Extracellular vesicles (EVs) are membrane-enclosed particles, which are secreted from various cell types into the extracellular space. EVs are highly heterogeneous and comprise a diverse set of surface protein markers as well as intra-vesicular cargoes, such as RNAs. Current approaches to the isolation and study of EVs lack the necessary sensitivity and precision to fully characterize and understand the make-up and the distribution of various EV subpopulations that may be present. In fact, most current EV isolation methodologies, including differential centrifugation, affinity/immuno-magnetic isolation, polymer-based precipitation, size-based exclusion, can be prone to contaminations; for example, affinity/immuno-magnetic methods can be adversely affected by non-specific interactions that can cause co-precipitation of contaminants with EVs. Additionally, these bulk techniques can only report information that is averaged over many millions of EVs, and thus cannot be used to understand the high degree of heterogeneity that exists among the EVs. Yet, understanding the diversity of EVs and the cargos they carry is an essential step towards gaining a better understanding of the precise roles EVs play in both physiological and pathophysiological processes. This understanding, in turn, is important towards realizing the potentials of EVs in diagnostics (e.g. as a new class of biomarkers) and therapeutics (e.g. as drug carriers). To address the limitations of the current methodologies, we propose to develop and apply three sets of new but related technologies for studying EVs with high-throughput at the single-EV level. These new techniques include a nanoscale flow analyzer and flow sorter for the analysis and sorting of individual EVs with high sensitivity and high throughput. Furthermore, we also plan to demonstrate an imaging digital PCR platform for quantifying the RNA contents of single EVs as well as small groups of EVs.