The Extracellular vesicles (EV) field is growing due to increased interest in their roles in diagnostics and therapeutics. Current methods to purify and quantify EV’s take a long time, introduce a bias, are costly and imprecise, thereby hampering advancement in the EV R&D field, while the lack of methods to quantify EVs directly in crude samples restricts applications in diagnostic and bioprocessing.
The main pain for EV R&D community (both academic and industrial) is a lack of standardized EV tools that allow a user-friendly, time-and cost-efficient EV isolation, quantification and characterization. Inconsistency in non-standardized methodologies for the reproducible isolation, quantification and characterization of EVs is a major
pain that hampers rapid advancement in EV research. Diagnostics save lives in cancer and cardiovascular diseases. Earlier diagnosis reduces testing need and disease severity, while stratification efficiently selects an effective treatment. Extracellular vesicles (EV) show potential in significantly reducing the associated healthcare costs by >5% but method inconsistency for EV isolation and analysis in crude samples is hampering progress in EV R&D and diagnostics.
Current solutions are characterized by high variability, poor sensitivity, biased sample preparation and characterization, long, unreproducible, and inaccurate protocols blocking accurate and unbiased EV isolation and quantification analysis. EV isolation is traditionally based on filters and/or ultracentrifugation (UC). These protocols are labor-intensive, variable and slow with questionable integrity and purity. These existing solutions were either not specifically designed for EV handling and characterization, or fall short in being able to handle the sample matrices, the performance of the solution and the ability to link the different characterization techniques. This unreliable EV quantification obtained from biased samples restricts EV use in R&D and diagnostics to qualitative decisions at best. Current EV quantification and characterization tools thus impair clinical insights. There is a pressing need to quantify EV during isolation and quantify their molecular contents to provide relevant information. KOLs in the EV field, involved in this project, are aware of this and at the forefront of addressing this.
