Immunity testing against COVID-19 from blood by an IoT-enabled and AI-controlled multiplexed microfluidic platform
Developing herd immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pivotal for changing the course of the coronavirus disease 2019 (COVID-19) pandemic. However, the uncertainty of vaccine-induced immunity development and inequitable distribution of vaccines hinders the...
Saved in:
Published in | Biosensors & bioelectronics Vol. 244; p. 115791 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
15.01.2024
|
Online Access | Get full text |
Cover
Loading…
Summary: | Developing herd immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pivotal for changing the course of the coronavirus disease 2019 (COVID-19) pandemic. However, the uncertainty of vaccine-induced immunity development and inequitable distribution of vaccines hinders the global vaccination effort. Therefore, routine serodiagnosis and ensuring effective vaccination on a time-to-time basis are essential for developing sustainable immunity against SARS-CoV-2. Herein, an AI-driven multiplexed point-of-care testing (POCT) platform capable of utilizing a microfluidic lab-on-a-chip (LOC) device has been proposed for analyzing bodily fluid response against SARS-CoV-2. The developed platform has been successfully utilized for the quantification of SARS-CoV-2 S-protein, N-protein, IgM, and IgG from human blood samples with limits of detection (LODs) as low as 0.01, 0.02, 0.69, and 0.61 ng/mL respectively. Finally, a data-receptive web-based dashboard system has been developed and demonstrated to provide real-time, territory-specific analysis of herd immunity progress from the test results. Thus, the proposed platform could be an imperative tool for healthcare authorities to analyze and restrain ongoing COVID-19 outbreaks or similar pandemics in the future by ensuring effective immunization. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0956-5663 1873-4235 |
DOI: | 10.1016/j.bios.2023.115791 |