# A Reaction- Diffusion-Based Approach for Nucleic Acid Quantification

> **NIH NIH R01** · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · 2020 · $331,006

## 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 organization:** UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
- **Principal Investigator:** Changchun Liu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $331,006
- **Award type:** 3
- **Project period:** 2020-06-10 → 2022-06-09

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10152033

## Citation

> US National Institutes of Health, RePORTER application 10152033, A Reaction- Diffusion-Based Approach for Nucleic Acid Quantification (3R01EB023607-05S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10152033. Licensed CC0.

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