Response surface methodology for the development of self-nanoemulsified drug delivery system (SNEDDS) of all-trans-retinol acetate.

UNLABELLED

The purpose was to prepare, characterize, and optimize a self-nanoemulsified drug delivery system (SNEDDS) of a model lipophilic compound, all-trans-retinol acetate. As part of the optimization process, the main effects, interaction effects, and quadratic effects of the formulation ingredients were investigated.

METHOD

A three-factor, three-level Box-Behnken design was used to explore the quadratic response surfaces and construct a second-order polynomial model in the form: Y = A + A1X1 + A2X2+ A3X3 + A4X1X2 + A5X2X3 + A6X1X3+ A7X1(2) + A8X2(2) + A9X3(2) + E. Amount of added oil (X1), surfactant (X2), and cosurfactant (X3) were selected as the factors. Particle size (Y1), turbidity (Y2), and cumulative amount of the active ingredient emulsified after 10 (Y3) and 30 (Y4) min were the observed variables. Response surface plots were used to demonstrate the effect of factors (X1), (X2), and (X3) on the response (Y4). Amount of added soybean oil (X1), Cremophor EL (X2), and Capmul MCM-C8 (X3) showed a significant effect on the emulsification rates, as well as on the physical properties of the resultant emulsion (particle size and turbidity). Observed and predicted values of Y4 obtained from the constructed equations were in close agreement. Response surface methodology was then used to predict the levels of factors X1, X2, and X3 under the constrained variables for an optimum response. Applied constraints were 0 < Y1 < 0.5, 1 < Y2 < 20, 60 < Y3 < 80, and 90 < Y4 < 100. The predicted values were 0.0704 microm for particle size (Y1), 18.95 NTU for turbidity (Y2), 88.88% for drug release after 10 min (Y3), and 110.7% drug release after 30 min (Y4). Two new formulations were prepared according to the predicted levels. The observed and predicted values were in close agreement.