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Model-based approach to the design of pharmaceutical roller-compaction processes

This work presents a new model based approach to process design and scale-up within the same equipment of a roller compaction process. The prediction of the operating space is not performed fully in-silico, but uses low-throughput experiments as input. This low-throughput data is utilized in an iter...

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Autores principales: Toson, Peter, Lopes, Diogo G., Paus, Raphael, Kumar, Ashish, Geens, Jeroen, Stibale, Sandy, Quodbach, Julian, Kleinebudde, Peter, Hsiao, Wen-Kai, Khinast, Johannes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733294/
https://www.ncbi.nlm.nih.gov/pubmed/31517270
http://dx.doi.org/10.1016/j.ijpx.2019.100005
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author Toson, Peter
Lopes, Diogo G.
Paus, Raphael
Kumar, Ashish
Geens, Jeroen
Stibale, Sandy
Quodbach, Julian
Kleinebudde, Peter
Hsiao, Wen-Kai
Khinast, Johannes
author_facet Toson, Peter
Lopes, Diogo G.
Paus, Raphael
Kumar, Ashish
Geens, Jeroen
Stibale, Sandy
Quodbach, Julian
Kleinebudde, Peter
Hsiao, Wen-Kai
Khinast, Johannes
author_sort Toson, Peter
collection PubMed
description This work presents a new model based approach to process design and scale-up within the same equipment of a roller compaction process. The prediction of the operating space is not performed fully in-silico, but uses low-throughput experiments as input. This low-throughput data is utilized in an iterative calibration routine to describe the behavior of the powder in the roller compactor and improves the predictive quality of the mechanistic models at low and high-throughput. The model has been validated with an experimental design of experiments of two ibuprofen formulations. The predicted sweet spots in the operating space are in good agreement with the experimental results.
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spelling pubmed-67332942019-09-12 Model-based approach to the design of pharmaceutical roller-compaction processes Toson, Peter Lopes, Diogo G. Paus, Raphael Kumar, Ashish Geens, Jeroen Stibale, Sandy Quodbach, Julian Kleinebudde, Peter Hsiao, Wen-Kai Khinast, Johannes Int J Pharm X Article This work presents a new model based approach to process design and scale-up within the same equipment of a roller compaction process. The prediction of the operating space is not performed fully in-silico, but uses low-throughput experiments as input. This low-throughput data is utilized in an iterative calibration routine to describe the behavior of the powder in the roller compactor and improves the predictive quality of the mechanistic models at low and high-throughput. The model has been validated with an experimental design of experiments of two ibuprofen formulations. The predicted sweet spots in the operating space are in good agreement with the experimental results. Elsevier 2019-01-26 /pmc/articles/PMC6733294/ /pubmed/31517270 http://dx.doi.org/10.1016/j.ijpx.2019.100005 Text en © 2019 Published by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Toson, Peter
Lopes, Diogo G.
Paus, Raphael
Kumar, Ashish
Geens, Jeroen
Stibale, Sandy
Quodbach, Julian
Kleinebudde, Peter
Hsiao, Wen-Kai
Khinast, Johannes
Model-based approach to the design of pharmaceutical roller-compaction processes
title Model-based approach to the design of pharmaceutical roller-compaction processes
title_full Model-based approach to the design of pharmaceutical roller-compaction processes
title_fullStr Model-based approach to the design of pharmaceutical roller-compaction processes
title_full_unstemmed Model-based approach to the design of pharmaceutical roller-compaction processes
title_short Model-based approach to the design of pharmaceutical roller-compaction processes
title_sort model-based approach to the design of pharmaceutical roller-compaction processes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733294/
https://www.ncbi.nlm.nih.gov/pubmed/31517270
http://dx.doi.org/10.1016/j.ijpx.2019.100005
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