The need to decrease the time scale for clinical compound discovery has led to innovations at several stages in the process, including genomics/proteomics for target identification, ultrahigh-throughput screening for lead identification, and structure-based drug design and combinatorial chemistry for lead optimization. A critical juncture in the process is the identification of a proper lead compound, because a poor choice may generate costly difficulties at later stages. Lead compounds are commonly identified from high-throughput screens of large compound libraries, derived from known substrates/inhibitors, or identified in computational prescreeusing X-ray crystal structures. Structural information is often consulted to efficiently optimize leads, but under the current paradigm, such data require preidentification and confirmation of compound binding. Here, we describe a new X-ray crystallography-driven screening technique that combines the steps of lead identification, structural assessment, and optimization. The method is rapid, efficient, and high-throughput, and it results in detailed crystallographic structure information. The utility of the method is demonstrated in the discovery and optimization of a new orally available class of urokinase inhibitors for the treatment of cancer.