In this paper, an analytical method has been developed and validated for the analysis of new psychoactive substances (NPS) and metabolites in hair samples. The method was based on pressurized liquid extraction (PLE) followed by solid-phase extraction (SPE) clean-up and high performance liquid chromatography-high resolution mass spectrometry (HPLC-HRMS) analysis. To evaluate extraction efficiency and the applicability of the method, hair samples were fortified by soaking in order to obtain a good surrogate for drug users' hair; the amount of incorporated drugs related to their lipophilicity, similarly to in vivo drug incorporation. To the best of our knowledge, this is the first method that allowed for the analysis of both cathinones (5) and synthetic cannabinoids (7) in hair with a single extraction procedure and chromatographic run. A phenethylamine (2C-T-4), 4- fluorophenylpiperazine and methoxetamine were also included showing that PLE coupled to SPE clean-up was suitable for a multi-class analysis of NPS in hair. In addition, the use of PLE significantly reduced hair analysis time: decontamination, incubation, clean-up, and liquid chromatography-mass spectrometry (LC-MS) analysis were carried out in approximately 45 min. The method was fully validated according to Scientific Working Group for Forensic Toxicology (SWGTOX) and Society of Hair Testing (SoHT) guidelines. Limit of quantification (LOQ) values ranged from 8 to 50 pg mg-1 for cathinones, phenetylamines and piperazines, and from 9 to 40 pg mg-1 for synthetic cannabinoids (10 pg mg-1 for methoxetamine). Matrix effects were below 15% for all the analytes, demonstrating the effectiveness of the clean-up step. Inaccuracy was lower than 9% in terms of bias.
Multi-class analysis of new psychoactive substances and metabolites in hair by pressurized liquid extraction coupled to HPLC-HRMS / Montesano, Camilla; Vannutelli, Gabriele; Massa, Maristella; Simeoni, Maria Chiara; Gregori, Adolfo; Ripani, Luigi; Compagnone, Dario; Curini, Roberta; Sergi, Manuel. - In: DRUG TESTING AND ANALYSIS. - ISSN 1942-7603. - STAMPA. - 9:5(2017), pp. 798-807. [10.1002/dta.2043]
Multi-class analysis of new psychoactive substances and metabolites in hair by pressurized liquid extraction coupled to HPLC-HRMS
MONTESANO, CAMILLA;VANNUTELLI, GABRIELE;CURINI, Roberta;SERGI, MANUEL
2017
Abstract
In this paper, an analytical method has been developed and validated for the analysis of new psychoactive substances (NPS) and metabolites in hair samples. The method was based on pressurized liquid extraction (PLE) followed by solid-phase extraction (SPE) clean-up and high performance liquid chromatography-high resolution mass spectrometry (HPLC-HRMS) analysis. To evaluate extraction efficiency and the applicability of the method, hair samples were fortified by soaking in order to obtain a good surrogate for drug users' hair; the amount of incorporated drugs related to their lipophilicity, similarly to in vivo drug incorporation. To the best of our knowledge, this is the first method that allowed for the analysis of both cathinones (5) and synthetic cannabinoids (7) in hair with a single extraction procedure and chromatographic run. A phenethylamine (2C-T-4), 4- fluorophenylpiperazine and methoxetamine were also included showing that PLE coupled to SPE clean-up was suitable for a multi-class analysis of NPS in hair. In addition, the use of PLE significantly reduced hair analysis time: decontamination, incubation, clean-up, and liquid chromatography-mass spectrometry (LC-MS) analysis were carried out in approximately 45 min. The method was fully validated according to Scientific Working Group for Forensic Toxicology (SWGTOX) and Society of Hair Testing (SoHT) guidelines. Limit of quantification (LOQ) values ranged from 8 to 50 pg mg-1 for cathinones, phenetylamines and piperazines, and from 9 to 40 pg mg-1 for synthetic cannabinoids (10 pg mg-1 for methoxetamine). Matrix effects were below 15% for all the analytes, demonstrating the effectiveness of the clean-up step. Inaccuracy was lower than 9% in terms of bias.File | Dimensione | Formato | |
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