Optimization and application of fabric phase sorptive extraction coupled to ultra-high performance liquid chromatography tandem mass spectrometry for the determination of cytostatic drug residues in environmental waters

Every year, hundreds of tons of organic pollutants reach the environment through effluents released from wastewater treatment plants worldwide, and many of these compounds have harmful effects on the aquatic ecosystem. A new class of emerging pollutants of high concern is cytostatic drugs, which are designed to treat different types of cancers by attacking cells. Environmentabconcentrations of cytostatic drugs are known to be in the range of ng L-1, and for this reason, it is imperative to develop analytical methods of extraction and preconcentration to allow for subsequent instrumental analysis of these drugs. In this work, a rapid, simple and green method for the analysis of seven cytostatic drug compounds that are commonly used in anti-cancer therapies was developed using a novel extraction process based on a powerful miniaturized technique, fabric phase sorptive extraction (FPSE) coupled to ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). The major parameters that affect the extraction process were optimized. The new method shows good linearity, with a relative standard deviation (RSD) of less than 12%. Relative recoveries higher than 40% were obtained for the studied compounds, and the detection limit of the method was within the values at which these compounds are usually found in environmental water (0.20 ng L-1 to 80 ng L-1). The Limit of Quantification ranged from 0.68 to 267 ng L-1. Significant suppression of the signal due to the matrix effect, a common shortcoming attributed to interference from the extraction process as well as the use of ionization mode, was not observed. Subsequently, the method was applied to real wastewater samples from an effluent obtained from a hospital area and three wastewater treatment plants located in Gran Canaria Island, Spain. (C) 2017 Elsevier B.V. All rights reserved.