSN: 0378-7966            Impact factor:   2.441


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