SBIR Phase I: Using patient specific DNA methylation to predict COVID-19 clinical prognosis
SBIR Phase I: Using patient specific DNA methylation to predict COVID-19 clinical prognosis
批准号:
2034014
负责人:
Kristin Brogaard
金额:
$25.6万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-01 至 2021-09-30
中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of an onsite, clinical test to screen incoming patients potentially infected with COVID-19 and prioritize hospital resources and personnel based on a predicted infection severity and treatment response. The benefits of a test that can predict COVID-19 infection severity are enormous. In addition to the millions of infections and hundreds of thousands of dealths, it costs hospitals an average of roughly $2,500 per day per patient for inpatient care. This project will develop a test for COVID-19 screening to accurately identify patients at risk. This Small Business Innovation Research (SBIR) Phase I project is establishing the use of DNA methylation patterns for personalized screening and treatment for COVID-19. The variation in symptoms and outcomes for COVID-19 progression make it challenging for healthcare workers to triage accurately. The development of a DNA methylation-based test to predict the severity of COVID-19 infection will help manage the pandemic. This project will: 1) generate a comprehensive dataset of white blood cell DNA methylation patterns, health history, and clinical data for patients infected with COVID-19; 2) generate a predictive model for COVID-19 infection severity and treatment response. The anticipated technical results of this project are a testing method and a computer algorithm for predicting infection severity and treatment response based on a patient’s unique DNA methylation pattern.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.
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