(148c) Digital Design of Crystallization Process: Application of a Mechanistic Morphological Crystallizer Model to Improve Powder Flowability Via Aspect Ratio Reduction

Crystallization is the most widely used method for separating an active pharmaceutical ingredient (API) from a reaction product mixture. It functions to control purity, crystal form, particle morphology, and particle size distribution (PSD). The application of population balance modelling (PBM) to crystallization process development has been growing as a result of improvements in process analytical tools (PAT) and numerical software packages. One such improvement has been the ability to account for high aspect ratios particle morphologies, such as needles or plates, by tracking the major and minor particle axis using a 2-dimensional (2D) framework. This approach allows for each particle axis to have independent growth kinetics, so that crystal size and shape evolution can be described over the course of a crystallization process. Particles with needle-like morphology lead, in many cases, to poor manufacturability in downstream drug product unit operations due to poor powder flowability, driving formulation and sequence of unit operations to adjust the physical properties often creating the need for redundancy for improving control and robustness of the process. Hence, reducing particle aspect ratio (length/width) can be beneficial for enhancing manufacturability of an API.

In this work, process simulation and mechanistic modelling were applied to gain further process understanding and investigate how better control over particle size and shape could be achieved, with a view to improving flowability of the crystallized material. In order to probe the crystallization behaviour of the solution system, lab scale experiments were performed at a 300mL scale using an RC1 MT system. The crystallization process considered a sequence of heating and cooling cycles in order to investigate the effect on the shape of product crystals aswell as wet milling steps (see steps 2a-2b and 4a-4b in figure 1 below), in order to break the needle-like particles, hence reducing aspect ratio of the crystals and to facilitate the dissolution of fines. Seeding and cubic cooling profiles were used at lab scale to ensure the crystallization process studied was predominantly growth driven. Solute concentration over time was tracked via PAT and offline samples were taken for particle size and shape analysis using Malvern Morphologi G4, at stages 2a, 2b, 4a, 4b and of the final product in stage 6, as outlined in figure 1. These process measurements were used for model validation purposes.

Key results

The crystallization process was modelled using a mechanistic morphological crystallizer model, which utilises a 2D framework to describe the evolution of particle size and shape along two perpendicular axes (major & minor), from which shape descriptors, such as aspect ratio can be determined. Mechanisms and model discrimination was performed, yielding good predictions of the solute concentration over the cycles, as shown in figure 2. The model prediction of the evolution of particle size and shape during the process was coherent with what was qualitatively observed with the PVM images, in addition of providing a reasonable prediction of the quantitative values of volume-based PSD quantiles at the end of each pair of temperature cycles for the major and minor axes, as shown in figure 3(a) and 3(b), respectively.

The validated morphological crystallizer model of lab scale was subsequently utilised to investigate optimization strategies and potential process changes, such as heating & cooling rates and profiles, number of cycles and wet milling steps and wet milling duration, which could be utilised to reduce the aspect ratio (major axis length/minor axis length) of the crystallized material and hence improve the downstream flowability of the powder.