Comparing Chemical Series with Probabilistic Scoring in StarDrop

Oct 16, 2013

This example is taken from a project in which screening of a diverse library resulted in hits from multiple chemistries. Without the resources to follow-up all of the hit chemistries, the project team wished to focus on a small number of series which were most likely to yield high quality leads with appropriate physicochemical and ADME properties.

If you can’t play the video above, please use this link.


With its comprehensive suite of integrated software, StarDrop™ delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop™ enables a seamless flow from the latest data through predictive modelling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the drug optimisation and discovery process.