SEAing change in R&D

Researchers at the University of California, San Francisco, SeaChange Pharmaceuticals Inc. and the Novartis Institutes for BioMedical Research have developed a computational approach for large-scale, automated prediction of binding interactions between molecules and targets that have been associated with adverse drug reactions.¹ The method could help companies improve R&D productivity by pointing to safety signals and helping prioritize candidates in silico.

The computational approach uses a statistics-based chemoinformatics technique called the similarity ensemble approach (SEA), which the UCSF group first described in 2007.² SEA predicts whether a molecule will bind a target based on the similarity of the compound's chemical groups to known ligands of the target...