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An optimized automated assay for determination of metabolic stability using hepatocytes: assay validation, variance component analysis, and in vivo relevance.

Magazine article
Authors Lykke Jacobson
Brian Middleton
Jan Holmgren
Stefan Eirefelt
Maria Fröjd
Anders Blomgren
Lena Gustavsson
Published in Assay and drug development technologies
Volume 5
Issue 3
Pages 403-15
ISSN 1540-658X
Publication year 2007
Published at Institute of Biomedicine, Department of Microbiology and Immunology
Pages 403-15
Language en
Links dx.doi.org/10.1089/adt.2007.059
Keywords Automation, Cryopreservation, Drug Design, Hepatocytes, metabolism, Humans, Metabolic Clearance Rate
Subject categories Microbiology in the medical area

Abstract

Screening of new chemical entities for metabolic stability using hepatocytes is routinely used in drug discovery. To enhance compound throughput, an optimized automated microassay for determination of intrinsic clearance was developed. Dulbecco's modified Eagle's medium, Hanks' balanced salt solution, and Leibovitz L-15 medium (L-15) were tested for their ability to maintain cell viability during incubation in 96-well plates. L-15 was found to keep pH within 0.1 units and maintain high viability during several hours of incubation. Moreover, two different thawing protocols for cryopreserved hepatocytes were compared. Protocol 2 resulted in a nearly 100% increase in post-thaw yield, whereas no difference was observed in cell viability. The microassay was validated using human cryopreserved hepatocytes and 19 reference compounds covering the most important phase I and II liver metabolizing enzymes ranging from low to medium and high clearance compounds. The day-to-day variation was determined, revealing an overall good precision of the assay. In vitro-in vivo correlations, for both fresh rat and cryopreserved human hepatocytes, were calculated. For 86% (human) and 77% (rat) of the compounds, calculated hepatic clearance was within twofold observed clearance in vivo. Using the validation data, variance component analysis was applied to determine within and between-experiment variability, enabling estimation of variation and detection limit for any combination of repeated experiments and replicate samples. Based on the precision desired, this provides a tool to select the most optimal and cost-effective assay approach for different compounds considering the actual phase in the drug discovery program.

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