RT Journal Article
SR Electronic
T1 An Automated High-Throughput Metabolic Stability Assay Using an Integrated High-Resolution Accurate Mass Method and Automated Data Analysis Software
JF Drug Metabolism and Disposition
JO Drug Metab Dispos
FD American Society for Pharmacology and Experimental Therapeutics
SP dmd.116.072017
DO 10.1124/dmd.116.072017
A1 Pranav Shah
A1 R. Scott Obach
A1 Dac-Trung Nguyen
A1 Edward Kerns
A1 Amy Q Wang
A1 Alexey Zakharov
A1 Anton Simeonov
A1 Cornelis E.C.A Hop
A1 John McKew
A1 Xin Xu
YR 2016
UL http://dmd.aspetjournals.org/content/early/2016/07/22/dmd.116.072017.abstract
AB Advancement of in silico tools would be enabled by availability of data for metabolic reaction rates and intrinsic clearance (CLint) of a diverse compound structure dataset by specific metabolic enzymes. Our goal is to measure CLint for a large set of compounds with each major human cytochrome P450 (CYP) isozyme. In order to achieve our goal, it is of utmost importance to develop an automated, robust, sensitive, high-throughput metabolic stability assay that can efficiently handle large volume of compound sets. The substrate depletion method (in vitro half-life (t1/2) method) was chosen to determine CLint. The assay (384-well format) consisted of three parts: a robotic system for incubation and sample clean up; two different, integrated, ultra-performance liquid chromatography/mass spectrometry (UPLC/MS) platforms to determine the percent remaining of parent compound, and an automated data analysis system. The CYP3A4 assay was evaluated using two long-t1/2 compounds, carbamazepine and antipyrine (t1/2>30 min), one moderate-t1/2 compound, ketoconazole (10<t1/2<30 min), and two short-t1/2 compounds, loperamide and buspirone (t1/2<10 min). Inter-day and intra-day precision and accuracy of the assay was within acceptable range (~12%) for the linear range observed. Using this assay, CYP3A4 CLint and t1/2 values for more than 3000 compounds were measured. This high-throughput, automated, and robust assay allows for rapid metabolic stability screening of large compound sets and enables advanced computational modeling for individual human CYP isozymes.