Attrition is a major challenge in drug discovery and development with >50% of studies failing in clinical development due to lack of efficacy.Rapid progress in revealing the influence of genes on human disease can potentially transform the process of selecting the best targets and indications and leads us to ask what weight should be given to genetic associations in making drug discovery decisions.We address this by investigating how well clinically successful drug mechanisms are predicted by the current archive of genetic associations.We merged genetic data from GWASdb and OMIM, with up to 9,700 genes annotated to affect 2,600 traits, with Informa Pipeline(@), a commercial database of 23000 drugs with known human targets with 700 indications.We drew on linkage disequilibrium, eQTL data, epigenetic data, and location to map 19,400 genome-wide significant variants (p < 1e-8) to 8000 protein-coding genes.We found that among 1855 unique drug targets in Pipeline, 522 (28%) had one or more genome-wide significant associations.