ADAPTIVE CLINICAL TRIAL DESIGNS: APPLICATION OF BAYESIAN METHODS

Stacy R. Barnes, Averett University, Danville, Virginia, USA

Published in

JOURNAL OF INTERNATIONAL MANAGEMENT STUDIES
Volume 16, Issue 2, p85-94, October 2016

ABSTRACT

Bayesian probability theory is a mathematical construct designed for inference (deduction) based on experimentation and empirical data with the goal of making rational decisions. Even though its roots can be traced back more than two centuries ago, conclusions derived from the Bayesian Theory are often viewed with skepticism by many in various fields of endeavor. Nonetheless, more recently it has received greater attention; mainly because closer scrutiny of frequentist statistical inference leads to the underpinnings analogous to the foundations of Bayesian Theory and the growing importance of adaptive or flexible clinical trials. The purpose of this paper is to examine some applications of Bayesian Probability Theory in the field of medicine. The discussion centers around the fundamentals of Bayes Theorem and some pertinent illustrations and instances as to how it can be utilized in models concerning the management of accelerated pharma-drug development through adaptive (flexible) trial designs; and, in particular, those targeted in the treatment of rare diseases. Furthermore, we believe that there is enormous potential for producing targeted therapies concerning rare diseases that could significantly improve health outcomes.

Keywords

Bayes Theorem, Frequentist Methods, Adaptive (Flexible) Trial Designs, Rare Diseases


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