Intelligent Automation of LC–MS Analysis for the Characterization of Compound Libraries

arrays, researchers have made efforts to address the various bottlenecks and limitations associated with LC–MS analytical methods. Mobile-phase gradient programming, on-line sample handling, fast separation technique development, and multispray interfaces have enabled the characterization of many samples in a relatively short period of time (5–8,15). In addition, the application of computer controls has substantially improved the efficiency of LC–MS analysis (16–19). Many of the tasks or analytical procedures that previously required an instrument operator have been replaced with computer software automation, including processes such as sample handling, signal acquisition, and data interpretation. Despite the developments in highthroughput analytical characterization techniques, achieving maximum throughput often requires compromises in an analytical method. Compound libraries typically comprise many analytes with diverse chemical properties. Developing an optimized LC–MS analytical method — LC column selection, mobile-phase gradient program, electrospray ionization, and mass analyzer parameters — for each sample is impractical. Instead, workers need to develop a single, universal analytical method and implement The authors have developed an approach to applying intelligent automation of liquid chromatography–mass spectrometry analysis for analytical screening of compound libraries using Microsoft Visual Basic macros. They performed the initial characterization of compounds using universal analytical methods. Samples that failed to meet selected criteria of analysis were automatically reanalyzed using secondary or alternative analytical conditions. The approach enables automated high-throughput analysis of compounds with diverse chemical properties and does not compromise sample throughput and data quality. Intelligent Automation of LC–MS Analysis for the Characterization of Compound Libraries