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Finite Element Modeling for the Simulation of the Quasi-Static Compression of Corrugated Tapered Tubes
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Predictive compaction modelling of ternary direct compression formulations
Theo Tait1, Mohammad Salehian1, Magdalini Aroniada2
1CMAC, University of Strathclyde, Glasgow, G1 1RD, UK; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK.
International Journal of Pharmaceutics
|August 3, 2026
Summary
This study optimized mixture rules for directly-compressed formulations, reducing experimental burden and API use. Global optimization improved predictive models for tablet properties, enhancing efficiency in pharmaceutical development.
Area of Science:
- Pharmaceutical Sciences
- Materials Science
- Chemical Engineering
Background:
- Directly-compressed formulation development is resource-intensive, requiring extensive characterization.
- Predicting compressibility and compactability across formulation spaces is challenging.
- Optimizing ternary mixtures (API, brittle filler, elastic filler) is complex.
Purpose of the Study:
- To extend global optimization of mixture rules to ternary systems.
- To reduce experimental burden in characterizing formulation spaces.
- To maintain predictive accuracy of empirical compression and compaction models.
Main Methods:
- Applied global optimization of mixture rules to a ternary formulation space.
- Evaluated three grades of paracetamol and ibuprofen with a placebo base.
- Benchmarked Model-Based Design of Experiments (MBDoE) against random experiment selection.
Main Results:
- Global optimization outperformed traditional methods, showing strong predictive performance for the Kawakita model (R²>0.94).
- MBDoE with optimized rules reduced API consumption by over 30%, with median savings of 75%-95%.
- Kawakita model supported reductions across all thresholds; Ryshkewitch-Duckworth model showed limited capacity.
Conclusions:
- The optimization framework offers a resource-efficient approach for predicting tablet properties.
- MBDoE integrated with optimized rules significantly reduces API consumption.
- This method enhances the prediction of tablet porosity and tensile strength in ternary API blends.
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