Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation
- Author
- Ana Alejandra Barrera Jiménez (UGent) , Kensaku Matsunami (UGent) , Daan Van Hauwermeiren (UGent) , Michiel Peeters (UGent) , Fanny Stauffer, Eduardo dos Santos Schultz, Ashish Kumar (UGent) , Thomas De Beer (UGent) and Ingmar Nopens (UGent)
- Organization
- 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.
- Keywords
- Pharmaceutical Science, Continuous manufacturing, Solid drug products, Granule size distribution, Hybrid model, Mechanistic model, Data-driven model, STOCHASTIC-MODEL, CONSOLIDATION, MULTISCALE, GROWTH
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01H0QKN4PAPPADJ5ZZ867GSSEM
- MLA
- Barrera Jiménez, Ana Alejandra, et al. “Partial Least Squares Regression to Calculate Population Balance Model Parameters from Material Properties in Continuous Twin-Screw Wet Granulation.” INTERNATIONAL JOURNAL OF PHARMACEUTICS, vol. 640, 2023, doi:10.1016/j.ijpharm.2023.123040.
- APA
- Barrera Jiménez, A. A., Matsunami, K., Van Hauwermeiren, D., Peeters, M., Stauffer, F., dos Santos Schultz, E., … Nopens, I. (2023). Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation. INTERNATIONAL JOURNAL OF PHARMACEUTICS, 640. https://doi.org/10.1016/j.ijpharm.2023.123040
- Chicago author-date
- Barrera Jiménez, Ana Alejandra, Kensaku Matsunami, Daan Van Hauwermeiren, Michiel Peeters, Fanny Stauffer, Eduardo dos Santos Schultz, Ashish Kumar, Thomas De Beer, and Ingmar Nopens. 2023. “Partial Least Squares Regression to Calculate Population Balance Model Parameters from Material Properties in Continuous Twin-Screw Wet Granulation.” INTERNATIONAL JOURNAL OF PHARMACEUTICS 640. https://doi.org/10.1016/j.ijpharm.2023.123040.
- Chicago author-date (all authors)
- Barrera Jiménez, Ana Alejandra, Kensaku Matsunami, Daan Van Hauwermeiren, Michiel Peeters, Fanny Stauffer, Eduardo dos Santos Schultz, Ashish Kumar, Thomas De Beer, and Ingmar Nopens. 2023. “Partial Least Squares Regression to Calculate Population Balance Model Parameters from Material Properties in Continuous Twin-Screw Wet Granulation.” INTERNATIONAL JOURNAL OF PHARMACEUTICS 640. doi:10.1016/j.ijpharm.2023.123040.
- Vancouver
- 1.Barrera Jiménez AA, Matsunami K, Van Hauwermeiren D, Peeters M, Stauffer F, dos Santos Schultz E, et al. Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation. INTERNATIONAL JOURNAL OF PHARMACEUTICS. 2023;640.
- IEEE
- [1]A. A. Barrera Jiménez et al., “Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation,” INTERNATIONAL JOURNAL OF PHARMACEUTICS, vol. 640, 2023.
@article{01H0QKN4PAPPADJ5ZZ867GSSEM,
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.}},
articleno = {{123040}},
author = {{Barrera Jiménez, Ana Alejandra and Matsunami, Kensaku and Van Hauwermeiren, Daan and Peeters, Michiel and Stauffer, Fanny and dos Santos Schultz, Eduardo and Kumar, Ashish and De Beer, Thomas and Nopens, Ingmar}},
issn = {{0378-5173}},
journal = {{INTERNATIONAL JOURNAL OF PHARMACEUTICS}},
keywords = {{Pharmaceutical Science,Continuous manufacturing,Solid drug products,Granule size distribution,Hybrid model,Mechanistic model,Data-driven model,STOCHASTIC-MODEL,CONSOLIDATION,MULTISCALE,GROWTH}},
language = {{eng}},
pages = {{14}},
title = {{Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation}},
url = {{http://doi.org/10.1016/j.ijpharm.2023.123040}},
volume = {{640}},
year = {{2023}},
}
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