Utility of Multivariate Analysis in Modeling the Effects of Raw Material Properties and Operating Parameters on Granule and Ribbon Properties Prepared in Roller Compaction

Abstract

This article aimed to model the effects of raw material properties and roller compactor operating parameters (OPs) on the properties of roller compacted ribbons and granules with the aid of principal component analysis (PCA) and partial least squares (PLS) projection. A database of raw material properties was established through extensive physical and mechanical characterization of several microcrystalline cellulose (MCC) and lactose grades and their blends. A design of experiment (DoE) was used for ribbon production. PLS models constructed with only OP-modeled roller compaction (RC) responded poorly. Inclusion of raw material properties markedly improved the goodness of fit (R² = .897) and model predictability (Q² = 0.72).

Keywords:

• roller compaction
• near-infrared spectroscopy
• material characterization
• microcrystalline cellulose
• multivariate data analysis
• process analytical technology

ACKNOWLEDGMENTS

The authors thank the Consortium for the Advancement of Manufacturing of Pharmaceuticals (CAMP) for the funding of this work, especially Novartis Pharmaceuticals Corporation for providing the facilities where the RC work was performed. Students from the Massachusetts Institute of Technology (MIT) Practice School are acknowledged for their help in the RC. The assistance of Victor Hildebrand in the characterization work is also appreciated.