# Exosome-based Non-traditional Technologies Towards Multi-Parametric andIntegrated Approaches for SARS-CoV-2

> **NIH NIH U18** · JOHNS HOPKINS UNIVERSITY · 2022 · $500,000

## Abstract

Abstract
This supplement is in response to Funding Opportunity Announcement Number PA-20-272
Administrative Supplements to Existing NIH Grants and Cooperative Agreements. The
supplement application is in response to the RADx-rad announcement on the opportunity of
additional resources and funding support to facilitate the pathway to commercialization. The
opportunity was announced by the RADx-rad Data Coordination Center (DCC) and relayed
through the NIH SEED office.
The urgent need to curb the spread of SARS-CoV-2 demands availability of diagnostics that are
more rapid, accurate, sensitive and affordable than qPCR and antibody tests. Current qPCR tests
are specific and sensitive, but lengthy turnaround times limit interventions against disease spread.
Antibody testing is faster, but false-positive/negative rates are high. Here, we propose to
repurpose extracellular vesicle (EV) separation and characterization technologies into a fully
automated SARS-CoV-2 testing platform that is low-cost, accurate, sensitive, rapid (within 5 min),
and practical. The device has been optimized to analyze blood, saliva, and nasopharyngeal (NP)
swabs. However, in this proposal we will be focusing on saliva or drooling samples (25-50 ul) that
can be easily self-obtained at-home setting. The sample is processed with an automated device
developed with Sognef Inc., and data are transferred to the Sognef servers for analysis through
an app that can be downloaded to any smart device. This technology is similar to Abbott's recently
launched BinaxNOW COVID-19 Ag Card, but has the advantage of multiparametric detection of
viral RNA (vRNA), including Spike (S) and Nucleocapsid (N) protein-coding regions that reveals
infection even when viral loads are below detectable limits. This approach will decrease false-
positives/negatives, the major limitation of antigen/antibody tests.

## Key facts

- **NIH application ID:** 10666956
- **Project number:** 3U18TR003780-02S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Samarjit Das
- **Activity code:** U18 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $500,000
- **Award type:** 3
- **Project period:** 2022-09-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10666956

## Citation

> US National Institutes of Health, RePORTER application 10666956, Exosome-based Non-traditional Technologies Towards Multi-Parametric andIntegrated Approaches for SARS-CoV-2 (3U18TR003780-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10666956. Licensed CC0.

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