Open AccessUSING A SIMPLEX CENTROID DESIGN AND FATTY ACIDS TO OPTIMIZE FLUCONAZOLE-LOADED SOLID LIPID NANOPARTICLES (SLNs)
Author(s) -
Pakorn Kraisit,
Namon Hirun,
Premjit Limpamanoch,
Sontaya Limmatvapirat
Publication year - 2021
Publication title -
international journal of applied pharmaceutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.238
H-Index - 15
ISSN - 0975-7058
DOI - 10.22159/ijap.2021v13i6.42789
Subject(s) - solid lipid nanoparticle , stearic acid , dispersity , zeta potential , particle size , chemistry , chromatography , fatty acid , palmitic acid , centroid , nanoparticle , mathematics , materials science , organic chemistry , nanotechnology , geometry
Objective: This study aimed to prepare fluconazole (FZ)-loaded solid lipid nanoparticles (SLNs) using a simplex centroid design and fatty acids to optimize the SLNs to get small-sized nanoparticles with a narrow distribution.Methods: Hot emulsification was used to prepare the FZ-loaded SLNs. Stearic acid (Sa) (X1), palmitic acid (Pa) (X2), and myristic acid (Ma) (X3) were the solid lipids. The effect of various types and amounts of fatty acids on the particle size, polydispersity index, zeta potential, and pH of the SLNs was studied using the simplex centroid design.Results: The particle size of all formulations ranged between 16.49 nm and 56.65 nm, and the polydispersity index (PDI) ranged between 0.258 and 0.676, indicating a relatively narrow size distribution. The zeta potential ranged from–7.47 to–12.2 mV. The pH was around 4.63–4.77, indicating that the SLN system was a weak acid. Design-Expert® software was used to design the responses of all model formulations and to select the optimized formulation. The optimal formulation comprised 0.190 g Sa, 0.048 g Pa, and 0.002 g Ma. The experimental values of the particle size and PDI of the optimal formulation did not differ significantly from the predicted values and lay within a 95% confidence interval (CI).Conclusion: Therefore, the simplex centroid design using fatty acids could efficiently formulate and optimize FZ-loaded SLNs.