As the time to develop increasingly efficacious therapeutic agents has lengthened, there is a need from patients, caregivers and industry alike to modernize the drug development process.  An important part of this process is quantifying the efficacy of a drug across the range of tolerable doses in order to assess the risk-benefit of the recommended drug regimen, but this can be a time consuming exercise due to many factors.  This often leads dose-finding to be inadequate or overlooked.  When standard approaches to dose-finding are infeasible, statisticians should seek innovation through thoughtful inclusion of robust data in statistical models, novel trial designs to accelerate and improve learning or through other analytics driven means.  This presentation will describe these issues by outlining the clinical drug development process with a focus on dose-finding and Bayesian dose-response modeling.  An application of an adaptive dose-finding trial will be described and the results of a simulation study will be presented.