A novel detection method combining on-line liquid chromatography-accurate radioisotope counting (LC-ARC, advanced stop flow controller) coupled with a radioactivity detector and mass spectrometer has been developed. One of the major benefits of this method is that this system enhances the sensitivity of radioisotope measurement for metabolite identification in drug metabolism studies. Another advantage to this system is the easy interface with the mass spectrometer, which allows acquisition of mass spectrometric data on-line. For purposes of evaluating this system, in vitro microsomal incubations with [3Hlpropranolol were conducted. On-line separation and identification of [3H]propranolol metabolites was achieved without intensive sample preparation, concentration, or fraction collection. Mass spectrometric analysis showed the presence of propranolol major metabolites formed by hydroxylation, correlating with previously published results. Further evaluations of this system also were conducted using two 14C compounds, which are herein labeled X and Y. As our results show, 14C peaks were detected down to 6 cpm, which is approximately 20 times more sensitive than commercially available flow through radioactivity detectors. The overall results suggest that the combination of LC-ARC with radioactivity detection and mass spectrometry has great potential as a powerful tool for improving the sensitivity of radioisotope measurement in metabolite identification studies during drug discovery and development.

A method for metabolite identification in drug discovery and development utilizing online hydrogen-deuterium (H-D) exchange and a tandem-quadrupole time-of-flight mass spectrometer coupled with liquid chromatography has been developed for the first time. For purposes of evaluating this method, nimodipine is incubated with rat, dog, monkey, and human hepatic microsomes over a 60-min period. This procedure involves the replacement of H(2)O with D(2)O in the mobile phase. The equilibration time required to change (switch) from H(2)O in the mobile phase into D(2)O is approximately 10 min. There is no significant difference between the retention times in H(2)O or D(2)O mobile phase. The results show that the separations of nimodipine and its metabolites and the subsequent H-D exchanges were achieved online. This leads to the identification of nimodipine metabolites formed in vitro. Five metabolites of nimodipine are identified and characterized. These metabolites are formed by dehydrogenation, demethylation of methoxy group, cleavage of the ester groups by hydrolysis or oxidation, and hydroxylation of methyl groups. The combination of the H-D exchange process and the assay system is found to be a powerful tool for the study of metabolite identification. The method appears to be highly desirable for identification of metabolites produced by dehydrogenation, oxidation, and dealkylation, which are discussed herein. This method also greatly enhances throughput, which in turn facilitates the ability to rapidly provide metabolite elucidation.

In this study, the development and validation of a method of analysis for 11,17,21,-trihydroxypregn-4-ene-3,20-dione (hydrocortisone, cortisol, HC) using high-performance liquid chromatography (HPLC)-tandem mass spectrometry (MS) with atmospheric-pressure chemical ionization (APCI) is reported. This is the first report of the systematic development and validation of an HPLC-MS-MS method for the quantitation of HC in synthetic human urine with a deuterated internal standard. Prior to LC-MS-MS analysis, the only sample preparation used was the dilute-and-shoot technique prior to LC-MS-MS analysis. In this study, an analysis time of less than 3 min is achieved. The results show freedom of interference from other analytes such as analogous steroids. Validation parameters such as specificity/selectivity, limit of quantitation (LOQ), linearity, precision, accuracy, ruggedness, stability, and system suitability are evaluated for this method. The LOQ is 5 ng/mL with an 8% relative standard deviation (RSD). For calibration standard curves, an average linear response for a 3-day validation (R2 = 0.997) over the range of 5 to 500 ng/mL is obtained. The interday precision %RSDs are 7.2, 5.0, and 5.2 for 15, 75, and 300 ng/mL, respectively. Also, brief comparisons of the dilute-and-shoot and liquid-liquid extraction techniques for this analyte are discussed.

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.