Preconcentration and determination of five antidepressants from human milk and urine samples by stir bar filled magnetic ionic liquids using liquid-liquid-liquid microextraction-high-performance liquid chromatography

A sensitive and straightforward liquid-liquid-liquid microextraction method was developed to preconcentrate and cleanup antidepressants, including mirtazapine, venlafaxine, escitalopram, fluoxetine, and fluvoxamine, from biological samples before analyzing with high-performance liquid chromatography. The essential novelty of this study is using magnetic ionic liquids as the extraction phase in the lumen of hollow fiber and preparing a liquid magnetic stir bar. In this method, polypropylene hollow fiber was utilized as the permeable membrane for the analyte extraction. Six magnetic ionic liquids consisting of the transition metal and rare earth compounds were synthesized and then hollow fiber lumen was injected as acceptor phase to extract the antidepressants. Besides, 3-pentanol as a water-immiscible solvent was impregnated in the hollow fiber wall pores. The effective factors in the method were optimized with the central composition design. The resultant calibration curves were linear over the concentration range of 0.8-400.0 ng mL(-1) (R-2 >= 0.996). The method displayed the proper detection limit (0.11-0.24 ng mL(-1)), the reasonable limit of quantification (<= 0.79 ng mL(-1)), wide linear ranges, high preconcentration factors (>= 294.3), and suitable relative standard deviation (2.31-5.47%) for measuring antidepressant medications. Analysis of human milk and urine samples showed acceptable recoveries of 96.5-103.8% with excellent relative standard deviations lower than 5.95%.

Automated summary

A sensitive and straightforward liquid-liquid-liquid microextraction method was developed using magnetic ionic liquids as the extraction phase to preconcentrate and cleanup antidepressants from biological samples. The method showed good calibration curves, proper detection limit, reasonable limit of quantification, wide linear ranges, high preconcentration factors, and suitable relative standard deviation.