(42e) A Combined Theoretical and Experimental Investigation into the High Throughput Screening of Cocrystal Coformers

The CrystalPredictor^1,2 and CrystalOptimizer³ codes have been used to explore the space of crystal structures successfully in several crystal structure prediction (CSP) investigations in recent years, including in the series of blind tests organised by the Cambridge Crystallographic Data Centre⁴ and in the prediction of the crystal structures of pharmaceutically-relevant molecules^5-7. Recent advances in CrystalPredictor⁸, have allowed for orders of magnitude increases in the efficiency of the global search stage, whilst the capacity of CrystalOptimizer to reuse quantum mechanical calculations for the same molecule using LAM databases, allows for Quantum Mechanical (QM) accuracy in conformation, intramolecular energy and molecular electrostatics, at forcefield cost.

Exploiting these advances, we present a high throughput co-crystallisation study into 4 Active Pharmaceutical Ingredients (API’s), combined with 10 coformers, selected from the GRAS list. Having performed a standard, neat, CSP study on each of the molecules, assessing the energy of potential cocrystals of the API and any of the coformers becomes an almost trivial task, through the judicious use of LAM databases. Comparing the energies of the cocrystals, versus the combined single crystal energies, allows the user to make informed decisions on which coformer to crystallise the API with, in order to target specific physical properties.

Combined with the theoretical predictions, experimental co-crystallisation experiments were performed between the API’s and each of the coformers; comparisons will be made to assess the accuracy, as well as demonstrate the capacity for the technique to be taken up into standard pharmaceutical development workflows.

¹ M. Habgood, I. J. Sugden, A. V. Kazantsev, C. S. Adjiman, and C. C. Pantelides, J Chem Theory Comput 11, 1957 (2015).

² I. Sugden, C. S. Adjiman, and C. C. Pantelides, Acta Crystallogr B 72, 864 (2016).

³ A. V. Kazantsev, P. G. Karamertzanis, C. S. Adjiman, and C. C. Pantelides, J Chem Theory Comput 7, 1998 (2011).

⁴ A. M. Reilly, et al., Acta Crystallogr B 72, 439 (2016).

⁵ D. E. Braun, T. Gelbrich, K. Wurst, and U. J. Griesser, Cryst Growth Des 16, 3480 (2016).

⁶ D. E. Braun, V. Kahlenberg, and U. J. Griesser, Cryst Growth Des 17, 4347 (2017).

⁷ S. L. Price, D. E. Braun, and S. M. Reutzel-Edens, Chem Commun 52, 7065 (2016).

⁸ I. Sugden, C. S. Adjiman, and C. C. Pantelides, Acta Crystallogr B (Submitted).