Optimization of Sustained-Release Tablet Formulations: a Four-Component Mixture Experiment

ABSTRACT Sustained-release tablet formulations containing chlorpheniramine maleate were prepared using a mixture of two hydrophilic gums, γ-carrageenan and cross-linked carboxymethylcellulose sodium, and two filler materials, a-lactose monohydrate and dibasic calcium phosphate in different ratios. T...

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Bibliographic Details
Published in:Pharmaceutical development and technology 1997, Vol.2 (4), p.365-371
Main Authors: Hariharan, Madhusudan, Gupta, Vishal, Price, James C.
Format: Article
Language:English
Subjects:
Carrageenan
Chemistry, Pharmaceutical
Chlorpheniramine - therapeutic use
Cross-linked carboxymethylcellulose sodium
Delayed-Action Preparations
Histamine H1 Antagonists - therapeutic use
Regression Analysis
Response surface methodology
Simultaneous optimization
Surface Properties
Sustained release
Tablets
Zero-order release
γ-Carrageenan
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Summary:ABSTRACT Sustained-release tablet formulations containing chlorpheniramine maleate were prepared using a mixture of two hydrophilic gums, γ-carrageenan and cross-linked carboxymethylcellulose sodium, and two filler materials, a-lactose monohydrate and dibasic calcium phosphate in different ratios. The objective of the experiment was to find an optimum formulation with the most desirable properties. In order to achieve this, the matrices were evaluated for the time taken to release 80% drug (t80), the release exponent (n), and the crushing strength (h). Several formulations produced near zero-order release of the model drug over a time period of up to 10 hr. Response surface plots for the three dependent variables were generated over the experimental region. The effect of different levels of the components on the response variables was thus visualized. Upon superimposition of the plots it was possible to graphically find a region where the responses were in an optimum range of values. To pinpoint the best formulation, a simultaneous optimum point within this region was located by arbitrarily defining optimum values for each of the responses and using a multi-objective function that combined the three response variables. The observed response variables of the optimum formulation were in good agreement with the predicted values.
ISSN:1083-7450
1097-9867
DOI:10.3109/10837459709022635