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.

中文翻译：

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使用群体平衡模型降低集成结晶-湿法研磨工艺的放大风险


在结晶过程中控制活性药物成分的粒度分布 （PSD） 至关重要。有时，仅通过优化结晶过程将 PSD 控制到目标值可能具有挑战性;在这些情况下，通常使用高剪切湿法研磨来降低 PSD。已经做了大量工作来开发缩放参数，以便能够稳健地扩大湿磨工艺，并在工厂/商业规模上始终如一地实现目标 PSD。虽然不同的结垢参数在指导终端湿法研磨工艺的放大方面取得了很好的成功，但在结晶过程中进行湿法研磨（即集成结晶和湿法研磨;iCWM）给系统带来了额外的复杂性，因为它将不依赖结垢的生长与不依赖结垢的研磨相结合，因此更难以可重复的方式进行放大。在本文中，我们介绍了 iCWM 工艺的群体平衡模型如何表明，除了湿磨机尖端速度外，磨机规模和批量大小对最终 PSD 有很大影响。模型预测可用于指导湿磨机齿尖速度的选择，以便在不同的批量大小和研磨机尺寸上保持一致的 PSD。