SEURAT is a tool used by biologists, chemists and preclinical groups at Celera for exploring SAR. It provides an intuitive and flexible interface for data retrieval (including crystal structures), property calculation, and visual recognition of chemical trends. Viewing biological data and modeling predictions in the context of structure allows chemists and biologists to bring to bear their many years of experience when interpreting experiment results. SEURAT allows scientists to succinctly construct assay result retrieval templates from chemically aware databases, tune the results in “excel-like” ways and perform sub-structure searches on both global and local structure sets. The result is a tight integration between a traditional (table like) compound-based assay data view and novel aggregate visualizations (heat maps, scaffold matrices and the like) that provide scientific users efficient data mining capabilities in a familiar structural context. In this talk we will present some of the capabilities of SEURAT and share some of our insights on the requirements for easing acceptance of such tools in a drug design and development environment.