Artificial Intelligence Based Screening And Selection Of Co-Formers For Co-Crystallization

With nearly 70% of APIs in development facing poor water solubility, co-crystallization has emerged as a promising strategy to improve formulation success. This webinar explores the growing role of co-crystallization in drug development, highlighting both its potential and the experimental challenges it presents. Gain insight into how computational tools are transforming co-former screening, with a focus on the technical foundations required to build AI-driven prediction models. Learn more about mPredict™, a co-crystal prediction service that integrates quantum chemistry, statistical thermodynamics, and AI to identify optimal co-formers that deliver results three times faster than random digital screening.

Whether you're navigating solubility hurdles or exploring predictive modeling, uncover practical guidance and innovative solutions.