A Reaction- Diffusion-Based Approach for Nucleic Acid Quantification

NIH RePORTER · NIH · R01 · $331,006 · view on reporter.nih.gov ↗

Abstract

ABSTRACT The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a large global outbreak and become a major global public health concern. It is still spreading rapidly to many countries despite extensive implementation of control measures. So far, SARS-CoV-2 has affected more than 2,544,792 patients and resulted in more than 175,694 deaths all over the world. Rapid and accurate detection of novel coronavirus SARS-CoV-2, the causative agent of the coronavirus disease 2019 (COVID-19), plays a crucial role in facilitating early intervention and reducing rapid transmission of the virus. Reverse transcription polymerase chain reaction (RT-PCR)-based molecular detection is highly sensitive and specific method and has been widely used for early diagnostics of the COVID-19 disease. However, it relies on expensive instruments, and well-trained personnel, which are not suitable for point of care settings such as drive-thru testing sites, home care, small clinics with limited infrastructure and resources. Here, we propose to develop and validate a rapid, low cost, CRISPR-based molecular detection technology for early diagnostics of the COVID-19 disease at the point of care. To achieve the goal, we have assembled a highly interdisciplinary research team (e.g., bioengineer, clinician, virologist and industry partner). We will use this supplemental project to generate preliminary data to: i) develop and optimize our point of care diagnostic technology for SARS-CoV-2 detection, and ii) evaluate and validate the clinical feasibility of our technology for early diagnostics of the COVID-19 disease by using COVID-19 patient samples. The pilot-test data obtained in this project will provide a basis for future large-scale research and commercial applications. If successful, such simple and rapid diagnostic technology will open a new pathway for cost-effective, molecular detection of the COVID-19 disease at the point of care.

Key facts

NIH application ID
10152033
Project number
3R01EB023607-05S1
Recipient
UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
Principal Investigator
Changchun Liu
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$331,006
Award type
3
Project period
2020-06-10 → 2022-06-09