Abstract：
UNASSIGNED: Sticking is one of the most common and damaging issues that occur during tablet manufacturing. Sticking is the adhesion of powder onto tooling surfaces during compression. Because of the numerous factors involved in its occurrence, understanding tablet sticking requires the simultaneous investigation of these factors to clarify their possible interactions. However, conducting such a study experimentally can present a significant financial and technical burden. In this study, we aimed to leverage the large amount of data that is usually generated during industrial manufacturing to gain insights into sticking.
UNASSIGNED: This was achieved by collecting and analyzing a total of 71 historical batches that used an ibuprofen-based formulation. We associate each batch with a hundred parameters, including a qualitative descriptor of sticking, and employ a predefined methodology based primarily on multivariate data analysis.
UNASSIGNED: Our results highlight the role of lubrication, water content, and the low melting point of ibuprofen in its sticking tendency. Based on these findings, we propose and discuss an industrial manufacturing data analysis approach to sticking and its associated systematic methodology, consisting of collection, exploration, and data modeling.
UNASSIGNED: This was achieved by collecting and analyzing a total of 71 historical batches that used an ibuprofen-based formulation. We associate each batch with a hundred parameters, including a qualitative descriptor of sticking, and employ a predefined methodology based primarily on multivariate data analysis.
UNASSIGNED: Our results highlight the role of lubrication, water content, and the low melting point of ibuprofen in its sticking tendency. Based on these findings, we propose and discuss an industrial manufacturing data analysis approach to sticking and its associated systematic methodology, consisting of collection, exploration, and data modeling.
摘要：
目标：粘贴是片剂制造过程中最常见和最具破坏性的问题之一。粘附是在压缩期间粉末粘附到工具表面上。由于它的发生涉及众多因素，了解片剂粘附需要同时研究这些因素，以阐明它们可能的相互作用。然而,通过实验进行这样的研究可能会带来巨大的财务和技术负担。在这项研究中,我们的目标是利用工业制造过程中通常产生的大量数据来获得对粘附的见解。方法:这是通过收集和分析总共71个使用基于布洛芬的制剂的历史批次来实现的。我们将每个批次与一百个参数相关联，包括一个定性的粘滞描述符，并采用主要基于多变量数据分析的预定义方法。结果和结论：我们的结果强调了润滑的作用，含水量,低熔点布洛芬的粘附倾向。基于这些发现,我们提出并讨论了一种工业制造数据分析方法及其相关的系统方法论，由收集组成，探索,和数据建模。
