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Identifying overarching excipient properties towards an in-depth understanding of process and product performance for continuous twin-screw wet granulation

机译:识别朝向对过程和产品性能的深入理解,识别总体赋形性能,用于连续双螺杆湿造粒的过程和产品性能

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The overall objective of this work is to understand how excipient characteristics influence the process and product performance for a continuous twin-screw wet granulation process. The knowledge gained through this study is intended to be used for a Quality by Design (QbD)-based formulation design approach and formulation optimization. A total of 9 preferred fillers and 9 preferred binders were selected for this study. The selected fillers and binders were extensively characterized regarding their physico-chemical and solid state properties using 21 material characterization techniques. Subsequently, principal component analysis (PCA) was performed on the data sets of filler and binder characteristics in order to reduce the variety of single characteristics to a limited number of overarching properties. Four principal components (PC) explained 98.4% of the overall variability in the fillers data set, while three principal components explained 93.4% of the overall variability in the data set of binders. Both PCA models allowed in-depth evaluation of similarities and differences in the excipient properties. (c) 2017 Published by Elsevier B.V.
机译:这项工作的总体目标是了解辅料特征如何影响连续双螺杆湿造粒过程的过程和产品性能。通过本研究获得的知识旨在通过设计(QBD)的配方设计方法和配方优化来用于质量。为本研究选择总共9种优选的填料和9个优选的粘合剂。使用21材料表征技术,广泛地表征了所选填料和粘合剂关于它们的物理化学和固态性能。随后,对填料和粘合剂特性的数据组进行主成分分析(PCA),以将各种单一特征减少到有限数量的总体特性。四个主要成分(PC)在填充物数据集中解释了98.4%的整体变异性,而三个主要成分在粘合剂的数据集中解释了93.4%的整体变异性。两个PCA模型都允许深入评估赋形性质的相似性和差异。 (c)2017年由Elsevier B.V发布。

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