• N Willecke, A Szepes, M Wunderlich, J P Remon, C Vervaet, and T De Beer.
• Small Molecules Technical Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland; Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Ghent University, Belgium.
• Int J Pharm. 2018 Jul 10; 545 (1-2): 128-143.

AbstractThe overall objective of this work is to understand how excipient characteristics influence the drug product quality attributes and process performance of a continuous twin screw wet granulation process. The knowledge gained in this study is intended to be used for Quality by Design (QbD)-based formulation design and formulation optimization. Three principal components which represent the overarching properties of 8 selected pharmaceutical fillers were used as factors, whereas factors 4 and 5 represented binder type and binder concentration in a design of experiments (DoE). The majority of process parameters were kept constant to minimize their influence on the granule and drug product quality. 27 DoE batches consisting of binary filler/binder mixtures were processed via continuous twin screw wet granulation followed by tablet compression. Multiple linear regression models were built providing understanding of the impact of filler and binder properties on granule and tablet quality attributes (i.e. 16 DoE responses). The impact of fillers on the granule and tablet responses was more dominant compared to the impact of binder type and concentration. The filler properties had a relevant effect on granule characteristics, such as particle size, friability and specific surface area. Binder type and concentration revealed a relevant influence on granule flowability and friability as well as on the compactability (required compression force during tableting to obtain target hardness). In order to evaluate the DoE models' validity, a verification of the DoE models was performed with new formulations (i.e. a new combination of filler, binder type and binder concentration) which were initially not included in the dataset used to build the DoE models. The combined PCA (principle component analysis)/DoE approach allowed to link the excipient properties with the drug product quality attributes.Copyright © 2018 Elsevier B.V. All rights reserved.

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