4.7 Article

Didanosine extended-release matrix tablets:: optimization of formulation variables using statistical experimental design

期刊

INTERNATIONAL JOURNAL OF PHARMACEUTICS
卷 237, 期 1-2, 页码 107-118

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ELSEVIER SCIENCE BV
DOI: 10.1016/S0378-5173(02)00028-5

关键词

statistical experimental design; response surface methodology; multiple response optimization; didanosine; extended-release inert matrix tablets

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Statistical experimental design was applied to evaluate the influence of some process and formulation variables and possible interactions among such variables, on didanosine release from directly-compressed matrix tablets based on blends of two insoluble polymers. Eudragit RS-PM and Ethocel 100. with the final goal of drug release behavior optimization. The considered responses were the percent of drug released at three determined times, the dissolution efficiency at 6 h and the time to dissolve 10% of drug. Four independent variables were considered: tablet compression force. ratio between the polymers and their particle size. and drug content. The preliminary screening step. carried out by means of a 12-run asymmetric screening matrix according to a D-optimal design strategy. allowed evaluation of the effects of different levels of each variable. The drug content and the polymers ratio had the most important effect on drug release, which, moreover. was favored by greater polymers particle size: on the contrary the compression force did not have a significant effect. The Doehlert design was then applied for a response-surface study, in order to study in depth the effects of the most important variables. The desirability function was used to simultaneously optimize the five considered responses. each having a different target. This procedure allowed selection, in the studied experimental domain. of the best formulation conditions to optimize drug release rate. The experimental values obtained from the optimized formulation highly agreed with the predicted values. The results demonstrated the reliability of the model in the preparation of extended-release matrix tablets with predictable drug release profiles. (C) 2002 Elsevier Science B.V. All rights reserved.

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