Molecularly Imprinted Polymer-based voltammetric sensor for amino acids/indazole derivatives synthetic cannabinoids detection.

BACKGROUND

Synthetic cannabinoids (SCs) are a broad class of illicit drugs that are classified according to the chemical structure of the aromatic core that they present (i.e., indole, imidazole, pyrrole) and their detection is still a challenge, despite their widespread diffusion. The identification of a specific class of SC in complex matrices, such as real samples with a rapid, economic analytical device useable directly in the field, is highly desirable, as it can provide immediate and reliable information that eventually addresses more targeted analyses.

RESULTS

The present paper proposes a Molecularly Imprinted Polymer (MIP)-based voltammetric sensor for the rapid and selective detection of indazole-type SCs. In this context, a polyacrylate-based MIP was used to functionalize a Pt electrode. The MIP composition was optimized through a Design of Experiments approach, and for the sake of safety, a non-psychotropic compound structurally related to the selected SCs was employed as the template in the MIP formulation. A complete characterization of the electrochemical behavior of the selected SCs was performed, and differential pulse voltammetry (DPV) in acetonitrile/lithium perchlorate 0.1 M was the technique applied for their quantification. LOD around 0.01 mM and linearity up to 0.8 mM were found. Comparison with the non-imprinted (NIP) modified and bare electrodes showed better selectivity and reproducibility of the MIP-based sensor. Recovery tests (in the 70-115 % range) were performed on simulated pills and smoking mixtures to test the reliability of the proposed method.

SIGNIFICANCE

The method proposed allows the identification and quantification of indazole-based SCs as a class in complex matrices. Due to the selectivity of the obtained device, no clean-up of the sample before analyses is needed. For the same reason, the interference of cutting substances and natural cannabinoids was negligible.

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.