Wan Sarah Samiun1, Siti Efliza Ashari1,2, Norazlinaliza Salim1,2, Syahida Ahmad3. 1. Integrated Chemical Biophysics Research, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia. 2. Centre of Foundation Studies for Agricultural Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia. 3. Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia.
Abstract
BACKGROUND: Aripiprazole, which is a quinolinone derivative, has been widely used to treat schizophrenia, major depressive disorder, and bipolar disorder. PURPOSE: A Central Composite Rotatable Design (CCRD) of Response Surface Methodology (RSM) was used purposely to optimize process parameters conditions for formulating nanoemulsion containing aripiprazole using high emulsification methods. METHODS: This design is used to investigate the influences of four independent variables (overhead stirring time (A), shear rate (B), shear time (C), and the cycle of high-pressure homogenizer (D)) on the response variable namely, a droplet size (Y) of nanoemulsion containing aripiprazole. RESULTS: The optimum conditions suggested by the predicted model were: 120 min of overhead stirring time, 15 min of high shear homogenizer time, 4400 rpm of high shear homogenizer rate and 11 cycles of high-pressure homogenizer, giving a desirable droplet size of nanoemulsion containing aripiprazole of 64.52 nm for experimental value and 62.59 nm for predicted value. The analysis of variance (ANOVA) showed the quadratic polynomial fitted the experimental values with F-value (9.53), a low p-value (0.0003) and a non-significant lack of-fit. It proved that the models were adequate to predict the relevance response. The optimized formulation with a viscosity value of 3.72 mPa.s and pH value of 7.4 showed good osmolality value (297 mOsm/kg) and remained stable for three months in three different temperatures (4°C, 25°C, and 45°C). CONCLUSION: This proven that response surface methodology is an efficient tool to produce desirable droplet size of nanoemulsion containing aripiprazole for parenteral delivery application.
BACKGROUND: Aripiprazole, which is a quinolinone derivative, has been widely used to treat schizophrenia, major depressive disorder, and bipolar disorder. PURPOSE: A Central Composite Rotatable Design (CCRD) of Response Surface Methodology (RSM) was used purposely to optimize process parameters conditions for formulating nanoemulsion containing aripiprazole using high emulsification methods. METHODS: This design is used to investigate the influences of four independent variables (overhead stirring time (A), shear rate (B), shear time (C), and the cycle of high-pressure homogenizer (D)) on the response variable namely, a droplet size (Y) of nanoemulsion containing aripiprazole. RESULTS: The optimum conditions suggested by the predicted model were: 120 min of overhead stirring time, 15 min of high shear homogenizer time, 4400 rpm of high shear homogenizer rate and 11 cycles of high-pressure homogenizer, giving a desirable droplet size of nanoemulsion containing aripiprazole of 64.52 nm for experimental value and 62.59 nm for predicted value. The analysis of variance (ANOVA) showed the quadratic polynomial fitted the experimental values with F-value (9.53), a low p-value (0.0003) and a non-significant lack of-fit. It proved that the models were adequate to predict the relevance response. The optimized formulation with a viscosity value of 3.72 mPa.s and pH value of 7.4 showed good osmolality value (297 mOsm/kg) and remained stable for three months in three different temperatures (4°C, 25°C, and 45°C). CONCLUSION: This proven that response surface methodology is an efficient tool to produce desirable droplet size of nanoemulsion containing aripiprazole for parenteral delivery application.
Authors: N Joan Abbott; Adjanie A K Patabendige; Diana E M Dolman; Siti R Yusof; David J Begley Journal: Neurobiol Dis Date: 2009-08-05 Impact factor: 5.996
Authors: Jing Cui; Li Wang; Ge Ge Sun; Li Na Liu; Shuai Bing Zhang; Ruo Dan Liu; Xi Zhang; Peng Jiang; Zhong Quan Wang Journal: Acta Trop Date: 2014-11-01 Impact factor: 3.112
Authors: Steven G Potkin; Anutosh R Saha; Mary J Kujawa; William H Carson; Mirza Ali; Elyse Stock; Joseph Stringfellow; Gary Ingenito; Stephen R Marder Journal: Arch Gen Psychiatry Date: 2003-07