Fully Integrated and High‐Throughput Microfluidic System for Multiplexed Point‐Of‐Care Testing

Author:

Li Shunji1,Zhang Ying1,Liu Jingxuan1,Wang Xing1,Qian Chungen2,Wang Jingjing2,Wu Liqiang2,Dai Chenxi1,Yuan Huijuan1,Wan Chao1,Li Jiashuo1,Du Wei1,Feng Xiaojun1,Li Yiwei1,Chen Peng1,Liu Bi‐Feng1ORCID

Affiliation:

1. The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics Hubei Bioinformatics & Molecular Imaging Key Laboratory Systems Biology Theme Department of Biomedical Engineering, College of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

2. Department of Reagent Research and Development Shenzhen YHLO Biotech Co., Ltd. Shenzhen 518000 China

Abstract

AbstractFor every epidemic outbreak, the prevention and treatments in resource‐limited areas are always out of reach. Critical to this is that high accuracy, stability, and more comprehensive analytical techniques always rely on expensive and bulky instruments and large laboratories. Here, a fully integrated and high‐throughput microfluidic system is proposed for ultra‐multiple point‐of‐care immunoassay, termed Dac system. Specifically, the Dac system only requires a handheld portable device to automatically recycle repetitive multi‐step reactions including on‐demand liquid releasing, dispensing, metering, collecting, oscillatory mixing, and discharging. The Dac system performs high‐precision enzyme‐linked immunosorbent assays for up to 17 samples or targets simultaneously on a single chip. Furthermore, reagent consumption is only 2% compared to conventional ELISA, and microbubble‐accelerated reactions shorten the assay time by more than half. As a proof of concept, the multiplexed detections are achieved by detecting at least four infection targets for two samples simultaneously on a singular chip. Furthermore, the barcode‐based multi‐target results can rapidly distinguish between five similar cases, allowing for accurate therapeutic interventions. Compared to bulky clinical instruments, the accuracy of clinical inflammation classification is 92.38% (n = 105), with a quantitative correlation coefficient of R2 = 0.9838, while the clinical specificity is 100% and the sensitivity is 98.93%.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Wiley

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