In clinical research, Bayesian statistics provide a framework in which information beyond that collected in a particular clinical trial can be used to make statistical inferences about the treatment outcomes. Prior information (from previous trials, scientific research or “expert opinion”) can be combined with information as it is accrued during a trial, as well as with the usual data available on completion of the trial, to make efficient and timely inferences about the safety and/or efficacy of a treatment or therapy.
Due to the expensive nature of clinical trials, more and more pharmaceutical companies are becoming interested in Bayesian methods; and with on-going algorithmic development and improved computational speeds, these methods are becoming increasingly accessible and accepted.
At Quanticate our statistical consultants are experienced in clinical study designs and have delivered multiple trial analyses using Bayesian methods. We can provide expert advice on Bayesian adaptive designs with an approach that typically includes: