We specialize in knowledge-based drug discovery:  the application of all available information and data to the critical decisions in the drug discovery process.  We believe that combining the massive amounts of available data with the right scientists and methodology will lead to unexpected hypothesis to drive scientific discovery and ultimately to new opportunities to discover drugs.

 We have extensive experience in applying modeling and computation to drug discovery and a proven track record in applying diverse information to many drug discovery problems including structure- and ligand-based design, virtual screening, ADME/Tox modeling, HTS data analysis, target analyses, SAR analysis, library design and de novo design.  Further, we have built our computational tools on open source platforms to maintain cost effectiveness.

David Diller, PhD
Chief Science Officer
ddiller@data2discovery.com
"Think globally.  Act locally......Integrate parts."