ABSTRACTUnmet medical need exists for serious bacterial diseases caused by multidrug-resistant infections, necessitating an urgent need for newer therapies with greater treatment benefits to patients. For meeting this need, the usual approach has been to conduct separate clinical trials, each trial targeting infection at a single body-site, e.g., for respiratory tract, intra-abdominal site, urinary tract, or blood. However, for the unmet medical need situations, this approach seems inefficient for developing antibacterial drugs with activity against single species or against multiple species of bacteria for a broader indication. Instead, a streamlined clinical development program for such situations can benefit by considering multiple body-site infection trials. Such trials would enroll patients with infections at different body-sites, but with similar severity and comorbidity for avoiding potential treatment effect heterogeneity. Such trials, when properly designed and conducted, can be informative and can save time and resources in drug development. Goals for such trials would be to first demonstrate that there is evidence of an overall treatment effect, and then to show that the treatment effects at individual body-sites reveal consistency in contributing to the overall treatment effect, or to identify a subset of body-sites for which greater treatment effect can be supported by a specified statistical decision criterion. For this, we propose here an information-based procedure for the demonstration of treatment effect overall across all body-sites, or for a subset of body-sites, on considering two types of error rates of falsely concluding treatment effect.