(654b) Predicting the Neat Polymorphs of Axitinib

In recent years, there has been significant progress in crystal structure prediction methodologies, as demonstrated by recent blind tests and other work on the prediction of the crystal structure of small pharmaceutical molecules¹. In this paper, we discuss the application of one particular approach that has proved successful to the challenging case of axitinib. Axitinib is well-studied molecule developed by Pfizer, which has been shown to have 71 polymorphs² of which 5 are neat (i.e., they contain only the axitinib molecule). The focus of the present study on neat polymorphs with one molecule in the asymmetric unit, of which 4 are known experimentally (Forms I, VI, XXV and XLI).

The approach to crystal structure prediction adopted here is based on the lattice energy minimization of a large number of trial structures at 0 K in order to generate an energy landscape, in which low-energy minima are identified based on the computational model of choice. Success is dependent upon the accuracy of the lattice energy calculations, especially in terms of electrostatics and the impact of molecular flexibility, and the ability to optimise a hundreds of thousands to millions of putative structures. Such approaches have been proven to be successful in predicting the polymorphs of compounds with one or two polymorphs in many cases3.

We use a multi-stage methodology. A model is first chosen based on analysis of the conformational flexibility of the molecule. Then 4,800,000 structures are generated and locally minimised with a computationally inexpensive model, using the CrystalPredictor4,5 algorithm. Then the most promising structures (lowest in energy) are further minimised in a two-step approach with CrystalOptimizer6,7, a program performing local minimisation, adopting a highly accurate though computationally expensive model. The axitinib molecule is found to have a richly populated energy landscape. The four known structures are predicted as lattice energy minima with the chosen model. Although Form XLI is not found to be the most stable at 0 K, contrary to expectations based on data at higher temperatures, the relative stability of other forms is predicted correctly. The relative importance of the different contributions to the energy model (intramolecular energy, electrostatics, repulsion/dispersion) is analysed and provides insights into the need for future development of predictive methodologies.  

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