Abstract
Although personalized medicine appears to be a truism, medical doctors are still generally trained in an old-fashioned manner with a focus on reactive treatment. The aim of this paper is to emphasize the evolution of life sciences into a more predictive science, where the development of quantitative models is starting to take place. Personalized medicine is a consequence of such paradigm shift. To keep up with the change, the various actors within the health system must be trained in a completely different manner, focusing on the ability to work as part of a multidisciplinary team that includes medical doctors, nurses, engineers in medical imaging, and others who collect information from patients. In addition, these teams should include modelers that are able to integrate the flood of data into predictive and quantitative models. The challenge of implementing new training methods in line with the shift is a major bottleneck to the emergence and success of personalized medicine in our societies.