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Elastic recovery in roll compaction simulation
Hannah L Keizer1, Peter Kleinebudde1
1Heinrich Heine University Düsseldorf, Institute of Pharmaceutics and Biopharmaceutics Universitätsstraße 1, 40225 Düsseldorf, Germany.
International Journal of Pharmaceutics
|November 4, 2019
Summary
This study improves roll compaction simulation by accounting for elastic recovery, leading to more accurate predictions of ribbon solid fraction for pharmaceutical formulations. This enhances solid dosage form development.
Area of Science:
- Pharmaceutical Sciences
- Chemical Engineering
- Materials Science
Background:
- Roll compaction/dry granulation is crucial for pharmaceutical solid dosage form development.
- Accurate simulation of roll compaction is essential for predicting ribbon properties like solid fraction.
- Existing models often lack accuracy due to unaddressed elastic recovery phenomena.
Purpose of the Study:
- To investigate the in-die and out-of-die elastic recovery of various excipients during compaction.
- To develop and implement a method for compensating elastic recovery in roll compaction simulations.
- To enhance the prediction accuracy of ribbon solid fraction in pharmaceutical formulation development.
Main Methods:
- Investigated in-die and out-of-die elastic recovery of different excipients.
- Developed a compensation method for elastic recovery in roll compaction simulation.
- Implemented findings into a hybrid model through an additional learning step.
- Validated the improved model with an API-containing formulation.
Main Results:
- Elastic recovery was quantified for various excipients.
- A novel method significantly improved the prediction accuracy of ribbon solid fraction.
- The enhanced model accurately predicted process settings for desired solid fractions.
- Successful application to an API-containing formulation demonstrated practical utility.
Conclusions:
- Accounting for elastic recovery is critical for accurate roll compaction simulation.
- The developed method enhances the predictive power of hybrid models for solid dosage forms.
- This approach optimizes formulation development, reducing material usage and improving efficiency.
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