The project generated several important outputs. A liposome-based model was developed as a controllable test system for RNA topology studies, enabling method validation and optimization. Workflows were established for detecting RNA on the vesicle surface (flow cytometry) and for probing internal RNA localization (super-resolution microscopy), with further optimization ongoing. Automated quality-control software for flow cytometry instruments was developed during the non-academic placement and has already been implemented in the host laboratory to improve data quality and efficiency. In addition, the project generated novel methodological insights with potential to improve the reproducibility of extracellular vesicle isolation and downstream biomarker studies, which will be reported in future publications.
The potential impacts of these results include advancing the scientific understanding of EV-RNA topology, improving reproducibility in biomarker research, and providing practical tools for quality assurance in flow cytometry. These outcomes are relevant for both academic researchers and translational applications in biomarker development. For further uptake and success, continued research and validation in patient-derived samples will be required, as well as wider dissemination of the workflows and software tools. Future steps may include the integration of these methods into standardization frameworks (e.g. MISEV, EV-TRACK, MIFlowCyt-EV, MIBloodEV) and engagement with the EV community to ensure adoption. At this stage, no IPR opportunities were pursued, but potential commercial applications have already been explored through a collaboration with an industrial partner on the development of filters to improve sample preparation by removing residual platelets.