Design and Optimization of Floating Microspheres Using Abelmoschus esculentus Natural Polymer

Abstract

The main objective of the present research study was to fabricate Vildagliptin floating microspheres by ionotropic gelation using natural polymer, Abelmoschus esculentus obtained from the fruits of Abelmoschus esculentus in combination with sodium alginate. Microspheres were prepared and optimized using central composite rotatable design model using design expert software version 12 .The study is focussed on the interaction effects of the three independent variables, natural polymer concentration, sodium alginate concentration and crosslinker concentration, optimization of formulations response surface methodology was used . drug –excipient compatibility studies were carried out by infrared spectroscopic studies. Infrared spectroscopic studies clearly shown that drug and excipients were compatible. Totally 15 formulations were generated taking 8 factorial points, 6 axial points and 1 centre point. Response surface methodology was used to optimize the formulations. To investigate the responses %cumulative drug release, floating time and floating lag time Response surface methodology was used Polynomial equations and model plots of 3 dimensional model surface plots were generated. Vildagliptin optimized microspheres were formulated and a second order, model quadratic model was used to study influence of formulation factors on response variables. Experimental data of Statistical analysis exhibited good coefficient of regression for cumulative in vitro drug release Regression F –ratios for the experimental variables were significant. The experimental values and predicted values are agreed. All fifteen formulations exhibited % yield of 94.35-99.99%, particle size of 124-441µm, %swelling index 64.52-89.65%, floating time of 10.16 to 13.16 and floating lag time of 30.31 to 46.98 sec. F4 formulation is optimized based on cumulative % in-vitro drug release at 2nd hour, 12th hour, floating lag time and floating time values. Predicted and observed results are in agreement 95% confidence intervals. Based on investigation, RSM is the good tool for optimization of formulations.