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Research Articles

A multivariate data analysis approach to tablet sticking on an industrial scale: a qualitative case study of an ibuprofen-based formulation

, , , &
Pages 1093-1109 | Received 05 Jun 2022, Accepted 27 Nov 2022, Published online: 20 Dec 2022
 

Abstract

Objectives

Sticking is one of the most common and damaging issues that occur during tablet manufacturing. Sticking is the adhesion of powder onto tooling surfaces during compression. Because of the numerous factors involved in its occurrence, understanding tablet sticking requires the simultaneous investigation of these factors to clarify their possible interactions. However, conducting such a study experimentally can present a significant financial and technical burden. In this study, we aimed to leverage the large amount of data that is usually generated during industrial manufacturing to gain insights into sticking.

Methods

This was achieved by collecting and analyzing a total of 71 historical batches that used an ibuprofen-based formulation. We associate each batch with a hundred parameters, including a qualitative descriptor of sticking, and employ a predefined methodology based primarily on multivariate data analysis.

Results and Conclusions

Our results highlight the role of lubrication, water content, and the low melting point of ibuprofen in its sticking tendency. Based on these findings, we propose and discuss an industrial manufacturing data analysis approach to sticking and its associated systematic methodology, consisting of collection, exploration, and data modeling.

Acknowledgments

The authors would like to thank the production and engineering teams from the plant in Saint-Laurent for their support in accessing the processes and data used in this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Natural Sciences and Engineering Research Council of Canada Grant number: RDCPJ 522450 - 17.

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