The importance of adequately understanding the dose-response relationship is well recognized in drug development. Dose-finding studies, however, are often designed with a small number of doses and a narrow dose range using suboptimal analysis techniques. Inadequate dose exploration due to limited understanding of the dose-response relationship can lead to failed late-stage trials. To address this issue, the use of empirically based Bayesian Emax models with supporting software has been proposed to improve the design and analysis of clinical trials whose primary purpose is to characterize the relationship between efficacy and dose to guide dose selection for further development.
A multidisciplinary team, with representation from both the Office of Biostatistics and the Office of Clinical Pharmacology in the Office of Translational Sciences within the Center for Drug Evaluation and Research, has determined that an empirically based Bayesian Emax model, including the goodness-of-fit (GOF) statistic, can be designated as FFP under the following conditions:
component studies for a new compound are homogeneous,
he proposed GOF statistic is applicable,
the model is identifiable, and
study-specific information is considered for dose selection.
EMA adopts first list of critical medicines for COVID-19
News On 7 June 2022, EMA’s Medicines Shortages Steering Group (MSSG) adopted the list of critical medicines for the COVID-19 public health emergency. The medicines included in the list are authorised...