Pharmaceutical Technology: Controlled Drug Release, Volume 2

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5 Analysis of different parameters of an optimized prolonged release formulation obtained by five processes A.Peña Romero and A.Vérain Université Scientifique et Médicale de Grenoble, UFR de Pharmacie-Pharmacie Galénique, Avenue de Verdun, 38243 Meylan, France J.B.Costa INRS, France D.Chulia Université de Limoges, UFR de Pharmacie-Pharmacie Galénique, 2 rue Docteur Marcland, 87025 Limoges, France A.T.Luong Searle de France, 52 rue Marcel Dasault, 92514 Boulogne Billancourt, France INTRODUCTION In previous work, a prolonged release formulation was obtained by five different processes, and it was optimized by applying a statistical strategy [1–5]: direct compression: factorial and centred composite designs double compression: Hadamard matrix and factorial design compaction of the mixture of five raw materials: fractional 2 3−1 factorialdesign separate compaction of the drug and PVC: fractional 2 5−2 factorialdesign wet granulation: 3 2 design and stepwise regression A mathematical model was found for each studied response. From the models, the contoured curves and the response surfaces were plotted, and the optimal points were sought and confirmed. The aim of this study is to analyse and choose the best process for a formula which contains an anti-inflammatory agent (diclofenac sodium), two inert polymer matrices (PVC, ethylcellulose) and two lubricants (magnesium stearate, talc). MATERIALS The formula contained the following raw materials: Diclofenac sodium (Secifarma) 25.0% Ethylcellulose N-7 (Hercules) 26.1%
58 MATRIX FORMULATIONS [CH. 5 Pevikon PE 737 P (PVC) (SEPPIC) 45.9% Magnesium stearate (Prophac) 1.0% Talc USP (Prophac) 2.0% For the wet granulation formulation, 2.12% Glucidex 2B (Roquette) was added as binder. METHODS AND TESTS PERFORMED The following responses (Yi) and properties were studied: (1) the powder flow rate (Y 1 ), the cohesion index PS/TS (Y 2 ), the tablet weight variation (Y3), the friability (Y 4 ), the amount of drug dissolved at 8 h (Y 5 ) and its coefficient of variation (Y 7 ), the area under the dissolution curve AUC (Y 6 ) and its coefficient of variation (Y 8 ); (2) the volume before and after tapping (V10−V500), the lubrication index (R), the ejection force (F e ), the residual force (F r ), the total energy (E t ) and the coefficient of variation of the applied upper punch force (CV UPF); (3) the compressibility factor (f), the plasticity index (PI) and the compressibility index (Comp); (4) the porosity factor (f por ) and the flowability index (ic). Optimization will concern the following aspects: (a) the parameters of the mathematical models, (b) the optimized responses and evaluated properties, (c) analysis of the data and the statistical strategies, (d) the dissolution profiles and the fitted physical models, (e) the processes. The parameters of the mathematical models The applied upper punch force (UPF) exhibited a poor influence on several optimized responses. Nevertheless, it is possible to observe that the increment of this parameter is related to adequate values of the responses. In fact, the increase of UPF value (Table 1) Table 1—Effect of the UPF increase on the optimized responses
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PHARMACEUTICAL TECHNOLOGY Controlle
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3 TABLET MACHINE INSTRUMENTATION IN
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162 CH. 15] A SUSTAINED RELEASE OPH
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184 CH. 17] SILICON MATRIX SYSTEMS
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194 INDEX dry granulation, 43 elect
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Pharmaceutical Technology: Controlled Drug Release, Volume 2

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