A multivariate biosensor for non-invasive glucose and urea monitoring via saliva

Abstract

Non-communicable diseases such as diabetes and chronic kidney disease (CKD) are major global health concerns due to associated high morbidity rates. Conventional monitoring of these diseases typically involves invasive methods, which can be painful and inconvenient for patients. This study highlights the development of a non-invasive, handheld optical biosensor capable of multivariate analysis using saliva samples. The device used two distinct paper-fluidic strips designed with different enzyme–dye combinations to detect glucose and urea. The biosensor also used ambient temperature compensation to address the differential sensitivity of these sensors owing to variations caused by temperature-dependent enzyme kinetics, thereby enhancing the measurement accuracy. Biosensor characteristics with the glucose oxidase-based strip showed a sensitivity of 1.93 count per mg per dL, linearity range from 8 to 358 mg dL⁻¹, limit of detection (LOD) of 8 mg dL⁻¹, and response time of 7.35 s. The clinical validation shows good correlation between saliva glucose levels (SGLs) and blood glucose levels (BGLs). The urea biosensor strip shows a sensitivity of 1.51 count per mg per dL, LOD of 5 mg dL⁻¹, linearity range from 5 to 90 mg dL⁻¹, and response time of 3 s. The clinical validation for the CKD patient shows a significant correlation between blood urea levels and saliva urea levels. The results demonstrate that the device offers a rapid, reliable, and user-friendly alternative for point-of-care testing (POCT), potentially improving patient compliance and management of diabetes and CKD. Significance: The findings suggest that this technology could represent a significant advancement in non-invasive diagnostic tools and can be used as a POCT by chronic patients.