# Multi-omics profiling of individual exosomes for origin-tracing, biomarker discovery, and biological function characterization

> **NIH NIH R44** · WELLSIM BIOMEDICAL TECHNOLOGIES, INC. · 2024 · $801,485

## Abstract

PROJECT SUMMARY / ABSTRACT
Extracellular vesicles (EVs) exhibit high heterogeneity in biofluids, a feature that traditional bulk-level analysis
approaches fail to capture in terms of individual variations. While numerous techniques exist for single-EV
analysis, the majority focus primarily on profiling surface proteins. Transcriptional analysis at the level of
individual EVs, however, remains largely unexplored. To bridge this gap, we propose the development of a
technology for multimodal profiling of individual EVs, leveraging next-generation sequencing and an optimized
method for multiplex library preparation. This proposed platform will serve as a unique tool for high-throughput,
integrative profiling of single-EV gene expression and surface proteins. It aims to offer high-sensitivity, multi-
dimensional biological insights, thereby potentially accelerating the advancement of EV-based diagnostics and
targeted therapies.

## Key facts

- **NIH application ID:** 10919626
- **Project number:** 2R44GM145015-02A1
- **Recipient organization:** WELLSIM BIOMEDICAL TECHNOLOGIES, INC.
- **Principal Investigator:** Yuchao Chen
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $801,485
- **Award type:** 2
- **Project period:** 2022-03-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10919626

## Citation

> US National Institutes of Health, RePORTER application 10919626, Multi-omics profiling of individual exosomes for origin-tracing, biomarker discovery, and biological function characterization (2R44GM145015-02A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10919626. Licensed CC0.

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