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A computational simulation platform for designing real-time monitoring systems with application to COVID-19
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Shahbazi, Fatemeh, Jabbari, Masoud, Esfahani, Mohammad Nasr and Keshmiri, Amir (2021) A computational simulation platform for designing real-time monitoring systems with application to COVID-19. Biosensors and Bioelectronics, 171 . 112716. doi:10.1016/j.bios.2020.112716 ISSN 0956-5663.
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Official URL: https://doi.org/10.1016/j.bios.2020.112716
Abstract
With the aim of contributing to the fight against the coronavirus disease 2019 (COVID-19), numerous strategies have been proposed. While developing an effective vaccine can take months up to years, detection of infected patients seems like one of the best ideas for controlling the situation. The role of biosensors in containing highly pathogenic viruses, saving lives and economy is evident. A new competitive numerical platform specifically for designing microfluidic-integrated biosensors is developed and presented in this work. Properties of the biosensor, sample, buffer fluid and even the microfluidic channel can be modified in this model. This feature provides the scientific community with the ability to design a specific biosensor for requested point-of-care (POC) applications. First, the validation of the presented numerical platform against experimental data and then results and discussion, highlighting the important role of the design parameters on the performance of the biosensor is presented. For the latter, the baseline case has been set on the previous studies on the biosensors suitable for SARS-CoV, which has the highest similarity to the 2019 nCoV. Subsequently, the effects of concentration of the targeted molecules in the sample, installation position and properties of the biosensor on its performance were investigated in 11 case studies. The presented numerical framework provides an insight into understanding of the virus reaction in the design process of the biosensor and enhances our preparation for any future outbreaks. Furthermore, the integration of biosensors with different devices for accelerating the process of defeating the pandemic is proposed.
Item Type: | Journal Article | ||||||||
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Library of Congress Subject Headings (LCSH): | Microfluidics, Biosensors, Computational fluid dynamics | ||||||||
Journal or Publication Title: | Biosensors and Bioelectronics | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 0956-5663 | ||||||||
Official Date: | 1 January 2021 | ||||||||
Dates: |
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Volume: | 171 | ||||||||
Article Number: | 112716 | ||||||||
DOI: | 10.1016/j.bios.2020.112716 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 28 November 2022 | ||||||||
Date of first compliant Open Access: | 28 November 2022 | ||||||||
RIOXX Funder/Project Grant: |
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