STATISTICAL, DIAGNOSTIC AND RESPONSE SURFACE ANALYSIS OF NEFOPAM HYDROCHLORIDE NANOSPHERES USING 35 BOX-BEHNKEN DESIGN
Keywords:
Nefopam hydrochloride, Polyacrylate, Diagnostic analysis, Standardized Pareto chart, Desirability functionAbstract
Objective: Objective of the current investigation was to analyze effects of operating conditions on characteristics of nefopam hydrochloride nanospheres (NFH-NS). Statistical assessment and diagnostic analysis examined an adequacy and reliability of models.
Methods: NFH-NS were developed by quasi solvent diffusion technique using poly (meth) acrylates by 35 Box-Behnken design. Drug: polymer ratio (X1), surfactant concentration (X2), stirring time (X3), DP/CP Ratio (X4) and stirring speed (X5) were selected as independent variables. Response variables investigated were % entrapment efficiency (% EE), mean particle size, % process yield and % drug loading (% DL).
Results: Standardized Pareto chart illustrated that X1 and X5 were important factors (p<0.05) affecting response parameters of nanospheres. Significant model F-value (p<0.05) and non-significant lack of fit F-value (p>0.05) epitomized an accuracy of data. Smaller value of predicted residual error sum of squares (PRESS) for regression models stipulated good fit of models. Diagnostic analysis proved normality of data and signified that actual values of response parameters were in agreement with predicted values. Graphical analysis concluded that X1, X2, X4 and X5 had the significant positive effect on % EE. X1 and X5 produced remarkable synergistic and antagonistic effect on mean particle size, respectively. X1 and X5 exhibited positive effect on % process yield. X1 produced significant antagonistic effect on % DL.
Conclusion: Optimization report concluded that formulation prepared with 1:3 drug: polymer ratio (w/w), 2 % (w/v) surfactant, 3.8 h stirring time, 1:12 DP/CP ratio and 2000 rpm stirring speed was having highest desirability function of 0.920. Regression models indicated good fit of model, adequate model discrimination and concluded that models can be used to navigate design space.
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