Fully automated standalone microfluidic integrated electrochemiluminescence platform for sample-to-answer detection of diabetes complication markers

Abstract

The current standard for diabetes care primarily relies on the finger prick blood sample method to monitor glucose levels. However, this approach is often painful, poses a risk of infection to patients, and provides limited metabolic insights. To address these limitations, a non-invasive approach using easily accessible biofluids such as sweat and urine offers a painless alternative to traditional blood tests. Moreover, monitoring other biochemical markers alongside glucose, such as lactate and uric acid, can offer a more comprehensive assessment of diabetes and help detect early signs of complications. Herein, a microfluidic integrated electrochemiluminescence (μfluidic-ECL) biosensing chip and a fully automated standalone ECL sample-to-answer diagnostic platform were designed to perform the detection of multiple diabetes markers accurately and sensitively. The developed ECL platform can perform all the functions of a benchtop ECL analyzer without compromising on performance and accuracy. The developed diagnostic platform has been successfully implemented and validated for the detection of glucose, lactate, and uric acid in a laboratory setting and shows promising results for field deployment, positioning it at the technology readiness level (TRL) 4–5. The μfluidic-ECL biosensing chip performance was numerically investigated using COMSOL software to achieve the optimum fluid mixing efficiency and fluid interaction with the electrode surface. The sensor has shown a wide linear range of 10 μM to 10 mM, 10 μM to 2.5 mM, and 10 μM to 1 mM, a limit of detection of 27 μM, 20 μM, and 10.9 μM, and a limit of quantification of 84 μM, 61 μM, and 32.9 μM for glucose, lactate, and uric acid, respectively. The sensor analytical performance was evaluated in terms of stability, reproducibility against potential interferents, and real sample analysis using artificial sweat and artificial urine. The finding suggested that the developed μfluidic-ECL would be a comprehensive and integrated solution for the non-invasive and accurate detection of diabetes complication markers to offer personalized diagnostics.