Mechanistic modeling of twin screw wet granulation for pharmaceutical formulations : calibration, sensitivity analysis, and model-driven workflow

Bala, Neeru and Corrigan, Jeremiah and Ahmed, Bilal and Meyer, Jonathan and Schongut, Marek and Doshi, Pankaj and Iyer, Kiran and Lee, Kai and Rowland, Martin and Litster, James D. and Dawson, Neil and Smith, Rachel M. (2024) Mechanistic modeling of twin screw wet granulation for pharmaceutical formulations : calibration, sensitivity analysis, and model-driven workflow. International Journal of Pharmaceutics, 659. 124246. ISSN 1873-3476 (https://doi.org/10.1016/j.ijpharm.2024.124246)

[thumbnail of Bala-etal-2024-IJP-Mechanistic-modeling-of-twin-screw-wet-granulation-for-pharmaceutical-formulations]
Preview
 Text. Filename: Bala-etal-2024-IJP-Mechanistic-modeling-of-twin-screw-wet-granulation-for-pharmaceutical-formulations.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (4MB)| Preview

Abstract

Wet granulation, a particle size enlargement process, can significantly enhance the critical quality attributes of powders and improve the ability to form tablets in pharmaceutical manufacturing. In this study, a mechanistic-based population balance model is applied to twin screw wet granulation. This model incorporated a recently developed breakage kernel specifically designed for twin screw granulation, along with nucleation, layering, and consolidation. Calibration and validation were performed on Hydrochlorothiazide and Acetaminophen formulations, which exhibit different particle size and wettability characteristics. Utilizing a compartmental experimental dataset, a comprehensive global sensitivity analysis identified critical inputs impacting quality attributes. The study revealed that the nucleation rate process model, effectively represented particle size distributions for both formulations. Adjustments to nucleation and breakage rate parameters, influenced by material properties and screw configuration, improved the model's accuracy. A model-driven workflow was proposed, offering step-by-step guidelines and facilitating PBM model usage, providing essential details for future active pharmaceutical ingredient (API) formulations.

ORCID iDs

Bala, Neeru, Corrigan, Jeremiah, Ahmed, Bilal ORCID logoORCID: https://orcid.org/0000-0002-4419-8392, Meyer, Jonathan, Schongut, Marek, Doshi, Pankaj, Iyer, Kiran, Lee, Kai, Rowland, Martin, Litster, James D., Dawson, Neil and Smith, Rachel M.;
CORE (COnnecting REpositories)