SAR analysis is a cornerstone of the lead identification and optimization process in drug discovery.  With the advent of modern discovery informatics tools, project scientists now have more structure-activity data than ever readily at their fingertips.  The problem now becomes how to rationalize and make sense of this data.  What methods are available for effective structure-activity analyses that are not just limited to chemistry but also other entities?  In which ways can a scientist analyze a congeneric series to build a SAR model?  What effective visualization tools can be made available to scientists to find trends and patterns in a dataset?  We will present examples of how access to the right analysis and data visualization solutions can empower scientists to understand all the available project data.  Ultimately, these solutions not only make sense of the data deluge, but also facilitate collaboration between computational chemists, medicinal chemists and biologists for effective and faster decision making.

Utilizing modern tools for effective SAR analysis

248th National Meeting (2014)

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