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Extracellular vesicles (EVs) are secreted by most cell types and play a central role in cell-cell communication. These naturally occurring nanoparticles have been particularly implicated in cancer, but EV heterogeneity and lengthy isolation methods with low yield make them difficult to study. To circumvent the challenges in EV research, we aimed to develop a unique synthetic model by engineering bioinspired liposomes to study EV properties and their impact on cellular uptake. We produced EV-like liposomes mimicking the physicochemical properties as cancer EVs. First, using a panel of cancer and non-cancer cell lines, small EVs were isolated by ultracentrifugation and characterized by dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA). Cancer EVs ranged in mean size from 107.9 to 161 nm by NTA, hydrodynamic diameter from 152 to 355 nm by DLS, with a zeta potential ranging from - 25 to -6 mV. EV markers TSG101 and CD81 were positive on all EVs. Using a microfluidics bottom-up approach, liposomes were produced using the nanoprecipitation method adapted to micromixers developed by our group. A library of liposome formulations was created that mimicked the ranges of size (90-222 nm) and zeta potential (anionic [-47 mV] to neutral [-1 mV]) at a production throughput of up to 41 mL/h and yielding a concentration of 1 × 10¹² particles per mL. EV size and zeta potential were reproduced by controlling the flow conditions and lipid composition set by a statistical model based on the response surface methodology. The model was fairly accurate with an R-squared > 70% for both parameters between the targeted EV and the obtained liposomes. Finally, the internalization of fluorescently labeled EV-like liposomes was assessed by confocal microscopy and flow cytometry, and correlated with decreasing liposome size and less negative zeta potential, providing insights into the effects of key EV physicochemical properties. Our data demonstrated that liposomes can be used as a powerful synthetic model of EVs. By mimicking cancer cell-derived EV properties, the effects on cellular internalization can be assessed individually and in combination. Taken together, we present a novel system that can accelerate research on the effects of EVs in cancer models.