A bottom-up approach based on a solvent displacement technique was used for the production of atocopherol nanodispersions. Response surface methodology was utilized to study the effect of the mixing conditions of organic and aqueous phases, namely, mixing speed (1 9 100-6 9 100 rpm) and mixing time (30-150 s) on the average particle size (nm), polydispersity index and atocopherol concentration (mg/L) of the nanodispersions. Second order regression models, with high coefficient of determination values (R 2 [ 0.94 and adjusted R 2 [ 0.79), were significantly (p \ 0.05) fitted for predicting the atocopherol nanodispersion characteristics as functions of mixing parameters. A multiple optimization procedure presented the optimum mixing speed and time as 3.8 9 100 rpm and 70 s, respectively. The statistically insignificant differences between experimental and predicted values of studied responses, verified the satisfactoriness of the models found for explaining the variation of produced nanodispersions, as a function of mixing conditions.

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Abstract. α-Tocopherol is the main compound of vitamin E with great antioxidant activity. However, like other functional lipid bioactive compounds, it suffers from low bioavailability due to its low water solubility and liable chemical structure. A bottom-up procedure based on a solvent-displacement method was constructed for fabrication of α-tocopherol nanodispersions using response surface methodology (RSM). The effects of main formulation parameters, namely, weight ratio of emulsifier to α-tocopherol and volumetric percent of acetone to water on the average particle size (nm), polydispersity index, concentration of α-tocopherol loss (% w/w) and turbidity of the nanodispersions were evaluated and optimized to gain the most desirable nanodispersions (least particle size, polydispersity index, turbidity and highest α-tocopherol concentrations). Second order regression equations, holding quite high coefficients of determination (R2 and adjusted R2 > 0.882), were significantly (p-value < 0.05) fitted for predicting the α-tocopherol nanodispersion characteristics variations as functions of studied formulation parameters. A multiple optimization analysis offered 6.5 and 10% for weight ratio of Tween 20 to α-tocopherol and volume percent of acetone, respectively, as overall optimum values for studied parameters. Statistically insignificant differences between experimental and predicted values of studied responses, verified the satisfactoriness of presented models for explaining the response characteristics as a function of formulation parameters. Thus, the employed solvent-displacement technique may provide the most desired water dispersible α-tocopherol nanoparticles for several water-based foods, cosmetic nutraceutical formulations.