# A Label-free Extracellular-vesicle Automated Purification System (LEAP System)

> **NIH NIH R44** · WELLSIM BIOMEDICAL TECHNOLOGIES, INC. · 2022 · $749,646

## Abstract

PROJECT SUMMARY / ABSTRACT
Extracellular vesicles (EVs) are small lipid bilayer particles secreted by most cell types, which encapsulates
biomolecules including lipids, proteins, and nucleic acids from cells of origin. Profiling of EV-derived biomarkers
provides a promising approach for diagnosis of various diseases. However, one of the primary challenges for
the research and application of EVs is a lack of a reliable method for efficient isolation of EVs and their
subpopulations from complex biofluids. Researchers in this field suffer from tedious workflow, long processing
time, high cost, and poor EV quality. To overcome the challenges, WellSIM proposes in this Phase II project,
which built upon the promising results generated from our Phase I project, to complete development of a Label-
free Extracellular-vesicle Automated Purification System (LEAP System) for isolation of total EVs or EV
subpopulations from a variety of biofluids in a non-invasive and cost-effective manner. Once developed, the
integrated LEAP System will offer excellent EV quality, throughput, and flexibility for EV isolation that can
outperform ultracentrifugation and other isolation techniques.

## Key facts

- **NIH application ID:** 10546042
- **Project number:** 2R44GM144009-02
- **Recipient organization:** WELLSIM BIOMEDICAL TECHNOLOGIES, INC.
- **Principal Investigator:** Yuchao Chen
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $749,646
- **Award type:** 2
- **Project period:** 2021-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10546042

## Citation

> US National Institutes of Health, RePORTER application 10546042, A Label-free Extracellular-vesicle Automated Purification System (LEAP System) (2R44GM144009-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10546042. Licensed CC0.

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