This article reports the results of a meta-analysis based on dose–response studies conducted by a large pharmaceutical company between 1998–2009. Data collection targeted efficacy endpoints from all compounds with evidence of clinical efficacy during the time period. Safety data were not extracted. The goal of the meta-analysis was to identify consistent quantitative patterns in dose–response across different compounds and diseases. The article presents summaries of the study designs, including the number of studies conducted for each compound, dosing range, the number of doses evaluated, and the number of patients per dose. The  E_max model, ubiquitous in pharmacology research, was fit for each compound. It described the data well, except for a single compound, which had nonmonotone dose–response. Compound-specific estimates and Bayesian hierarchical modeling showed that dose–response curves for most compounds can be approximated by  E_max models with “Hill” parameters close to 1.0. Summaries of the potency estimates show pharmacometric predictions of potency made before the first dose ranging study within a (1/10, 10) multiple of the final estimates for 90% of compounds. The results of the meta-analysis, when combined with compound-specific information, provide an empirical basis for designing and analyzing new dose finding studies using parametric E_max models and Bayesian estimation with empirically derived prior distributions.