Abstract

Aim (For research use only, not for use in diagnostic procedures). Evaluate the effectiveness of a new beta glucuronidase enzyme to efficiently hydrolyze glucuronide drugs in less than 30 minutes followed by a dilute and shoot LC-MS/MS analysis. Methods Automated 30 minute purified β-Glucuronidase (IMCS, Columbia, USA) hydrolysis was performed on spiked urine, containing 8 glucuronidated and 64 non-glucuronidated drug compounds. Samples were loaded onto a GERSTEL MPS2 equipped with an incubator that allowed for the automated hydrolysis followed by dilution and direct injection on to the LC-MS/MS system. The LC-MS/MS system consisted of an AB SCIEX QTRAP ® 4500 System. LC separation was performed on a Phenomenex Kinetex 2.6 μm PhenylHexyl 100 A, 50 × 4.6 mm column at 30 °C; 10 minute gradient of water and methanol with ammonium formate buffer; 0.7 mL/min flow rate 10 μL injection volume. Results In order to demonstrate that the hydrolysis reaction had gone to completion within this short time period compared to the traditional 2 hour hydrolysis protocol, the urine standards were analysed for the presence of the glucuronide. In all cases only the parent drug was detected and no presence of the glucuronide was observed. The reproducibility of the automated protocol was assessed by preparing and analyzing replicates of each calibration standard, and the measured CVs were less than 15% over the entire concentration range covered by the assay. The method displayed good linearity for all analytes, with R > 0.99. The method was shown to be robust after monitoring response of the analytes over 900 injections. Not only does method automation eliminate human error, thus increasing reproducibility, it also eliminates subjectivity during data processing, and furthermore has the potential to save a great deal of time. Conclusion An automated, rapid urine hydrolysis LC-MSMS forensic toxicology screening method using the GERSTEL MPS2 as the sample preparation workstation and LC autosampler, has been investigated and has been shown to provide a viable approach to provide automated sample analysis from start to finish.

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