An Automated Micro Solid-Phase Extraction (μSPE) Liquid Chromatography-Mass Spectrometry Method for Cyclophosphamide and Iphosphamide: Biological Monitoring in Antineoplastic Drug (AD) Occupational Exposure.
Stefano DugheriDonato SquillaciValentina SaccomandoGiorgio MarrubiniElisabetta BucalettiIlaria RapiNiccolò FanfaniGiovanni CappelliNicola MucciPublished in: Molecules (Basel, Switzerland) (2024)
Despite the considerable steps taken in the last decade in the context of antineoplastic drug (AD) handling procedures, their mutagenic effect still poses a threat to healthcare personnel actively involved in compounding and administration units. Biological monitoring procedures usually require large volumes of sample and extraction solvents, or do not provide adequate sensitivity. It is here proposed a fast and automated method to evaluate the urinary levels of cyclophosphamide and iphosphamide, composed of a miniaturized solid phase extraction (µSPE) followed by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analysis. The extraction procedure, developed through design of experiments (DoE) on the ePrep One Workstation, required a total time of 9.5 min per sample, with recoveries of 77-79% and a solvent consumption lower than 1.5 mL per 1 mL of urine sample. Thanks to the UHPLC-MS/MS method, the limits of quantification (LOQ) obtained were lower than 10 pg/mL. The analytical procedure was successfully applied to 23 urine samples from compounding wards of four Italian hospitals, which resulted in contaminations between 27 and 182 pg/mL.
Keyphrases
- solid phase extraction
- liquid chromatography tandem mass spectrometry
- liquid chromatography
- ms ms
- mass spectrometry
- tandem mass spectrometry
- high performance liquid chromatography
- simultaneous determination
- high resolution mass spectrometry
- ultra high performance liquid chromatography
- molecularly imprinted
- healthcare
- gas chromatography
- gas chromatography mass spectrometry
- low dose
- high dose
- ionic liquid
- machine learning
- minimally invasive
- capillary electrophoresis
- high resolution
- deep learning
- emergency department
- drug induced
- adverse drug
- quality control