Expression data are an important element of target identification and validation. The authors have established an automated high-throughput method based on real time quantitative polymerase chain reaction, called the GeneTrawler, for the characterization of pharmaceutical targets on an annotated collection of human tissues. The authors have conducted a variability analysis of the system, which demonstrates that the majority of the variability between expression levels determined is due to biologic variation between samples, rather than technical variation due to imprecision of the method. Gene expression maps, generated with this carefully controlled system provide a large, reliable, consistent data set. The authors have used this system to characterize the expression of > 100 genes, and here they show the expression profile of SUR1 in order to illustrate its use. The authors were able to confirm SUR1 expression in the lung, which was suggested on the basis of pharmacologic experiments but has not previously been confirmed by mRNA detection. The data also show SUR1 expression in tissues that have been associated with some of the side effects seen with SUR1 modulators. This and other examples demonstrate that the GeneTrawler is useful to gauge the suitability of a prospective therapeutic target, to fully exploit a known drug target, or to identify and help validate new hypothetical druggable targets to fuel drug discovery pipelines.