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.