Resolution of opiate illicit drugs signals in the presence of some cutting agents with use of a voltammetric sensor array and machine learning strategies

• Published in: Sensors and actuators. B, Chemical Vol. 357; p. 131345
• Main Authors: Ortiz-Aguayo, Dionisia, Cetó, Xavier, De Wael, Karolien, del Valle, Manel
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 15.04.2022; Elsevier Science Ltd
• Subjects: Caffeine; Drug abuse; Drugs; Electronic tongue; Electronic tongues; Least squares method; Machine learning; Machine tools; Mixtures; Morphine; Narcotics; Opioids; Palladium; Partial-least squares regression; Sensor arrays; Square waves; Voltammetric sensors; Voltammetry; Partial-least squares regression; Electronic tongue; Voltammetric sensors; Opioids
• ISSN: 0925-4005; 1873-3077; 1873-3077
• DOI: 10.1016/j.snb.2021.131345

In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the µM level, LODs between 1.8 and 5.3 µM for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the μM level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset. [Display omitted] •The potential of an electronic tongue for the analysis of illicit substances is explored.•Voltammetric fingerprints of opiate drugs are extracted with a three-sensor array.•Chemometric model built using genetic algorithms and partial-least squares (GA-PLS).•Quantification of ternary mixtures of heroin, morphine and codeine is achieved.•Similar performance is demonstrated even in the presence of caffeine and paracetamol.