The pharmaceutical industry is increasingly exploring cocrystals as a solution to provide improved material properties for otherwise intractable active pharmaceutical ingredients (APIs). Researchers have attempted to streamline the experimental process of screening for cocrystals by developing in silico predictive tools. These tools use intermolecular interactions, primarily hydrogen bonding, as well as other molecular descriptors to quickly assess the likelihood of cocrystal formation between an API and a set of small-molecule coformers. We have developed a web-based application using three such predictive tools to help us prioritize experimental screening against a library of nearly 300 individual coformers. In order to validate our predictive algorithms, three API molecules from our compound library were screened, experimentally and with our application, against a subset of 40 coformers. Here, we present the design of the web-based app, the experimental work used to validate its predictions, and the relative success of our techniques.
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Sarjeant et al. (2024) studied this question.
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