Using Computational Crystal Structure Prediction (CSP) to Optimize Small Molecule Drug Formulation

Key Points:

• Computational CSP is a valuable tool to identify small molecule drug candidates with desirable solid properties
• OpenEye’s proprietary method and highly parallelizable approach makes this an accurate and practical tool for screening a large number of molecules
• Blind and semi-blind challenges of the method were validated with drug-like molecules from GlaxoSmithKline

Benefits to using CSP:

• Smart candidate selection – Identify and rank crystal candidates most suitable for web-lab formulation testing by computationally predicting polymorph landscape.
• Reduced costs and risks – Avoid costly experimental testing on candidates whose polymorph profiles will likely lead to safety or efficacy concerns down the line.
• Better business insights – Use knowledge gleaned from crystal structure prediction to consider a candidate’s impact on the IP landscape.

Estimated Reading Time: 15 minutes

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