Pharmacokinetic study on costunolide and dehydrocostuslactone after oral administration of traditional medicine Aucklandia lappa Decne. by LC/MS/MS

Ethnopharmacological relevance Radix Aucklandiae (RA), a well known traditional Chinese medicine, is widely used for treating various problems in digestive system. A selective and sensitive high-performance liquid chromatography coupled with mass spectrometry method was first developed and validated for simultaneous quantification of costunolide and dehydrocostuslactone in rat plasma with diazepam as internal standard after oral administration of RA extraction. Materials and methods Plasma samples were extracted via solid-phase extraction and detected by multiple-reaction monitoring mode under positive electrospray. Chromatographic separation was accomplished on an Agilent C18 column (2.1 mm×150 mm, 5 µm), with 0.1% formic acid and acetonitrile (1:1) as the mobile phase at a flow rate of 0.5 mL/min. Results The quantification was performed using the transitions of m/z 233/187 for costunolide, m/z 231/185 for dehydrocostuslactone and m/z 285/193 for diazepam, respectively. Calibration curves were linear over the concentration range of 0.7–769.7 ng/mL for costunolide and 0.9–956.0 ng/mL for dehydrocostuslactone. The intra-day and inter-day precisions (RSD%) for two compounds was less than 8.76% and 9.70% and the accuracy (RE%) range from 6.14% to 5.35%. The time to reach the maximum plasma concentration (Tmax) was 10.46 h for costunolide, 12.39 h dehydrocostuslactone. The elimination half-time (t1/2) of costunolide and dehydrocostuslactone was 5.54±0.81 and 4.32±0.71 (h). The AUC of costunolide and dehydrocostuslactone was 308.83 and 7884.51 respectively (ng h/mL). Conclusions It was the first report for the study of pharmacokinetic profile of costunolide and dehydrocostuslactone in rat plasma after oral administration of RA extract. These results provided a meaningful basis for better understanding the absorption of traditional medicine, RA, and provide useful scientific data for clinical application.