4.7 Review

Biosensors for detection of organophosphate pesticides: Current technologies and future directives

Journal

MICROCHEMICAL JOURNAL
Volume 178, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.microc.2022.107420

Keywords

Pesticides; Organophosphate; Biosensors; Electrochemical systems; Organ in a chip; Metabolomics

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This review discusses the development of various biosensors for detecting the effects of organophosphate pesticides in environmental and biological samples. It also highlights the use of organ-on-chip models to analyze the impact of these pesticides on specific organs in humans.
Organophosphate (OP) pesticides applied on agricultural fields undergo diffuse contamination and cause poisoning in humans and other non-target organisms. Therefore, it is of utmost importance to detect and analyse the effect of OP in environmental as well as biological samples. This review summarizes various biosensors which are being developed such as electrochemical-based, immune-based, optical, and enzyme-based biosensors, to detect the presence of OP with efficient accuracy. Biosensors analysing the effect of OP on different organs in humans are also being developed. These are Organ-on-chip models, which interpret the effect of OP at different concentrations on specific cells. These chips are maintained in a microfluidic environment such that it mimics the in vivo conditions, thus eliminating the use of animals or cell cultures. Even multi organ-on-chip can be developed to analyse the effect of OP with relation to other organs in the body. Currently, for OP like dichlorodiphenyl trichloroethane, permethrin, and rotenone, liver-on-chip have been developed to analyse their effects on liver cells. In the future, biosensing to analyse the effect of OP on the cells' metabolomics can also be done using metabolomics-on-chip. Despite the surge in research interest towards developing better biosensors, there is a lack of wide-scale application to detect OP efficiently; this is primarily due to inadequate technology to develop facile, stable models. Future research needs to focus on enhancing the potential of biosensors for field applications.

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