Voltammetric sensing using an array of modified SPCE coupled with machine learning strategies for the improved identification of opioids in presence of cutting agents

[Display omitted] •Array of voltammetric sensors is obtained through modification with a carbon-based ink.•Microscopy technique has been used to characterize the modified electrodes.•Electroanalytical response was studied vs. different opioids in presence of cutting agents.•Principal Component Analysis has been applied for the visualization of the clustering of tested compounds.•Silhouette parameter has been used to optimize composition of sensor array for best identification. This work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents.