In the pharmaceutical industry, the vast majority of drugs are delivered in a crystalline form. The performance of any solid form of an active pharmaceutical ingredient (API) depends on a range of factors such as aqueous solubility, chemical and physical stability, hygroscopicity, particle control, mechanical properties etc. Despite an extensive amount of research in this field, it is still difficult to predict, simply from the chemical structure, the number of crystal forms of a compound and how to control and prepare unknown crystal forms. The Cambridge Structural Database (CSD) has developed a knowledge-based model within the Mercury software which utilizes hydrogen-bond propensity, hydrogen-bond coordination and full interaction maps of a molecule. In this study, three case studies will be presented to determine whether these knowledge-based tools can guide us towards predicting the right intermolecular interactions in individual molecules as well as in multicomponent systems such co-crystals. The knowledge gained from this study can be applied to more flexible, larger drug-like molecules with higher complexity.<br/> <br/>

Using knowledge-based tools to evaluate solid-form design and risk assessment

2019 Fall National Meeting

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