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Published on: April 10, 2017
Using in-line measurement and statistical analyses to predict tablet properties compressed using a Styl'One
Issa Munu1, Andrei L Nicusan2, Jason Crooks3
1School of Chemical Engineering, The University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; GSK Global Supply Chain, Priory St, Ware SG12 0DJ, UK.
This study links in-line measurements during high shear wet granulation (HSWG) to granule and tablet properties. A predictive model for tablet tensile strength proved effective across different compaction simulators, indicating scalability for industrial tablet manufacturing.
Area of Science:
- Pharmaceutical Manufacturing
- Process Analytical Technology (PAT)
- Granulation Science
Background:
- High shear wet granulation (HSWG) is crucial for tablet manufacturing, enhancing powder properties and preventing segregation.
- In-line process analytical technology (PAT) is vital for real-time monitoring and control of complex granulation processes.
Purpose of the Study:
- To establish relationships between Lenterra in-line measurements and resultant granule and tablet properties.
- To investigate granule growth mechanisms during HSWG.
- To develop a predictive model for tablet tensile strength using PAT data.
Main Methods:
- Utilized the Styl'One Evolution compaction simulator to produce tablets, mimicking industrial rotary tablet presses.
- Employed Lenterra in-line measurements to capture particle dynamics.
- Developed a predictive model based on data from a Gamlen tabletting press.
Main Results:
- Identified an induction granule growth mechanism specific to the studied conditions.
- The predictive model achieved high accuracy (R²=0.9535, RMSE=0.4040 MPa) when applied to data from a different compaction simulator (Styl'One Evolution).
- Demonstrated the model's ability to predict tablet tensile strength irrespective of the compaction machine used.
Conclusions:
- The developed model shows high predictability for tablet tensile strength across different compaction equipment.
- Findings suggest significant potential for the model's application in industrial-scale tablet manufacturing.
- This research advances the understanding and monitoring of granulation processes for scalable pharmaceutical production.
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