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A Digital Mechanistic Workflow for Predicting Solvent-Mediated Crystal Morphology

By Kevin Roberts, Leeds University The crystallization of organic materials provides a common, energy efficient methodology for the purification and isolation of high value compounds such as pharmaceuticals. The inherent anisotropic molecular and morphological properties of these materials can affect downstream ingredient processing such as powder flow, blending and compaction as well as impact upon product quality associated with stability and bioavailability. Hence, the ability to control the morphological characteristics of crystals through the rational design of the crystallization process can be important to reduce bottlenecks in both R&D and manufacturing associated with the production of new drug products. In this presentation a digital mechanistically-based workflow, encompassing a combination of attachment energy and grid-based systematic search methods, is applied to predict the solvent-dependent morphologies of the monotropically related α and β polymorphic forms of L-glutamic acid. This work encompasses calculation of the crystal lattice energy and its constituent intermolecular synthons, their interaction energies, and their key role in understanding and predicting crystal morphology. It also assesses the surface chemistry, topology, and solvent binding on crystal habit growth surfaces. Through a comparison between the contrasting morphologies of the conformational polymorphs of L-glutamic acid, the overall approach highlights how the interfacial chemistry of organic crystalline materials and their inherent anisotropic interactions with their solvation environments direct their crystal habit with potential impact on their further downstream processing behaviour. Session 2 Physical Property Based Crystallization Process Development

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