Citation

Churcher NKM, Dhamu VN, Prasad S. Analyst 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Royal Society of Chemistry)

DOI

10.1039/d3an00522d

PMID

37306613

Abstract

Management of substances that possess high potential for abuse requires a comprehensive understanding of the temporal effects of a corresponding volume of intake. Cannabis is deemed as one of the most widely used drugs in the United States and studies related to the primary psychoactive compound present in it, Δ-9-tetrahydrocannabinol (THC), have revealed that it causes adverse health effects. In this study, we present a field-deployable electrochemical sensing system that can detect THC at the 5 ng mL(-1) cut-off level with a dynamic range of 0.1-100 ng mL(-1) in human saliva. Considering the complexity of the human saliva matrix, the specificity study demonstrated selectivity towards THC with minimum interactions with ethanol and cannabidiol (CBD). Surface Plasmon Resonance (SPR) has been implemented to visualize and validate the capture probe as a means for THC detection. A robust, compatible binary classifier model has been shown in this work to effectively group samples into THC+ (high) and THC- (low) groups from human saliva with an accuracy greater than 90% considering a limited dataset. Hence, we demonstrate the potential of an innovative end-to-end system to effectively regulate cannabis use and prevent substance abuse in our surroundings.

Language: en