Green Composite Sensor for Monitoring Hydroxychloroquine in Different Water Matrix
Danyelle Medeiros de Araújo, Suelya da Silva Mendonça de Paiva, João Miller de Melo Henrique, Carlos A. Martínez‐Huitle, Elisama Vieira dos Santos
Abstract
Hydroxychloroquine (HCQ), a derivative of 4-aminoquinolone, is prescribed as an antimalarial prevention drug and to treat diseases such as rheumatoid arthritis, and systemic lupus erythematosus. Recently, Coronavirus (COVID-19) treatment was authorized by national and international medical organizations by chloroquine and hydroxychloroquine in certain hospitalized patients. However, it is considered as an unproven hypothesis for treating COVID-19 which even itself must be investigated. Consequently, the high risk of natural water contamination due to the large production and utilization of HCQ is a key issue to overcome urgently. In fact, in Brazil, the COVID-19 kit (hydroxychloroquine and/or ivermectin) has been indicated as pre-treatment, and consequently, several people have used these drugs, for longer periods, converting them in emerging water pollutants when these are excreted and released to aquatic environments. For this reason, the development of tools for monitoring HCQ concentration in water and the treatment of polluted effluents is needed to minimize its hazardous effects. Then, in this study, an electrochemical measuring device for its environmental application on HCQ control was developed. A raw cork-graphite electrochemical sensor was prepared and a simple differential pulse voltammetric (DPV) method was used for the quantitative determination of HCQ. Results indicated that the electrochemical device exhibited a clear current response, allowing one to quantify the analyte in the 5-65 µM range. The effectiveness of the electrochemical sensor was tested in different water matrices (in synthetic and real) and lower HCQ concentrations were detected. When comparing electrochemical determinations and spectrophotometric measurements, no significant differences were observed (mean accuracy 3.0%), highlighting the potential use of this sensor in different environmental applications.