APPLICATION OF RESPONSE SURFACE METHODOLOGY (RSM) IN STATISTICAL OPTIMIZATION AND PHARMACEUTICAL CHARACTERIZATION OF A MATRIX TABLET FORMULATION USING METFORMIN HCL AS A MODEL DRUG
Tapan Kumar Pal, Shubhasis Dan, Nirnoy Dan
Abstract
Tapan Kumar Pal, Shubhasis Dan, Nirnoy Dan
Abstract
The present study is about the application of a statistical optimization tool in the pharmaceutical tablet formulation. The toil of numerous scientists for years resulted in evolvement of the modified application based on the Response Surface Methodology (RSM). It has been found constructively eloquent in overcoming the problems of optimization regarding formulation of a sustained release tablet. In this study Metformin HCl is chosen as a model drug. In different time-points, experimental data are tabulated and graphically plotted. Depending upon the process variables, the predicted data obtained by RSM were compared with the experimental data. The result showed that the statistical optimization decreases the number of trial batches which is undoubtedly helpful in curtailing the resources i.e. principal, time and human effort.
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The present study is about the application of a statistical optimization tool in the pharmaceutical tablet formulation. The toil of numerous scientists for years resulted in evolvement of the modified application based on the Response Surface Methodology (RSM). It has been found constructively eloquent in overcoming the problems of optimization regarding formulation of a sustained release tablet. In this study Metformin HCl is chosen as a model drug. In different time-points, experimental data are tabulated and graphically plotted. Depending upon the process variables, the predicted data obtained by RSM were compared with the experimental data. The result showed that the statistical optimization decreases the number of trial batches which is undoubtedly helpful in curtailing the resources i.e. principal, time and human effort.
Key concepts: Response surface methodology, Statistical analysis, Matrix (chemical analysis), Experimental data, Process optimization, Computer science, Design of experiments, Mathematics