Abstract:

Early assessment of crystal polymorphism and thermodynamic solubility continues to be elusive for drug discovery and development despite its critical importance, especially for the ever-increasing fraction of poorly soluble drug candidates. We have developed a crystal structure prediction (CSP) method that combines a novel systematic crystal packing search algorithm and a hierarchical energy ranking protocol to predict crystal polymorphs. This is complemented by a free energy perturbation (FEP+) approach for computing thermodynamic aqueous solubility. The high accuracy, reliability, and efficiency of our CSP and FEP+ methods with large scale validations is designed to support polymorph screening and solubility prediction in drug substance and drug product development processes.

Webinar Highlights:

• Introduction to Schrödinger’s Crystal Structure Prediction platform and validation on a large and diverse dataset of 65 drug-like molecules with 135 experimentally found polymorphic forms
• Overview of physics-based free energy perturbation (FEP+) approach for computing thermodynamic aqueous solubility and assessment across a diverse chemical space spanning several pharmaceutically relevant compounds