Implementation of experimental design methodology in preparation and characterization of zolmitriptan loaded chitosan nanoparticles
DOI:
https://doi.org/10.3329/icpj.v6i3.32684Keywords:
Factorial design, regression, nanoparticles, chitosan, zolmitriptanAbstract
The present study investigated the implementation of 32 factorial design of experiment and statistical analysis for the optimization of chitosan nanoparticles containing zolmitriptan an antimigraine drug. The influence of chitosan concentration (X1) and sodium tripoly phosphate (X2) on responses namely nanoparticle size (Y1), and entrapment efficiency (Y2), was studied. As per design, nine runs of nanoparticles were prepared by modified ionic gelation method using high speed vortex mixing. The particle size was found in the range of 151-880 nm and entrapment efficiency was 72.3-81.2%. A statistical analysis was performed using licensed design expert software V.8.0 with respect to ANOVA, regression analysis. The contour plots and response surface plots showed visual representation of relationship between the experimental responses and the set of independent variables. Regression model equations were validated by a numerical and graphical optimization method. Further, optimized drug loaded nanoparticles showed +23.7mV zeta potential indicating storage stability, electron micrograph reflects spherical shape and mixed type of drug release followed by Fickian diffusion (n=0.266) was observed. Thus, using systematic factorial design approach, desirable goals can be achieved in shortest possible time with lesser number of experiments which was proven to be an effective tool in quality by design.
Mandlik and Ranpise, International Current Pharmaceutical Journal, February 2017, 6(3): 16-22
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