结晶
湿磨
放大
工艺工程
磨坊
缩放比例
材料科学
比例(比率)
粒度分布
过程(计算)
人口
粒径
机械工程
计算机科学
工程类
数学
化学工程
冶金
物理
人口学
经典力学
量子力学
社会学
操作系统
几何学
作者
Tamar Rosenbaum,Andrew Werneth,Shasad Sharif,Torsten Wilkens,Benjamin Cohen,Joshua D. Engstrom,Antonio C. Ferretti,Yash Melkeri
标识
DOI:10.1021/acs.oprd.4c00390
摘要
Control over the particle size distribution (PSD) of the active pharmaceutical ingredient in the crystallization process is of key importance. Sometimes, it can be challenging to control the PSD to the target value via optimization of the crystallization process alone; in these scenarios, high shear wet milling is often utilized to reduce PSD. Much work has been done developing scaling parameters to be able to robustly scale-up wet milling processes and consistently achieve target PSD at the plant/commercial scale. While different scaling parameters have had good success with guiding scale-up of terminal wet milling processes, wet milling while crystallization is ongoing (i.e., integrated crystallization and wet milling; iCWM) introduces additional complexity to the system, as it couples scale-independent growth with scale-dependent milling and is therefore more difficult to scale-up in a reproducible manner. Herein, we present how population balance modeling of an iCWM process indicated that mill size and batch size, in addition to wet mill tip speed, had a large impact on final PSD. The model predictions can be used to guide selection of wet mill tip speed in order to maintain consistent PSD across different batch sizes and mill sizes.
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