Application of proteomic data in the translation of in vitro observations to associated clinical outcomes

Abstract

Translation of information on drug exposure and effect is facilitated by in silico models that enable extrapolation of in vitro measurements to in vivo clinical outcomes. These models integrate drug-specific data with information describing physiological processes and pathological changes, including alterations to proteins involved in drug absorption, distribution and elimination. Over the past 15 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. In this review, we explore current and emerging applications of targeted and global (untargeted) proteomics in translational pharmacology as well as strategies for improved integration into model-based drug development.