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使用离散元法(DEM)在两种混合机之间展示可扩展性。

Demonstrating scalability between two blender types using DEM.

机构信息

Research Center Pharmaceutical Engineering GmbH, Graz, Austria.

Pharmaceutical Technical Development Synthetic Molecules, F. Hoffmann-La Roche, Basel, Switzerland.

出版信息

Int J Pharm. 2024 Dec 5;666:124773. doi: 10.1016/j.ijpharm.2024.124773. Epub 2024 Sep 27.

Abstract

Powder blending is a critical step in pharmaceutical manufacturing that can impact product quality such as tablet tensile strength. This study utilized the Discrete Element Method (DEM) to investigate blending in a 5-liter mini-batch and a 2-liter Turbula blender. DEM parameters were calibrated using small-scale powder characterization tests, so that the particle behavior in the DEM simulations matches the measured behavior. The research explored the effects of blender designs and process conditions on blending and lubricant dispersion. A predictive model for tablet tensile strength was developed. The model takes the lubricant's dispersion via the lubrication energy into account. The model is then used to predict the tablet tensile strength depending on the chosen process parameters, blending speed, duration, and fill level. DEM simulations enabled scaling between the two blenders, providing valuable insights for a semi-continuous manufacturing process based on mini-batch blending. The findings contribute to a deeper understanding of blending mechanics, offering potential enhancements in pharmaceutical manufacturing efficiency and product consistency.

摘要

粉末混合是制药生产中的关键步骤,会影响片剂拉伸强度等产品质量。本研究利用离散元法(DEM),在 5 升迷你批次和 2 升 Turbula 混合机中研究混合过程。通过小尺度粉末特性测试对 DEM 参数进行校准,以使 DEM 模拟中的颗粒行为与测量行为相匹配。研究探讨了混合机设计和工艺条件对混合和润滑剂分散的影响。开发了片剂拉伸强度的预测模型。该模型考虑了润滑剂的润滑能分散情况。然后,该模型根据所选工艺参数、混合速度、持续时间和填充水平来预测片剂拉伸强度。DEM 模拟实现了两种混合机之间的缩放,为基于迷你批次混合的半连续制造工艺提供了有价值的见解。研究结果有助于深入了解混合力学,为提高制药生产效率和产品一致性提供了潜在的改进方法。

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