Extracellular vesicles (EVs) represent small, membrane-enclosed particles that are derived from parent cells and are secreted into the extracellular space. Once secreted, EVs can then travel and communicate with nearby or distant cells. Due to their inherent stability and biocompatibility, these particles can effectively transfer RNAs, proteins, and chemicals/metabolites from parent cells to target cells, impacting cellular and pathological processes. EVs have been shown to respond to disease-causing agents and impact target cells. Given that disease-causing agents span environmental contaminants, pathogens, social stressors, drugs, and other agents, the translation of EV methods into public health is now a critical research gap. This paper reviews approaches to translate EVs into exposure science, toxicology, and public health applications, highlighting blood as an example due to its common use within clinical, epidemiological, and toxicological studies. Approaches are reviewed surrounding the isolation and characterization of EVs and molecular markers that can be used to inform EV cell-of-origin. Molecular cargo contained within EVs are then discussed, including an original analysis of blood EV data from Vesiclepedia. Methods to evaluate functional consequences and target tissues of EVs are also reviewed. Lastly, the expanded integration of these approaches into future public health applications is discussed, including the use of EVs as promising biomarkers of exposure, effect, and disease. IMPACT STATEMENT:• Extracellular vesicles (EVs) represent small, cell-derived structures consisting of molecules that can serve as biomarkers of exposure, effect, and disease. •This review lays a novel foundation for integrating EVs, a rapidly advancing molecular biological tool, into the field of public health research including epidemiological, toxicological, and clinical investigations.• This article represents an important advancement in public health and exposure science as it is among the first to translate EVs into this field.