A case study in teaching and learning the design, conduction, and analysis of Bayesian adaptive trials through an application.

Introduction: Gaining clinical trial design and management experience can be challenging for students in class. Opportunities for students to participate in designing and implementing a "from scratch" design are essential to succeeding after graduating. Limited materials are available that provide meaningful opportunities for learners to practice and implement adaptive trial design. As a solution, we developed an open-source case study framework that instructors can use directly in a course to give students hands-on experience with Bayesian adaptive trial design and implementation. Materials and methods: We developed an open case study (DRIVE trial) project, which offers an instructor-ready framework organized into seven components. Each component is designed to map onto a distinct stage of a clinical trial and include materials that instructors can adapt to match their course level and chosen scientific questions. These components are tied together by a worked example in which, after comparing multiple study designs, a Bayesian adaptive design with response adaptive randomization was chosen and implemented throughout the framework. Results and discussion: The framework provides instructors with a complete, ready-to-use template for bringing adaptive trial experience into the classroom without building a case study from scratch. The study's significance lies in its broader implications for biostatistics student training and experience. The trial underscored the effectiveness of comparing study designs and the necessity for collaboration when implementing a clinical trial. This offers valuable practical training and resources for future biostatisticians, serving as a template across various fields. Supplementary materials for this article can be found online (https://github.com/BayesPhase/DRIVE).