Automated system for multiplexing detection of COVID-19 and other respiratory pathogens

Parker Y.L. Tsang, Sunny L.H. Chu, Libby C.W. Li, Deborah M.S. Tai, Berry K.C. Cheung, Firaol Tamiru Kebede, Pete Y.M. Leung, Winston Wong, Teresa Chung, Cyril C.Y. Yip, Rosana Y.S. Poon, Jonathan Chen, Kwok-Yung Yuen, Manson Fok, Johnson Y.N. Lau, Lok-Ting Lau*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Infectious diseases are global health challenge, impacted the communities worldwide particularly in the midst of COVID-19 pandemic. The need of rapid and accurate automated systems for detecting pathogens of concern has always been critical. Ideally, such systems shall detect a large panel of pathogens simultaneously regardless of well-equipped facilities and highly trained operators, thus realizing on-site diagnosis for frontline healthcare providers and in critical locations such as borders and airports. Methods & Results: Avalon Automated Multiplex System, AAMST, is developed to automate a series of biochemistry protocols to detect nucleic acid sequences from multiple pathogens in one test. Automated processes include isolation of nucleic acids from unprocessed samples, reverse transcription and two rounds of amplifications. All procedures are carried out in a microfluidic cartridge performed by a desktop analyzer. The system was validated with reference controls and showed good agreement with their laboratory counterparts. In total 63 clinical samples, 13 positives including those from COVID-19 patients and 50 negative cases were detected, consistent with clinical diagnosis using conventional laboratory methods. Conclusions: The proposed system has demonstrated promising utility. It would benefit the screening and diagnosis of COVID-19 and other infectious diseases in a simple, rapid and accurate fashion.
Original languageEnglish
Article number9992220
Number of pages13
JournalIEEE Journal of Translational Engineering in Health and Medicine
DOIs
Publication statusE-pub ahead of print - 19 Dec 2022

Scopus Subject Areas

  • Biomedical Engineering

User-Defined Keywords

  • Automation
  • COVID-19
  • biochemistry
  • clinical diagnosis
  • genomics
  • microfluidics
  • polymerase chain reaction (PCR)

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