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Updated: Jul 30, 2025

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Published on: January 27, 2021
Partial least squares regression to calculate population balance model parameters from material properties in
Ana Alejandra Barrera Jiménez1, Kensaku Matsunami1, Daan Van Hauwermeiren1
1BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium.
Abstract:
In the pharmaceutical industry, twin-screw wet granulation has become a realistic option for the continuous manufacturing of solid drug products. Towards the efficient design, population balance models (PBMs) have been recognized as a tool to compute granule size distribution and understand physical phenomena. However, the missing link between material properties and the model parameters limits the swift applicability and generalization of new active pharmaceutical ingredients (APIs). This paper proposes partial least squares (PLS) regression models to assess the impact of material properties on PBM parameters. The parameters of the compartmental one-dimensional PBMs were derived for ten formulations with varying liquid-to-solid ratios and connected with material properties and liquid-to-solid ratios by PLS models. As a result, key material properties were identified in order to calculate it with the necessary accuracy. Size- and moisture-related properties were influential in the wetting zone whereas density-related properties were more dominant in the kneading zones.
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