AI drug discovery
Big Data

Thousands of global models are routinely built at Exscientia from literature, patent and internal data for the widest range of targets as well as other DMPK characteristics. Application of these broad models to a specific project ensures that any compounds proposed will have had selection pressure applied to ensure they are unlikely to hit a broad set of selectivity targets.  

As a project progresses the criteria placed on evolved compounds will become stricter. Where compounds are actively tested in multiple assays, these data are used to update the models so that they become project specific. When coupled with Exscientia’s range of discovery algorithms, the result is sector leading progression from hits and leads to candidates for entry to preclinical pipelines.