In silico approaches accelerate reverse translational research from bedside to bench

Abstract

Corresponding with accelerated computing power, such as that found in supercomputers, simulation and big data are becoming increasingly important to modern science, second only to experimental and theoretical sciences research. The field of medicine is said to have entered the era of big data, with significant progress in recent years in the development of increasingly sophisticated equipment for measurement, observation, and information and communication technology (ICT). In particular, greater precision in personalized medicine will require the analysis of a large quantity of individual genome sequences. Research and development of techniques to analyze big data with respect to individual genome sequences are an urgent need. In clinical medicine and epidemiology, the analysis of clinical big data or real-world data has attracted attention as a new approach, which can be applied to examining occurrences at an actual clinical site. In this review, we have discussed the challenges and potential of an in silico approach for reverse translational research.