Rapid resolution liquid chromatography-mass spectrometry and high-performance liquid chromatography-fluorescence detection for metabolism and pharmacokinetic studies of ergosta-4,6,8(14),22-tetraen-3-one.

Ergosta-4,6,8(14),22-tetraen-3-one (ergone) from many medicinal plants has been demonstrated to possess a variety of pharmacological activities in vivo and in vitro, including cytotoxic, diuretic and immunosuppressive activity. Metabolism and pharmacokinetic studies on rat were conducted for ergone. Rapid resolution liquid chromatography with atmospheric pressure chemical ionization tandem multi-stage mass spectrometry (RRLC-APCI-MS(n)) and high-performance liquid chromatography with fluorescence detection (HPLC-FLD) methods were applied for the identification and quantification of ergone and its metabolite from rat plasma, faeces and urine. A metabolite was identified by RRLC-DAD-APCI-MS(n): 22,23-epoxy-ergosta-4,6,8(14)-triaen-3-one (epoxyergone). The concentrations of the analyte with its metabolites were determined by HPLC-FLD at excitation wavelength of 370 nm and emission wavelength of 485 nm. The samples were deproteinized with methanol after addition of camptothecin as internal standard (IS). The analysis was performed on a Diamonsil C18 column (150 mm x 4.6 mm x 5 microm) with a mobile phase gradient consisting of methanol and water at a flow rate of 1 mL min(-1). The assay was linear over the concentration range of 42-1500, 36-7500 and 42-1500 ng mL(-1) for plasma, faecal homogenate and urine respectively. The absolute recoveries were found to be 97.0+/-1.2%, 98.1+/-0.7% and 96.6+/-1.8% for plasma, faecal homogenate and urine respectively. The intra-day and inter-day relative standard deviations (RSD) were less than 10%. The previous HPLC-MS/MS method is not affordable for most laboratories because of the specialty requirement and high equipment cost. However, the HPLC-FLD method is economic and operating simply for quantitative determination of ergone and its metabolite in rat plasma, faeces and urine. In addition, liquid chromatography coupled with ion trap multi-stage mass spectrometry is becoming a useful technique for ergone metabolite identification.

Review of the newest HPLC methods with mass spectrometry detection for determination of immunosuppressive drugs in clinical practice.

High performance liquid chromatography coupled with electrospray mass spectrometry is widely used for quantitative determination of immunosuppressive drugs (sirolimus, tacrolimus, everolimus, CsA and MPA) in biological fluids. The growth in volume for testing these drugs and economic constraints in clinical laboratories has led to heightened demand for high throughput methods. Fast-flow on-line extraction with switching valve technique and implementation of automation accelerates sample preparation. For on-line purification the combination of fast flow of washing solution and narrow-bore extraction column provides a clean sample in a very short time without compromising precision and accuracy. The unique feature of multireactant monitoring tandem mass spectrometry reduces significantly the need for chromatographic separation, as long as matrix effects are not detected, and permits simultaneous measurement of several drugs in one run when they are present in the same specimen. Additionally, the same method together with the identical sample preparation and HPLC-MS conditions and setting can be used for measurement of all five immunosuppressants, four of them in blood, MPA in plasma. Thanks to the high sensitivity of LC-MS only a small volume of biological sample is required for analysis. However for MPA quantitation, mass interference attributable to in-source fragmentation of its glucuronide metabolite can be a problem if the latter is not chromatographically separated from the parent drug before introduction of the sample into the ion source. Thus, chromatographic separation is extremely important for MPA analysis. In conclusion, important features of LC-MS methodology for immunosuppressive drugs include: shortened analysis time, increased throughput, selectivity and lower cost of analysis.