Higher Throughput Bioanalysis by Automation of a Protein Precipitation Assay Using a 96-Well Format with Detection by LC−MS/MS

Generic methodology for the automated preparation and analysis of drug levels in plasma samples within a drug discovery environment was achieved through the redesign of a protein precipitation assay to a microtiter (96−well) plate format and the application of robotic liquid handling for performance...

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Bibliographic Details
Published inAnalytical chemistry (Washington) Vol. 72; no. 5; pp. 979 - 984
Main Authors Watt, Alan P, Morrison, Denise, Locker, Karen L, Evans, David C
Format Journal Article
LanguageEnglish
Published Washington, DC American Chemical Society 01.03.2000
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Summary:Generic methodology for the automated preparation and analysis of drug levels in plasma samples within a drug discovery environment was achieved through the redesign of a protein precipitation assay to a microtiter (96−well) plate format and the application of robotic liquid handling for performance of all transfer and pipetting steps. Validation studies revealed that the application of robotics to sample preparation, in general, maintained the analytical accuracy and precision compared with preparing samples manually. The use of rapid gradient LC-MS/MS for analysis coupled with flow diversion of the solvent front allowed the introduction of protein-precipitated samples into the mass spectrometer without the necessity for source cleaning. The problem inherent in automatically pipetting plasma, caused by fibrinogen clots, was overcome by storing samples at −80 °C and thus precluding clot formation. The resulting methodology allowed sample preparation for a 96-well plate designed to accommodate 54 unknowns, duplicate 12-point calibration curves, and 6 sets of quality controls at three levels in approximately 2 h. This approach allowed an increase in throughput of sample preparation and analysis to >400 samples per day per LC-MS/MS instrument with minimal manual intervention. Overall, substantial time savings were realized, demonstrating that automation is an increasingly essential tool in a drug discovery bioanalytical environment.
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ISSN:0003-2700
1520-6882
DOI:10.1021/ac9906633