The Canadian Bayesian Adaptive Trials (CanBAT) Network

The CanBAT Network focuses on four distinct projects led by trainees at institutions throughout Canada. These projects focus on:

Platform trials

Platform trials aim to assess multiple research questions using a single trial infrastructure, but novel methodology is required to efficiently exploit this infrastructure and answered the proposed research questions with minimal patient burden and costs.

Dose finding trials

Statistical methods in dose finding trials aim to accurately determine the optimal dose based on a small number of patients. The proposed methodology will improve the chances of evaluating safe and effective treatments in later trials.

Computationally efficient design of trials

Intensive simulations are currently required to design Bayesian adaptive trials. We aim to build on efficient Bayesian simulation algorithms to reduce computational complexity of these simulations and provide accurate uncertainty quantification to dramatically improve the feasibility of designing Bayesian adaptive trials.

Decision theoretic trials

Bayesian decision theory provides a principled framework for trial design, but its practical implementation is prevented by computational issues. Leveraging Area #3, we aim to develop novel algorithms to efficiently estimate key quantities and optimise Bayesian adaptive trials that support clinical decision making.