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Drug Delivery Letters

Author(s): Hannlie Hamman*, Jan H. Steenekamp, Josias H. Hamman and Christi A. Wilkins

DOI: 10.2174/0122103031284291240306071000

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Applying the SeDeM Expert Diagram System for Characterization of Multiple Component Powder Mixtures for Fixed-dose Combination Matrix-type Tablet Formulations

Page: [244 - 258] Pages: 15

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Abstract

Background: The SeDeM Expert Diagram System (SeDeM EDS) is an innovative formulation tool that provides an index of compressibility, which can be used to predict a powder’s suitability for direct compression to produce acceptable tablets.

Objective: This study investigated the application of this tool to evaluate multiple component powder formulation mixtures for direct compression of tablets. The SeDeM EDS was specifically used to characterize powder mixtures for fixed-dose combination (FDC) matrix-type tablets that contained multiple active ingredients, which has not been done previously with SeDeM EDS.

Methods: The FDC matrix-type tablets contained diclofenac sodium and vitamins B1, B6 and B12 in fixed ratios, intended for the management of peripheral neuropathy. The parameters of the SeDeM EDS were determined for the multiple-component powder mixtures and the indices were calculated to predict direct compressibility. The FDC tablets were subsequently manufactured utilizing direct compression and subjected to pharmacotechnical test evaluations to measure the accuracy of the SeDeM EDS’s predictions.

Results: This study proved the versatility of the SeDeM EDS and its utility to adequately characterize FDC powder mixtures for matrix-type tablets manufactured by direct compression. Additionally, a new calculation was suggested to determine the percentage of corrective excipients re-quired in the case when multiple incidence factor values are below the value of 5. Prediction of the correct quantity of corrective excipient to be added is important to obtain an acceptable direct compressible formulation.

Conclusion: The results obtained confirmed that the SeDeM EDS correctly predicted the performance of all formulations.

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