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Predicting Throughput and Melt Temperature in Pharmaceutical Hot Melt Extrusion
Tobias Gottschalk1,2, Cihangir Özbay1, Tim Feuerbach2
1Laboratory of Solids Process Engineering, Department of Biochemical and Chemical Engineering, TU Dortmund University, Emil-Figge-Str. 68, 44227 Dortmund, Germany.
Pharmaceutics
|September 23, 2022
Summary
Optimizing hot melt extrusion (HME) parameters is challenging. This study introduces SIOS 2.0, a new method using material data and experiments to predict optimal screw speed, melt temperature, and throughput for pharmaceutical polymers.
Area of Science:
- Pharmaceutical Technology
- Polymer Processing
- Chemical Engineering
Background:
- Hot melt extrusion (HME) is a widely used pharmaceutical manufacturing process.
- Determining optimal HME process parameters, such as material temperature and throughput, is complex and time-consuming.
Purpose of the Study:
- To develop a rational and predictable approach for optimizing HME process parameters.
- To establish a scale-independent optimization strategy (SIOS) for HME parameter determination.
Main Methods:
- Application and further development of the scale-independent optimization strategy (SIOS).
- Inclusion of an autogenic extrusion mode in the optimization process.
- Evaluation of three distinct polymers: Plasdone S-630, Soluplus, and Eudragit EPO.
Main Results:
- Maximum barrel load is influenced by polymer bulk density and extruder dimensions.
- Melt temperature is dependent on screw speed and polymer rheological properties.
- Melt viscosity is primarily governed by screw speed and self-adjusts in autogenic extrusion.
Conclusions:
- A novel approach, SIOS 2.0, is proposed for calculating HME process parameters.
- SIOS 2.0 utilizes material data and minimal experimental runs for parameter prediction.
- This strategy aims to streamline the optimization of pharmaceutical hot melt extrusion.
