Statistical design for formulation optimization of hydrocortisone butyrate-loaded PLGA nanoparticles.

The aim of this investigation was to develop hydrocortisone butyrate (HB)-loaded poly(D,L-lactic-co-glycolic acid) (PLGA) nanoparticles (NP) with ideal encapsulation efficiency (EE), particle size, and drug loading (DL) under emulsion solvent evaporation technique utilizing various experimental statistical design modules. Experimental designs were used to investigate specific effects of independent variables during preparation of HB-loaded PLGA NP and corresponding responses in optimizing the formulation. Plackett-Burman design for independent variables was first conducted to prescreen various formulation and process variables during the development of NP. Selected primary variables were further optimized by central composite design. This process leads to an optimum formulation with desired EE, particle size, and DL. Contour plots and response surface curves display visual diagrammatic relationships between the experimental responses and input variables. The concentration of PLGA, drug, and polyvinyl alcohol and sonication time were the critical factors influencing the responses analyzed. Optimized formulation showed EE of 90.6%, particle size of 164.3 nm, and DL of 64.35%. This study demonstrates that statistical experimental design methodology can optimize the formulation and process variables to achieve favorable responses for HB-loaded NP.