(139a) Rapid Temperature Correction to Lattice Energy Landscape for Crystal Structure Prediction

The ability to solve solid-state structures through organic crystal structure prediction (CSP) would reduce risk and improve efficiency during drug development by guiding and complementing experimental screens for low free energy crystal forms. Recent advances in computational hardware and algorithms have enabled high accuracy crystal structure predictions to assist in pharmaceutical decision making for molecules with few low energy polymorphs or large energy gaps between polymorphs. These methods generally focus on crystal lattice energies computed through various quantum mechanics calculations, e.g. the widely used density functional theory, at 0 Kelvin, and thus the predicted stability ranking of polymorphs does not necessarily correspond to their ranking at physically relevant temperatures. This poses a challenge for compounds with many low energy polymorphs, as, for a given compound, tens to hundreds of polymorphs may be predicted by CSP, many of which cannot be crystallized experimentally, e.g. due to kinetic traps or low thermodynamic populations. The ability to determine the thermodynamic stability ranking of predicted polymorphs at physically relevant temperatures, as well as their kinetic accessibility, is required for CSP to have wide-spread applicability in drug development. We demonstrate the strength of our CSP method coupled with finite temperature analysis on compounds with multiple metastable polymorphs. Such predictions can guide and accelerate experimental polymorph screening for drug development and manufacture.

Corresponding authors' emails: shuhao@xtalpi.com, bruno.c.hancock@pfizer.com

* These authors contributed equally to this work.