Bayesian methods are used as solutions for a wide variety of clinical trial challenges. The adoption of historical and external data into a clinical trial to supplement regulatory submissions is a growing use of Bayesian methods. Similarly, in therapeutic areas like oncology, where standard of care might evolve during the course of a clinical trial, statisticians trained in Bayesian methods can help salvage data collected during a clinical trial.
The nature of statistics is such that many common problems can be solved using both Frequentist or Bayesian methods, but with different investment of time and resources depending on the situation. Cytel’s consulting and RWE teams are trained in both the traditional Frequentist paradigm as well as Bayesian solutions for a vast range of scenarios.
At Cytel we believe that statisticians ought to be well-versed in both Bayesian and Frequentist statistical paradigms, so that they can apply the best solutions for our customers’ specific needs. Through our hybrid approach we will ensure that our customers receive tailored solutions that build on the best of both paradigms.