Engineering Downstream Processes to Enhance Processability of Crystallized Products

在活性药物成分（API）的生产链中，结晶步骤是分离和纯化的重要组成部分。典型的溶液结晶步骤之后是所谓的下游处理步骤。这些步骤对应于固液分离步骤，即过滤，从滤饼中除去母液的洗涤步骤，最后是蒸发洗涤溶剂的干燥步骤。干燥的粉末最终与辅料混合，在某些情况下配制成片剂或颗粒，以获得最终的固体产品。这些步骤的性能通常由结晶步骤决定，即通过结晶产物的粒度和形状分布（PSSD），水分含量，表面特性（例如内聚/粘合相互作用）等等。上述下游步骤已经在实验和计算上进行了详细的研究，用于许多不同的应用，例如制药，农用化学品，造纸和纸浆等。实验和模型研究旨在提供PS(S)D（主要在尺寸上，很少在形状上）和最终滤饼孔隙率之间的经验关系。尽管洗涤具有重要意义，但多年来几乎没有对其进行探索，重点放在开发经验法则和经验模型上，这些规则和模型在特定化合物的狭窄操作条件下工作。说到干燥，许多报道的工作都研究了溶剂/洗涤溶剂含量、滤饼搅拌、颗粒大小等因素对干燥过程在时间和破碎或结块程度上的有效性的影响。尽管这些下游步骤已经研究了很长时间，但它们还没有与上游结晶步骤在一个集成的框架中进行。较少研究的是结晶产品的PSSD对产品下游可加工性的影响。这主要是由于无法获得可靠和准确的尺寸和形状表征工具。最重要的是，即使这种联系是建立的，文献中也只有少数几种工艺能够调节晶体的大小和形状，以提高其下游加工能力。该项目旨在通过使用多尺度方法弥合上游结晶步骤和下游步骤之间的差距。我们将在实验数据的支持下，为上述三个下游步骤（过滤、洗涤和干燥）开发预测微观和宏观模型，以提高我们的理解，进而开发有效的工艺。这些模型将为整合整个工艺链铺平道路，在这个过程中，给定一个PSSD，人们可以从处理时间和能耗两方面定量地衡量结晶产品的可加工性。

In the production chain of active pharmaceutical ingredients (API), a crystallization step is an integral part for separation and purification purposes. A typical solution crystallization step is followed by the so-called downstream processing steps. These correspond to a solid-liquid separation step, i.e. filtration, a washing step to remove the mother liquor from the filter cake, and finally a drying step to evaporate the wash solvent. The dried powder is eventually blended with excipients and in some cases formulated as tablets or granules to obtain the final solid product. The performance of these steps is often dictated by the crystallization step, namely through the particle size and shape distribution (PSSD), the moisture content, the surface properties (e.g. cohesive/adhesive interactions), to name a few, of the crystallized product.The aforementioned downstream steps have been studied both experimentally and computationally in detail for many different applications, e.g. pharmaceuticals, agrochemicals, paper and pulp, etc. Experimental and modeling studies that aim to provide an empirical relationship between the PS(S)D (mostly on size and rarely on shape) and the final filter cake porosity have been reported. Despite its significance, washing has been scarcely explored over the years, with the focus being on developing rules of thumb and empirical models that work under a narrow range of operating conditions for specific compounds. When it comes to drying, many of the reported works have looked into understanding the impact of the solvent/wash solvent content, agitation of filter cakes, size of particles, to name a few, on the effectiveness of the drying process in terms of time and the extent of breakage or agglomeration. Even though these downstream steps have been studied for a long time, they have not been done in an integrated framework with the upstream crystallization step. Much less studied is the impact of the PSSD of the crystallized product on the downstream processability of the product. This can be mainly attributed to the unavailability of reliable and accurate size and shape characterization tools. Most importantly, even if this link is established there are only a handful of processes reported in the literature that have the ability to tune the size and shape of the crystals to enhance its downstream processability.This project is aimed at bridging the gap between the upstream crystallization step and the downstream steps by using a multiscale approach. We will develop predictive microscopic and macroscopic models backed by experimental data for all the three aforementioned downstream steps (filtration, washing and drying) to improve our understanding and in turn develop efficient processes. These models will pave way to integrate the entire process chain, where given a PSSD one could quantitatively gauge the processability of the crystallized product in terms of both processing time and energy consumption.