Bayesian adaptive clinical trial designs place subjects in treatment groups based on a posterior distribution. (Clinical trials accrue patients gradually, so you don’t have to assign the patients using the prior: you assign new patients using the posterior conditioned on observations of the current patients.)
These adaptive trials are, as you conjecture, much more efficient than traditional randomized trials.
Example: I-SPY 2.
Assigns patients to treatments based on their “biomarkers” (biological measurements made on the patients) and the posterior derived from previous patients.
When I heard one of the authors explain adaptive trials in a talk, he said they were based on multi-armed bandit theory, with a utility function that combines accuracy of results with welfare of the patients in the trial.
However, unlike in conventional multi-armed bandit theory, the trial design still makes random decisions! The trials are still sort of randomized: “adaptively randomized,” with patients having a higher chance of being assigned to certain groups than others, based on the current posterior distribution.
Bayesian adaptive clinical trial designs place subjects in treatment groups based on a posterior distribution. (Clinical trials accrue patients gradually, so you don’t have to assign the patients using the prior: you assign new patients using the posterior conditioned on observations of the current patients.)
These adaptive trials are, as you conjecture, much more efficient than traditional randomized trials.
Example: I-SPY 2. Assigns patients to treatments based on their “biomarkers” (biological measurements made on the patients) and the posterior derived from previous patients.
When I heard one of the authors explain adaptive trials in a talk, he said they were based on multi-armed bandit theory, with a utility function that combines accuracy of results with welfare of the patients in the trial.
However, unlike in conventional multi-armed bandit theory, the trial design still makes random decisions! The trials are still sort of randomized: “adaptively randomized,” with patients having a higher chance of being assigned to certain groups than others, based on the current posterior distribution.