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Predicting Residence Time and Melt Temperature in Pharmaceutical Hot Melt Extrusion
Hot-melt extrusion is increasingly applied in the pharmaceutical area as a continuous processing technology, used to design custom products by co-processing drugs together with functional excipients. In this context, the residence time and processing temperature during extrusion are critical process...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10221575/ https://www.ncbi.nlm.nih.gov/pubmed/37242659 http://dx.doi.org/10.3390/pharmaceutics15051417 |
Sumario: | Hot-melt extrusion is increasingly applied in the pharmaceutical area as a continuous processing technology, used to design custom products by co-processing drugs together with functional excipients. In this context, the residence time and processing temperature during extrusion are critical process parameters for ensuring the highest product qualities, particularly of thermosensitive materials. Within this study, a novel strategy is proposed to predict the residence time distribution and melt temperature during pharmaceutical hot-melt extrusion processes based on experimental data. To do this, an autogenic extrusion mode without external heating and cooling was applied to process three polymers (Plasdone S-630, Soluplus and Eudragit EPO) at different specific feed loads, which were set by the screw speed and the throughput. The residence time distributions were modeled based on a two-compartment approach that couples the behavior of a pipe and a stirred tank. The throughput showed a substantial effect on the residence time, whereas the influence of the screw speed was minor. On the other hand, the melt temperatures during extrusion were mainly affected by the screw speed compared to the influence of the throughput. Finally, the compilation of model parameters for the residence time and the melt temperature within design spaces serve as the basis for an optimized prediction of pharmaceutical hot-melt extrusion processes. |
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