Response surface methodology (RSM) was utilized to investigate the influence of the main emulsion composition; mixture of palm and medium-chain triglyceride (MCT) oil (6%–12% w/w), lecithin (1%–3% w/w), and Cremophor EL (0.5%–1.5% w/w) as well as the preparation method; addition rate (2–20 mL/min), on the physicochemical properties of palm-based nanoemulsions. The response variables were the three main emulsion properties; particle size, zeta potential and polydispersity index. Optimization of the four independent variables was carried out to obtain an optimum level palm-based nanoemulsion with desirable characteristics. The response surface analysis showed that the variation in the three responses could be depicted as a quadratic function of the main composition of the emulsion and the preparation method. The experimental data could be fitted sufficiently well into a second-order polynomial model. The optimized formulation was stable for six months at 4 °C.
Palm kernel oil esters nanoemulsion-loaded with chloramphenicol was optimized using response surface methodology (RSM), a multivariate statistical technique. Effect of independent variables (oil amount, lecithin amount and glycerol amount) toward response variables (particle size, polydispersity index, zeta potential and osmolality) were studied using central composite design (CCD). RSM analysis showed that the experimental data could be fitted into a second-order polynomial model. Chloramphenicol-loaded nanoemulsion was formulated by using high pressure homogenizer. The optimized chloramphenicol-loaded nanoemulsion response values for particle size, PDI, zeta potential and osmolality were 95.33nm, 0.238, -36.91mV, and 200mOsm/kg, respectively. The actual values of the formulated nanoemulsion were in good agreement with the predicted values obtained from RSM. The results showed that the optimized compositions have the potential to be used as a parenteral emulsion to cross blood-brain barrier (BBB) for meningitis treatment.
Response surface methodology (RSM) was used to optimize the formulation of a nanoemulsion for central delivery following parenteral administration. A mixture of medium-chain triglyceride (MCT) and safflower seed oil (SSO) was determined as a sole phase from the emulsification properties. Similarly, a natural surfactant (lecithin) and non-ionic surfactant (Tween 80) (ratio 1:2) were used in the formulation. A central composite design (CCD) with three-factor at five-levels was used to optimize the processing method of high energy ultrasonicator. Effects of pre-sonication ultrasonic intensity (A), sonication time (B), and temperature (C) were studied on the preparation of nanoemulsion loaded with valproic acid. Influence of the aforementioned specifically the effects of the ultrasonic processing parameters on droplet size and polydispersity index were investigated. From the analysis, it was found that the interaction between ultrasonic intensity and sonication time was the most influential factor on the droplet size of nanoemulsion formulated. Ultrasonic intensity (A) significantly affects the polydispersity index value. With this optimization method, a favorable droplet size of a nanoemulsion with reasonable polydispersity index was able to be formulated within a short sonication time. A valproic acid loaded nanoemulsion can be obtained with 60% power intensity for 15 min at 60 °C. Droplet size of 43.21±0.11 nm with polydispersity index of 0.211 were produced. The drug content was then increased to 1.5%. Stability study of nanoemulsion containing 1.5% of valproic acid had a good stability as there are no significant changes in physicochemical aspects such as droplet size and polydispersity index. With the characteristisation study of pH, viscosity, transmission electron microscope (TEM) and stability assessment study the formulated nanoemulsion has the potential to penetrate blood-brain barrier in the treatment of epilepsy.
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