Design, optimization and in vitro characterization of valsartan loaded floating tablets
Department of Pharmaceutics, V.L. College of Pharmacy, Raichur, Karnataka, India.
Review Article
GSC Biological and Pharmaceutical Sciences, 2024, 29(03), 373-385.
Article DOI: 10.30574/gscbps.2024.29.3.0433
Publication history:
Received on 06 October 2024; revised on 18 November 2024; accepted on 21 November 2024
Abstract:
The present work was aim to design and optimize floating drug delivery systems of Valsartan using HPMC K15M, HPMC K100M, Guar gum as polymer and sodium bicarbonate as a gas generating agent. The tablets were prepared by direct compression method. Response surface methodology (RSM) was adapted using Box Behnken Design (BBD) using amount of HPMC K15M (X1), HPMC K100M (X2) and Guar gum (X3) were selected as independent variables, buoyancy time (Y1) and t50 (Y2) selected as dependent variables. All the designed 15 trial batches of formulations were evaluated for precompression, postcompression, drug content uniformity, swelling index, in vitro buoyancy, floating period and in vitro drug release profile. The response data were analyzed by using Design Expert software trial V13 to study the influence of independent variables on dependent variables. Point prediction method was adapted to generate optimized formulation with predicted response values within the design space. Validity of the developed polynomial equation was verified by experimenting the optimized formula. The closeness of predicted and observed values for buoyancy time (Y1) and t50 (Y2) indicates validity of derived equations for the dependent variables. These studies indicated that the proper balance between HPMC K15M (X1), HPMC K100M (X2) and Guar gum (X3) can produce a desired buoyancy and predicted dissolution profile. The optimized formulations followed Korsemeyer peppas kinetics while the drug release mechanism was found to be anomalous type, controlled by diffusion through the swollen matrix.
Keywords:
Buoyancy time; Floating tablets; BBD; ANOVA; Numerical optimization
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