SBIR Phase I: COVID-19 Rapid Sensing Using Structural DNA Biosensor
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$248,368Funder
National Science Foundation (NSF)Principal Investigator
Xiaohu YaoResearch Location
United States of AmericaLead Research Institution
ATOM BIOWORKS INCResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Diagnostics
Special Interest Tags
Innovation
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the development of a new rapid COVID-19 virus diagnostic system that recognizes specific virus surface characteristics and generates accurate results within minutes. The current viral diagnostics standard involves complex instruments and technical expertise to run, taking hours to produce and interpret a result. The proposed technology is a sensor that selectively interacts with the COVID-19 virus to produce visible results without expensive instruments or time-consuming procedures. The fundamental technology can also be adapted to rapidly and cheaply develop new diagnostic tests. The lower cost of the test and faster sample-to-result time will greatly improve disease measurement and control, supporting public health needs.
This project proposes to develop a highly functional, sensitive and specific diagnostic for the diagnosis of coronavirus based on a Pattern-Recognition Enhanced Sensing and Therapeutics (PEST) concept. The proposed diagnostic solution uses algorithmically designed structural DNA to form a trap that will detect the ?signature pattern? of the pathogen and selectively bind to it to generate a signal, without the need of DNA/RNA preprocessing or amplification associated with the current state of practice. The proposed work is to build a pre-clinical prototype of PEST-enabled lateral flow-based COVID-19 rapid diagnostics; the technical performance goal is a sample-to-result time of 5 minutes. The proposed work will also perform pre-clinical validation to validate its specificity and detection limit, as well as implement mechanisms to improve the assay specificity to avoid cross-reaction to other virus types in the Coronavirus family.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
This project proposes to develop a highly functional, sensitive and specific diagnostic for the diagnosis of coronavirus based on a Pattern-Recognition Enhanced Sensing and Therapeutics (PEST) concept. The proposed diagnostic solution uses algorithmically designed structural DNA to form a trap that will detect the ?signature pattern? of the pathogen and selectively bind to it to generate a signal, without the need of DNA/RNA preprocessing or amplification associated with the current state of practice. The proposed work is to build a pre-clinical prototype of PEST-enabled lateral flow-based COVID-19 rapid diagnostics; the technical performance goal is a sample-to-result time of 5 minutes. The proposed work will also perform pre-clinical validation to validate its specificity and detection limit, as well as implement mechanisms to improve the assay specificity to avoid cross-reaction to other virus types in the Coronavirus family.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.