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Discovery & Development Formulation, Small Molecules, Ingredients

Crystal Clear Predictions

Cocrystals – two or more molecular entities combined in a homogenous crystalline structure – have recently become attractive targets for the pharmaceutical industry, as cocrystallization can have a positive effect on the properties of solid dosage forms. However, predicting which potential coformers will successfully cocrystallize with a given active pharmaceutical ingredient (API) has proved difficult. Here, we describe a new computational method that does not require any knowledge or prediction of three-dimensional crystal structures, making it fast enough to virtually screen very large libraries of compounds to successfully identify new API cocrystals.

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About the Authors

Christopher A. Hunter

“I was born in Dunedin in New Zealand, but then lived in Nigeria before my parents settled in Ireland. Following an undergraduate degree in Natural Sciences, I stayed at the University of Cambridge for a PhD in the Chemistry Department,” says Chris Hunter. He then decided to revisit New Zealand and took a lectureship in bioorganic chemistry at the University of Otago. He later moved to the University of Sheffield before returning to the University of Cambridge in 2014 as the Herchel Smith Professor of Organic Chemistry.


Rafel Prohens

Born in Catalonia, Rafel Prohens grew up in Mallorca. “I received a PhD in Organic Chemistry from the University of the Balearic Islands and straightaway joined Chris Hunter's group at Sheffield University. In 2012, I founded CIRCE Crystal Engineering, a project to transfer Hunter’s approach on the study of intermolecular interactions into technological tools for the pharmaceutical industry.” Today, Rafel combines his roles as Scientific Director of CIRCE, Technical Manager at the University of Barcelona, and Research Visitor at the University of Cambridge.

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