Use of Population Balance Modelling to Derisk Scale-Up of an Integrated Crystallization–Wet Milling Process

Abstract

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.