This paper presents a brief overview of the recent literature on adaptive design of clinical
trials from a Bayesian perspective for statistically not so sophisticated readers. Adaptive …

Background Randomization is the foundation of any clinical trial involving treatment
comparison. It helps mitigate selection bias, promotes similarity of treatment groups with …

While interest in the application of machine learning to improve healthcare has grown
tremendously in recent years, a number of barriers prevent deployment in medical practice …

Abstract Response-Adaptive Randomization (RAR) is part of a wider class of data-
dependent sampling algorithms, for which clinical trials are typically used as a motivating …

Abstract The Staphylococcus aureus Network Adaptive Platform (SNAP) trial is a
multifactorial Bayesian adaptive platform trial that aims to improve the way that S. aureus …

In adaptive clinical trials, the conventional end‐of‐trial point estimate of a treatment effect is
prone to bias, that is, a systematic tendency to deviate from its true value. As stated in recent …

Theoretical‐information approach applied to the clinical trial designs appeared to bring
several advantages when tackling a problem of finding a balance between power and …

Clinical trials of a vaccine during an epidemic face particular challenges, such as the
pressure to identify an effective vaccine quickly to control the epidemic, and the effect that …

Major Depressive Disorder (MDD) is one of the most common causes of disability
worldwide. Unfortunately, about one-third of patients do not benefit sufficiently from available …

Bayesian adaptive designs formalize the use of previous knowledge at the planning stage of
an experiment, permitting recursive updating of the prior information. They often make use of …