High-throughput selected reaction monitoring liquid chromatography-mass spectrometry determination of methylphenidate and its major metabolite, ritalinic acid, in rat plasma employing monolithic columns

Abstract

This work presents a high-throughput selected reaction monitoring (SRM) LC-MS method for the determination of methylphenidate (MPH), a central nervous stimulant, and its de-esterified metabolite, ritalinic acid (RA) in rat plasma samples. A separation of these two compounds was achieved in 15 s by employing a 3.5-ml/min flow-rate, a porous monolithic column and a TurboIonSpray source compatible with relatively high flow-rates. In addition, a relatively fast autosampler and a new data acquisition system resulted in a time lag of less than 17 s between consecutive injections. Overall, 768 protein-precipitated rat plasma samples (eight 96-well plates) containing both MPH and RA were analyzed within 3 h and 45 min. The partial method validation described in this report included an assessment of linearity, intra and inter-assay precision and accuracy, and method robustness. Deuterated internal standards for the target compounds, d(3)-MPH and d(5)-RA, were employed. The calibration curves ranged from 0.1 to 50 ng/ml for MPH and from 0.5 to 50 ng/ml for RA. The limit of quantification (LOQ) for MPH and RA was 0.1 and 0.5 ng/ml, respectively. For both analytes, the intra- and inter-assay precision (relative standard deviation, % C.V.) and accuracy (relative error) did not exceed 15% for the quality control samples (QCs) QC1, QC2 or QC3 (0.3, 1.5 and 40 ng/ml for MPH and 0.15, 15 and 40 ng/ml for RA) for either analyte and did not exceed 20% at the lower limit of quantitation (LOQ) level. No carry-over from the autosampler was detected. The retention times remained constant throughout the experiment. Baseline resolution of MPH and RA was consistently observed throughout the plates analyzed. The described method demonstrates the feasibility for employing monolithic HPLC columns to effect rapid bioanalytical SRM LC-MS analysis of representative biological samples.