Abstract

Personalized medicine strives to deliver the ‘right drug’ at the ‘right dose’ at the ‘right time’ by considering the unique characteristics that define specialized populations of patients and contribute to inter-individual variability, a leading cause of therapeutic failure when not properly considered. Given the challenges of studying specialized patient subgroups in clinical trials as well as the high degree of control necessary to tease out differences across populations, physiologically based pharmacokinetic (PBPK) modeling emerged as a key tool to evaluate complex clinical phenotypes and to predict the potential distribution of patient responses. Unfortunately, the inherent variability of biological systems and knowledge gaps in physiological data often limit confidence in model predictions for special populations. Thus, a critical step in model development for special populations involves an in-depth analysis of estimated model input and evaluation of the underlying physiological mechanisms leading to variability in pharmacokinetics, both of which may be guided by global sensitivity analysis and advanced statistical techniques.