Automation of metabolic stability studies in microsomes, cytosol and plasma using a 215 Gilson liquid handler

Linget, Jean-Michel; Vignaud, Pierre du

doi:10.1016/s0731-7085(98)00238-6

Cited by 32 publications

(14 citation statements)

References 16 publications

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“…The concentration of the test compound reported in the literature for microsomal stability assays varies from 0.5 to 15 µM. 4,[6][7][8][11][12][13] Microsomal stability, based on percent remaining of parent, is dependent on the test concentration due to nonlinear kinetics. Higher test concentrations (e.g., 10 µM) produce results indicating apparently higher stability.…”

Section: Discussionmentioning

confidence: 99%

Optimization of a Higher Throughput Microsomal Stability Screening Assay for Profiling Drug Discovery Candidates

Di¹,

Kerns²,

Hong³

et al. 2003

SLAS Discovery

127

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Metabolic stability plays an important role in the success of drug candidates. First-pass metabolism is one of the major causes of poor oral bioavailability and short half-life. Traditionally, metabolic stability was evaluated at a later stage of drug discovery and required laborious manual manipulations. With the advance of high-throughput screening, combinatorial chemistry, and early profiling of drug-like properties, automated and rapid stability assays are needed to meet the increasing demand of throughput, speed, and reproducibility at earlier stages of drug discovery. The authors describe optimization of a simple, robust, high-throughput microsomal stability assay developed in a 96-well format. The assay consists of 2 automated components: robotic sample preparation for incubation and cleanup and rapid liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS) analysis to determine percent remaining of the parent compound. The reagent solutions and procedural steps were optimized for automation. Variables affecting assay results were investigated. The variability introduced by microsome preparations from different sources (various vendors and batches) was studied and indicates the need for careful control. Quality control and normalization of the stability results are critical when applying the screening data, generated at different times or research sites, to discovery projects. (Journal of Biomolecular Screening 2003:453-462)

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Section: Discussionmentioning

confidence: 99%

Optimization of a Higher Throughput Microsomal Stability Screening Assay for Profiling Drug Discovery Candidates

Di¹,

Kerns²,

Hong³

et al. 2003

SLAS Discovery

127

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show abstract

“…In vitro metabolic stability assays for drugs and drug candidates have been reported over the past 20 years (Houston, 1994;Linget and du Vignaud, 1999). These assays use microsomes, S9, and cytosol fractions from various species and have been extended to stability assessment in living hepatocytes (Obach et al, 1997;Niro et al, 2003;Ito and Houston, 2004).…”

Section: Introductionmentioning

confidence: 99%

An Automated High-Throughput Metabolic Stability Assay Using an Integrated High-Resolution Accurate Mass Method and Automated Data Analysis Software

Shah

Kerns

Nguyễn³

et al. 2016

Drug Metabolism and Disposition

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Advancement of in silico tools would be enabled by the availability of data for metabolic reaction rates and intrinsic clearance (CL int ) of a diverse compound structure data set by specific metabolic enzymes. Our goal is to measure CL int for a large set of compounds with each major human cytochrome P450 (P450) isozyme. To achieve our goal, it is of utmost importance to develop an automated, robust, sensitive, high-throughput metabolic stability assay that can efficiently handle a large volume of compound sets. The substrate depletion method [in vitro half-life (t 1/2 ) method] was chosen to determine CL int . The assay (384-well format) consisted of three parts: 1) a robotic system for incubation and sample cleanup; 2) two different integrated, ultraperformance liquid chromatography/mass spectrometry (UPLC/MS) platforms to determine the percent remaining of parent compound, and 3) an automated data analysis system. The CYP3A4 assay was evaluated using two long t 1/2 compounds, carbamazepine and antipyrine (t 1/2 > 30 minutes); one moderate t 1/2 compound, ketoconazole (10 < t 1/2 < 30 minutes); and two short t 1/2 compounds, loperamide and buspirone (t ½ < 10 minutes). Interday and intraday precision and accuracy of the assay were within acceptable range (∼12%) for the linear range observed. Using this assay, CYP3A4 CL int and t 1/2 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 P450 isozymes.

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“…Recently, Shou et al described a novel approach in a screening mode to simultaneously perform metabolite detection and quantitative metabolic stability determination [20]. At the same time, developing efficient and reliable sample incubation, analytical preparation, and data reporting systems for in vitro microsome studies has been reported, which accelerates this process [24][25][26][27][28]. In this report we describe a new automated method based on a custom-designed 96-well format incubator integrated with a Beckman Biomek FX liquid handling system.…”

Section: Introductionmentioning

confidence: 99%

High throughput metabolic stability screen for lead optimization in drug discovery

Tong

Zheng

et al. 2006

Journal of Chromatography B

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Automation of metabolic stability studies in microsomes, cytosol and plasma using a 215 Gilson liquid handler

Cited by 32 publications

References 16 publications

Optimization of a Higher Throughput Microsomal Stability Screening Assay for Profiling Drug Discovery Candidates

Optimization of a Higher Throughput Microsomal Stability Screening Assay for Profiling Drug Discovery Candidates

An Automated High-Throughput Metabolic Stability Assay Using an Integrated High-Resolution Accurate Mass Method and Automated Data Analysis Software

High throughput metabolic stability screen for lead optimization in drug discovery

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