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

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

• Level A · Stronger Clinical Evidence
• Level B · Emerging clinical evidence with positive signals
• Level C · Early human research exploring benefits
• Level D · Scientific groundwork from lab and animal studies
• Emerging · Emerging topic under active research

Abstract (original English)

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 o

Evidence level

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

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