Determination of Ketamine and Norketamine in hair samples using MEPS as sample clean-up

Simão, Ana Y.; Oliveira, Patrik; Rosendo, Luana M.; Rosado, Tiago; Gallardo, Eugenia; Andraus, Maristela; Barroso, Mário

http://hdl.handle.net/10400.26/44097

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Introduction and Aim: The use of hair samples to determine ketamine (K) and its metabolite, norketamine (NK), has been studied by several authors, using different clean-up approaches. However, microextraction by packed sorbent (MEPS), a miniaturized form of the classic solid-phase extraction has not been applied to date for the purpose. Therefore, a method to determine K and NK in hair samples was developed, optimized, and validated using MEPS as sample clean-up. Materials & Methods: Hair samples were scissor-cut into small fragments, and rinsed with methanol to remove dirt and externally deposited material. Following an overnight incubation with methanol at 65 ºC (no stirring), the compounds were analysed by GC-MS/MS without the need of derivatization procedures; MEPS conditions were: conditioning (5 x 250 µL of methanol and 4 x 250 µL of deionized water); load (10 x 150 µL of hair extract); washing (50 µL of 0.1% acetic acid and 50 µL of 10% methanol); and elution (100 µL of 3% ammonium hydroxide in methanol). Results & Discussion: The procedure resulted in acceptable recoveries, 39-61% for K and 32-43% for NK, and allowed reaching limits of quantification (LOQs) of 50 pg/mg for both analytes. The analytical method presented acceptable accuracy and precision with coefficients of variation typically lower than 15% and BIAS within ± 15%, except at the LOQ (20%). The method was successfully applied to 2 authentic samples, and ketamine concentrations were below 0.05 and 0.18 ng/mg. Norketamine was not detected. Conclusions: This work is the first analytical method using MEPS coupled to GC-MS/MS for the determination of K and NK in hair samples. Following a comparison with a SPE-based method using authentic samples, it was considered rapid and suitable for routine analysis. Acknowledgments: FCT (UIDB /00709/2020 and UIDP/00709/2020). A.Y. Simão acknowledges the PhD fellowship from FCT (2020.09070.BD).