4.6 Article

Optimization by response surface methodology of a dispersive magnetic solid phase extraction exploiting magnetic graphene nanocomposite coupled with UHPLC-PDA for simultaneous determination of new oral anticoagulants (NAOs) in human plasma

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DOI: 10.1016/j.jpba.2019.112992

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Ultra high-performance liquid chromatography; Anticoagulants; Magnetic solid phase extraction; Graphene nanocomposite; Box-Behnken design of experiment

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In this paper a dispersive magnetic-solid phase extraction (MSPE) using a graphene nanocomposite (rG/Fe3O4) followed by ultra high performance liquid chromatography with photodiode array detection has been developed for the simultaneous analysis of new class of oral anticoagulants (NOAs) in human plasma. The performance of the nanocomposite graphene@Fe3O4 on the magnetic solid phase extraction of apixaban, rivaroxaban and dabigatran has been optimized using a Box-Behnken design of experiment. The amount of graphene nanocomposite, the sample pH and the adsorption time were the investigated parameters as a function of the extraction recovery. The analytical method was fully validated based on linearity, limit of detection (LOD), limit of detection (LOQ), inter- and intra-day precision and trueness, and extraction yield. Under optimal condition, excellent linearity (R-2 > 0.9987) over the range (0.001-5.0 mu g/mL), limit of detection (0.003 mu g/mL), precision (0.81-8.97% RSD) and trueness (-5 to 9 % BIAS%) were observed for the target drugs. The average extraction recovery under optimal from plasma samples ranged between 96.6-98.6% for apixaban, rivaroxaban and dabigatran and the internal standard. The proposed method was developed, validated and successfully applied to the measurement of these NOAs in patients. The new approach offers an attractive alternative for the simultaneous analysis of the selected NOAs from plasma samples, providing several advantages including fewer sample preparation steps, ease of performance, and higher recoveries compared to traditional methodologies. (C) 2019 Elsevier B.V. All rights reserved.

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