The present study involves an analysis of the performance of liquid chromatography (LC)-accurate radioisotope counting (ARC) and microplate scintillation counter (TopCount) technologies in drug metabolism studies. For the purpose of evaluating these systems, biological samples resulting from the metabolism of a radiolabeled [14C] compound, known as compound B, are analyzed using LC-ARC and TopCount under similar high-performance LC conditions. Counting efficiency is 83% for LC-ARC, 77% for TopCount, and linearity is R2 of 0.9998 versus 0.9984, respectively. The limit of detection for LC-ARC is 12 disintegrations per minute (dpm) with 1-min/fraction counting, yet for TopCount it is 8.7 dpm with 5-min/fraction counting. Under optimal conditions for each, the total run time of LC-ARC is approximately half that of TopCount. These results indicate that there is no significant difference between these two systems in terms of efficiency, linearity, and limit of detection. However, the LC-ARC system does not involve any manual operations, yet TopCount requires manual sample transfer and data import. This study shows that impressive progress has been made in the technology of radioisotope counting in drug metabolism using LC-ARC. This system enhances the resolution of radiochromatograms and is able to measure volatile metabolites that TopCount cannot detect at all. The ability to acquire mass spectra online is also a major advancement. The overall results suggest that the combination of LC-ARC with radioactivity detection and mass spectrometry has great potential as a powerful tool for radioisotope measurement in metabolite identification studies during drug discovery and development.

A novel online method is developed, using liquid chromatography (LC)-accurate radioisotope counting dynamic-flow (ARC) coupled with a radioactivity detector and mass spectrometer, for metabolite identification in drug discovery and development. This method offers the advantages of improved sensitivity for detecting radiolabeled drugs as well as streamlining the process of identifying and characterizing metabolites. For the purposes of evaluating this method, in vitro human liver microsomal incubations with [(14)C]dextromethorphan are conducted. Online separation and identification of [(14)C]dextromethorphan metabolites are achieved without intensive sample preparation, concentration, or fraction collection. Mass spectrometric analysis identified and characterized the metabolites of dextromethorphan formed by N - and O -dealkylation, correlated well with previously published results. Chromatographic peaks for [(14)C]dextromethorphan and its metabolites are collected online, then infused for extended periods of time at a flow rate of 10 microL/min while maintaining the column pressure. The continuous analytical signal input allowed acquisition of a higher order of multistage fragmentation for both major and minor metabolites. The multistage MS fragmentation pattern obtained for the metabolites allowed defining the sites of metabolism for dextromethorphan. Further evaluations of this method are also conducted using a [(14)C]compound A to check the linearity and sensitivity of the dynamic-flow method. The R(2) value is 0.996 for the dynamic-flow method between 50 and 600 disintegrations per minute (dpm); the limit of detection for LC-ARC is 20 dpm, which is approximately 10 times more sensitive than conventional continuous-flow radioactivity detection techniques. The overall results suggest that the combination of LC-ARC with radioactivity detection and mass spectrometry has great potential as a powerful tool for enhancing the sensitivity of radioisotope measurement in metabolite identification studies during drug discovery and development.