Label-Free Clustering Analysis Platform Drives Cascaded Workflow for Scalable Production of Therapeutic Extracellular Vesicles.

Abstract

Extracellular vesicles (EVs) have emerged as highly promising natural nanomedicines and nanocarriers, holding transformative potential for the treatment of various diseases. However, the lack of rapid and comprehensive characterization techniques for EV preparation analysis, coupled with the absence of efficient quality control methods, significantly hinders process optimization and large-scale production. To address these challenges, we developed a label-free clustering analysis (LFCA) platform that integrates nano-flow cytometry for particle size distribution analysis with a clustering algorithm to deconvolute EV subpopulations and distinguish them from impurities. This platform enables the rapid quantification of EV component distribution and composition within 5 min using minimal sample input. Leveraging the high-throughput capabilities of LFCA, we established a cascaded workflow incorporating a microcarrier-based 3D culture system, a custom tangential flow filtration device, and multimodal size exclusion chromatography for EV preparation from adipose mesenchymal stem cells. This approach achieves a 4-fold increase in EV yield compared to ultracentrifugation while maintaining comparable purity and preserving EV integrity. Critically, the resulting EVs exhibited enhanced functional potency in pro-angiogenic and anti-inflammatory assays, confirming the clinical relevance of our optimized production system. These advancements provide a scalable solution for EV production, paving the way for clinical applications.