Issue 14, 2021

A portable droplet microfluidic device for cortisol measurements using a competitive heterogeneous assay

Abstract

Point-of-care monitoring of chemical biomarkers in real-time holds great potential in rapid disease diagnostics and precision medicine. However, monitoring is still rare in practice, as the measurement of biomarkers often requires time consuming and labour intensive assay procedures such as enzyme linked immunosorbent assay (ELISA), which pose a challenge to an autonomous point-of-care device. This paper describes a prototype device capable of performing ELISA autonomously and repeatedly in a high frequency using droplet microfluidics. Driven by a specially designed peristaltic pump, the device can collect liquid samples from a reservoir, produce trains of droplets, complete magnetic bead based ELISA protocols and provide readouts with colourimetric measurement. Here, cortisol was chosen as a target analyte as its concentration in the human body varies on a circadian rhythm which may be perturbed by disease. The prototype device draws in and analyses 350 nL of the sample containing free bioactive cortisol every 10 seconds, with a sample-to-signal time of 10 minutes, and measures favourably in the analytical range of 3.175–100 ng ml−1, with reliably lower variability compared with the well plate based assay. As most ELISA type assays share similar procedures, we envisage that this approach could form a platform technology for measurement or even continuous monitoring of biomarkers in biological fluids at the point-of-care.

Graphical abstract: A portable droplet microfluidic device for cortisol measurements using a competitive heterogeneous assay

Supplementary files

Article information

Article type
Paper
Submitted
18 Apr 2021
Accepted
24 May 2021
First published
26 May 2021
This article is Open Access
Creative Commons BY-NC license

Analyst, 2021,146, 4535-4544

A portable droplet microfluidic device for cortisol measurements using a competitive heterogeneous assay

G. W. H. Evans, W. T. Bhuiyan, S. Pang, B. Warren, K. Makris, S. Coleman, S. Hassan and X. Niu, Analyst, 2021, 146, 4535 DOI: 10.1039/D1AN00671A

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