There is no one-tool-fits-all solution for all the steps or issues in drug discovery.

A successful lead passes through several tests and we have predictive models developed for everyone of those using structure based, ligand based, field based, empirical and machine learning models in a fit-for-purpose manner.

Our machine learning models inform and augment the traditional modeling techniques. Together they drive the structure-activity relationships and enable prospective and synthetically accessible designs.

Using our molecular similarity engine we can identify potential off targets of the lead compounds and help build selectivity.

In short, we have the entire range of the technologies that can be leveraged across the entire drug discovery chain. Get in touch with us to know more.