4.8 Article

Artificial Intelligence-Controlled Microfluidic Device for Fluid Automation and Bubble Removal of Immunoassay Operated by a Smartphone

期刊

ANALYTICAL CHEMISTRY
卷 94, 期 9, 页码 3872-3880

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.1c04827

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资金

  1. 2021 KwangWoon Research Grant
  2. Korea Medical Device Development Fund grant - Korea government (Ministry of Science and ICT) [202012D12]
  3. Korea Medical Device Development Fund grant - Korea government (Ministry of Trade, Industry and Energy) [202012D12]
  4. Korea Medical Device Development Fund grant - Korea government (Ministry of Health Welfare) [202012D12]
  5. Korea Medical Device Development Fund grant - Korea government (Ministry of Food and Drug Safety) [202012D12]
  6. Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) - Ministry of Health Welfare
  7. Ministry of Science and ICT, Republic of Korea [HU20C0414]
  8. Business for Startup growth and technological development (TIPS Program) - Korean Ministry of SMEs and Startups [S3033064]
  9. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2018R1D1A1B07050677]
  10. Korea Technology & Information Promotion Agency for SMEs (TIPA) [S3033064] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The use of AI technology to control microfluidics has revolutionized the field of point-of-care clinical diagnosis, providing an automated and reliable platform with low-cost and high sensitivity for immunoassays.
There have been tremendous innovations in microfluidic clinical diagnostics to facilitate novel point-of-care testing (POCT) over the past decades. However, the automatic operation of microfluidic devices that minimize user intervention still lacks reliability and repeatability because microfluidic errors such as bubbles and incomplete filling pose a major bottleneck in commercializing the microfluidic devices for clinical testing. In this work, for the first time, various states of microfluid were recognized to control immunodiagnostics by artificial intelligence (AI) technology. The developed AI-controlled microfluidic platform was operated via an Android smartphone, along with a low-cost polymer device to effectuate enzyme-linked immunosorbent assay (ELISA). To overcome the limited machine-learning capability of smartphones, the region-of-interest (ROI) cascading and conditional activation algorithms were utilized herein. The developed microfluidic chip was incorporated with a bubble trap to remove any bubbles detected by AI, which helps in preventing false signals during immunoassay, as well as controlling the reagents' movement with an on-chip micropump and valve. Subsequently, the developed immunosensing platform was tested for conducting real ELISA using a single microplate from the 96-well to detect the Human Cardiac Troponin I (cTnI) biomarker, with a detection limit as low as 0.98 pg/mL. As a result, the developed platform can be envisaged as an AI-based revolution in microfluidics for point-of-care clinical diagnosis.

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