Technical Name Revolutionary CAR-sEV: Non-Genetically Modified Targeted Stem Cell-Derived Exosome Drugs for Precision Medicine Applications
Project Operator National Taiwan University, College of Medicine
Project Host 王惠鈞
Summary
The study integrates metabolic glycoengineering in serum-free cultured MSCs to present azide groups on the surface of MSC-derived extracellular vesicles (EVs). Through SPAAC click chemistry, DBCO molecules are attached, and a single-chain antibody fragment (scFv) targeting the liver receptor ASGR1 is designed for modification. This establishes a high-quality, precise, and cost-effective non-genetic modification platform for CAR-sEV, enhancing the targeting capability and therapeutic efficiency.
Scientific Breakthrough
This technology overcomes the lack of targeting specificity in extracellular vesicles (EVs). By applying metabolic glycoengineering and SPAAC click chemistry, azide-labeled EVs from MSCs are conjugated with ASGR1-targeting scFv to generate CAR-sEVs. This non-genetic method improves liver targeting and enhances therapeutic effects in a liver injury model. The approach preserves EV integrity and offers a safe, modular, and scalable strategy for precision, cell-free delivery.
Industrial Applicability
CAR-sEV technology creates a cell-free, targeted delivery platform for cell/gene therapies and vaccines. Using mild, metal-free SPAAC click chemistry with EV purification, it supports scalable manufacturing. Modular scFv swapping enables liver (ASGR1), neurological (TransferrinR), cancer (PD-L1/EGFR), and cardiovascular (VCAM-1) applications. Flexible licensing and OEM partnerships accelerate market entry. Biocompatible, low-immunogenic, and customizable, it meets precision delivery demands.
Keyword Extracellular vesicles (EVs) precision drug delivery click chemistry metabolic glycoengineering single-chain variable fragment (scFv) liver-targeting technology non-genetically modified vectors nanomedicine platform regenerative medicine technology cell-free therapeutic strategy
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  • Thai-Yen Ling