Empowering Statisticians To Create Complex Bayesian Clinical Study Designs

In the world of clinical trials, the pace of innovation is accelerating, and approaches such as Bayesian methods are gaining traction. These methods bring flexibility and speed to clinical trial design and analysis, and with increased access to the necessary computational power, are transforming today’s clinical research ^[1]. However, the number of simulation and modeling tools necessary to perform Bayesian computations requires statisticians to be well-resourced technologically. Many biostatisticians may not readily have access to the cloud computing power to make these design approaches practical within the time constraints afforded for statistical design.

There are many dose-finding designs that have been developed over the past 30 years and several more are anticipated ^[2]. Sponsors often face the dilemma of choosing from the various design options available today. Finding the right dose in Phase 2 gives a potential new therapy its best chance to demonstrate efficacy during Phase 3, and Bayesian techniques prove to be useful for optimal dose-finding.