Clinical Research Design and Statistical Analysis for Personalized Medicine

Abstract

Interindividual variation in drug response among patients is well known and poses a serious problem in medicine. The variation could be due to multiple factors including those of the host (e. g., age, genetic and environmental factors) and disease (pathophysiological phenotypes). The complex interplay of these factors may influence pharmacodynamic responses such as adverse effects and efficacy, as well as pharmacokinetic manifestations. However, at present, few biomarkers can predict responders and non-responders, and those who might experience adverse reactions for the same medication and dose. In order to realize personalized medicine, rigorous development of biomarkers is required to identify new biomarkers that may change clinical practice.
In this review, we first introduce how biomarkers may be used as targets and the difference between prognostic and predictive markers. Next, we focus on confirmatory clinical trial designs for biomarker development and introduce their application in actual studies. Finally, we introduce exploratory statistical screening techniques for detecting biomarkers in phase I and pharmacokinetics studies.