Towards remote monitoring of autoimmune disease progression with the use of portable, electrochemical cytokine detection platforms

Abstract

The healthcare industry is increasingly adopting digital technologies, facilitating access to quality medical care for traditionally under-served and remote communities. However, modern remote medicine is limited to Q&A sessions and optical explorations, hindering effective patient monitoring. To address this, novel tools are required to bridge the gap between hospitals and patients’ homes. Electrochemical detection, with its miniaturization capabilities, has emerged as a viable option for remote biomarker detection. In addition, microfluidics can enhance electrochemical detection techniques, allowing for the integration of the entire assay workflow into a small portable form-factor.

This thesis presents three technologies aimed at enabling remote patient monitoring through decentralized biomarker detection. First, a method for enhancing electrochemical assays through magnetophoretic bead confinement is presented. This technique enables the design of increasingly sensitive electrochemical detection electrodes, regardless of size, material, or detected analyte. Second, a portable and automated sample-to-answer platform capable of detecting proteins with high sensitivity and in short assay times is introduced and characterized. This platform enables patients to monitor protein biomarkers outside the confines of clinical laboratories with low limits-of-detection. Lastly, an electroactive bead for label-free biomarker detection is presented. This work introduces the development of inherently electroactive magnetic beads for analyte immobilization, handling, and quantification.

All of these technologies are developed with the goal of creating a simple, automated platform for multiplexed biomarker detection. It is envisioned that the development of these technologies will give rise to the decentralisation of clinical tests and allow medical practitioners and researchers to tap into an undiscovered trove of data and information.

Date of Award	2023
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	George Jie YUAN (Supervisor)