# The HIV-Stick Assay: A Rapid, Molecular Detection Approach for Self-Monitoring HIV-1 Rebound Infection

> **NIH NIH N43** · DARWIN BIOSCIENCES, INC. · 2024 · $299,408

## Abstract

Rapid Diagnostic Assays for Self-Monitoring of Acute or Rebound HIV-1 Infection: The goal of this program is to develop low-cost, rapid diagnostic assays needed to enable untrained individuals to test for HIV-1 infection during the earliest stages of initial infection or during loss of viral suppression in chronic treated infection – times when antibody responses are not an accurate surrogate for viral load. Assays will be designed for self-testing at home (or in other locations), so that individuals collect their own samples, perform the test, and read the results without the need to send a sample to a laboratory. The assay should be easy to be carried out and designed for use by individuals who are at risk of HIV infection, including those taking pre-exposure prophylaxis (PrEP), who wish to detect HIV infection as early as possible, as well as people living with HIV (PLWH) who wish to detect viral spikes or rebound either while on antiretroviral therapy or during treatment interruption. The goal of this contract is to develop a self-administered nucleic acid amplification test with high sensitivity and specificity for monitoring HIV-1 rebound infection and identifying early HIV-1 infection.

## Key facts

- **NIH application ID:** 11172344
- **Project number:** 75N93024C00029-0-9999-1
- **Recipient organization:** DARWIN BIOSCIENCES, INC.
- **Principal Investigator:** Nicholas Ryan Meyerson
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $299,408
- **Award type:** —
- **Project period:** 2024-08-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11172344

## Citation

> US National Institutes of Health, RePORTER application 11172344, The HIV-Stick Assay: A Rapid, Molecular Detection Approach for Self-Monitoring HIV-1 Rebound Infection (75N93024C00029-0-9999-1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11172344. Licensed CC0.

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