The new big is small: Leveraging knowledge from small trials for rare disease drug development: Blarcamesine for Rett syndrome

Abstract

Big data in drug development may not satisfactorily address the demands of precision medicine in a rare disease population, making the use of smaller clinical trials necessary. Consequently, the use of innovative design and analysis of these clinical trials using model-informed approaches have become indispensable. This requires informative exposure–outcome analysis, together with formal statistical analysis, which should include the strength of evidence for a study outcome. We demonstrate how knowledge can be gained, with supporting strength of evidence, from a small (data) clinical trial with a low dose of blarcamesine in the treatment of Rett syndrome. Based on a small data paradigm, pharmacometrics item response theory modelling and Bayes factor analysis were used to demonstrate the efficacy of blarcamesine in Rett syndrome.