# Rapid at-home Detection for Serologic Status of Hepatitis C Virus (HCV) Infection

> **NIH NIH N43** · QOOLABS, INC. · 2022 · $400,000

## Abstract

Hepatitis C Virus (HCV) infection is a worldwide health concern, affecting about 3% of the world’s population. Over 2 million people in the United States have a current HCV infection, however, nearly half of them are not aware of their infection. HCV-related end stage liver disease is the leading reason for liver transplantation in the USA. Because symptoms are generally absent in individuals with chronic HCV infection, appropriate HCV testing must be linked with risk factors to allow for recognition of infection. Effective treatments for HCV infection are currently available. However, diagnosis is a bottleneck for appropriate HCV care and treatment, especially in low- and medium-income countries. 
In this project, Qoolabs proposes to develop at-home rapid test for HCV antibody detection The test will use finger prick blood samples, can be completed within 20 minutes without special instrument. The HCV antibody at-home test will be complementary with the HCV core antigen rapid tests that are being developed. With both core antigen and total antibody detection, it is feasible to achieve accurate and cost-effective at-home serodiagnostics to fulfill the need of screening large populations.

## Key facts

- **NIH application ID:** 10709149
- **Project number:** 75N91022C00028-0-9999-1
- **Recipient organization:** QOOLABS, INC.
- **Principal Investigator:** HONG QI
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $400,000
- **Award type:** —
- **Project period:** 2022-09-19 → 2023-09-18

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10709149

## Citation

> US National Institutes of Health, RePORTER application 10709149, Rapid at-home Detection for Serologic Status of Hepatitis C Virus (HCV) Infection (75N91022C00028-0-9999-1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10709149. Licensed CC0.

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