Orthogonal and Robust Analytics Enable Reproducible and Scalable Manufacturing of High Purity Extracellular Vesicles Derived from Mesenchymal Stromal Cells

The development of extracellular vesicle (EV) based therapeutics requires robust analytical assays and scalable downstream processing (DSP) strategies to ensure product quality and reproducibility. In this study, we established an analytical toolbox comprising scattering and fluorescence mode nanoparticle tracking analysis (NTA), fluorescence-based flow cytometry (Fl-FC), and multi-detector analytical size exclusion chromatography. Liposomes, selected for their physicochemical similarity to EVs, were used as reference materials to optimize assay parameters, fluorescence labeling conditions, and dynamic range, minimizing artifacts such as photobleaching and masking effects. Using these optimized analytical tools, we designed a scalable DSP workflow for human bone marrow mesenchymal stromal cell (hBM-MSC) derived EVs, incorporating clarification, tangential flow filtration (TFF), ion exchange chromatography (IEX), buffer exchange, and sterile filtration. IEX chromatography resulted in the elution of two cell-secreted populations, with similar scattering signals while eluate 1 showed approximately 30 times higher absorbance signal compared to eluate 2. Transmission electron microscopy revealed that eluate 1 contained non-vesicular extracellular particles (NVEPs), and eluate 2 was enriched in EVs and showed higher expression of positive markers such as CD81 and CD73 using Simple Western. Additionally, the two IEX eluates showed different proteomic and lipidomic profiles. Then the analytical toolbox was utilized to monitor the DSP process in terms of particle recovery and impurity removal throughout the process determining the high purity level of the final EV preparation. Together, these results demonstrate that orthogonal analytics coupled to a scalable DSP yield reproducible MSC-EV preparations while depleting commonly co-isolated NVEPs. This practical framework advances process analytics of MSC-EV manufacturing and supports reporting of identity, purity, and function aligned with existing guidelines in the field.