Training in Systems Approaches for the Next Generation of Life Scientists and Medical Doctors

Abstract

The last decades have challenged us with novel technologies and abilities to look deep into the human genome of each individual, to screen for numerous metabolites in the blood, to search organs by imaging techniques, and much more. We can collect data from all these measurements from humans with different (usually multifactorial) diseases and, in accordance with ethical rules, store the data safely, locally, or remotely. The human data is growing exponentially, from giga- (10⁹), tera- (10¹²) to peta- (10¹⁵) and zettabytes (10²¹), both in public and restricted access settings. However, everyone agrees that the technological and information booms have not yet sufficiently reached medicine and have so far only barely influenced the clinical settings. In this chapter, we discuss the opinion that without topping up the education system, it will be difficult to catch up. We propose that in addition to the classical medical education, which is traditionally good and highly respected in European countries, we must find ways on how to introduce into the medical curricula mathematical and big data aspects and insights. Only a global (systems) view on physiology and pathophysiology can break the Gordian knot of many multifactorial diseases where we still don’t understand the complexity of disease causes nor we can predict or cure the disease. We believe that the breakthrough is in the systems and interdisciplinary education and training, as early as possible in professional careers. If medical and related students and professionals would be formally educated in such interdisciplinary manner, they could take this knowledge further towards applications in their daily medical practice. We describe the current challenges and scattered best practices of introducing the wider systems medicine topics into the medical education as well as possibilities for systems medicine training at the doctoral and lifelong levels.