Analysis of the impact of material properties on tabletability by principal component analysis and partial least squares regression.

Autor: Mareczek L; Institute of Pharmaceutical Technology and Biopharmaceutics, Technische Universität Braunschweig, Braunschweig 38106, Germany; Department of Orals Development, Merck Healthcare KGaA, Darmstadt 64293, Germany., Riehl C; Department of Orals Development, Merck Healthcare KGaA, Darmstadt 64293, Germany. Electronic address: carolin.riehl@merckgroup.com., Harms M; Department of Orals Development, Merck Healthcare KGaA, Darmstadt 64293, Germany., Reichl S; Institute of Pharmaceutical Technology and Biopharmaceutics, Technische Universität Braunschweig, Braunschweig 38106, Germany. Electronic address: s.reichl@tu-braunschweig.de.
Jazyk: angličtina
Zdroj: European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences [Eur J Pharm Sci] 2024 Sep 01; Vol. 200, pp. 106836. Date of Electronic Publication: 2024 Jun 18.
DOI: 10.1016/j.ejps.2024.106836
Abstrakt: Principal component analysis (PCA) and partial least squares regression (PLS) were combined in this study to identify key material descriptors determining tabletability in direct compression and roller compaction. An extensive material library including 119 material descriptors and tablet tensile strengths of 44 powders and roller compacted materials with varying drug loads was generated to systematically elucidate the impact of different material descriptors, raw API and filler properties as well as process route on tabletability. A PCA model was created which highlighted correlations between different powder descriptors and respective characterization methods and, thus, can enable reduction of analyses to save resources to a certain extent. Subsequently, PLS models were established to identify key material attributes for tabletability such as density and particle size but also surface energy, work of cohesion and wall friction, which were for the first time demonstrated by PLS as highly relevant for tabletability in roller compaction and direct compression. Further, PLS based on extensive material characterization enabled the prediction of tabletability of materials unknown to the model. Thus, this study highlighted how PCA and PLS are useful tools to elucidate the correlations between powder and tabletability, which will enable more robust prediction of manufacturability in formulation development.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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