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Automated System for Multiplexing Detection of COVID-19 and Other Respiratory Pathogens.
Tsang, Parker Y L; Chu, Sunny L H; Li, Libby C W; Tai, Deborah M S; Cheung, Berry K C; Kebede, Firaol Tamiru; Leung, Pete Y M; Wong, Winston; Chung, Teresa; Yip, Cyril C Y; Poon, Rosana W S; Chen, Jonathan H K; Yuen, Kwok-Yung; Fok, Manson; Lau, Johnson Y N; Lau, Lok-Ting.
Affiliation
  • Tsang PYL; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Chu SLH; Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong China.
  • Li LCW; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Tai DMS; Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong China.
  • Cheung BKC; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Kebede FT; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Leung PYM; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Wong W; Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong China.
  • Chung T; Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong China.
  • Yip CCY; Emerging Viral Diagnostics (HK) Ltd. Hong Kong China.
  • Poon RWS; Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong China.
  • Chen JHK; Department of MicrobiologyThe University of Hong Kong Hong Kong China.
  • Yuen KY; Department of MicrobiologyThe University of Hong Kong Hong Kong China.
  • Fok M; Department of MicrobiologyThe University of Hong Kong Hong Kong China.
  • Lau JYN; Department of MicrobiologyThe University of Hong Kong Hong Kong China.
  • Lau LT; Centre for VirologyVaccinology and Therapeutics, Hong Kong Science and Technology Park Hong Kong China.
IEEE J Transl Eng Health Med ; 11: 424-434, 2023.
Article in En | MEDLINE | ID: mdl-37435542
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. Clinical and Translational Impact Statement- A rapid and multiplex diagnostic system proposed in this work can clinically help to control spread of COVID-19 and other infectious agents as it can provide timely diagnosis, isolation and treatment to patients. Using the system at remoted clinical sites can facilitate early clinical management and surveillance.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic_studies / Guideline Limits: Humans Language: En Journal: IEEE J Transl Eng Health Med Year: 2023 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic_studies / Guideline Limits: Humans Language: En Journal: IEEE J Transl Eng Health Med Year: 2023 Document type: Article Country of publication: United States