Biomedical field and the Big data issues

The arrival of "big data" in healthcare coincides with the emergence of so-called "precision" medicine , i.e. medicine where the aim is to take better account of patients in terms of both their overall pathology and their individual characteristics. The French National Authority for Health (HAS) refers to this as the 5B rule , i.e. "administer the right medicine, at the right dose, on the right route, at the right time, to the right patient". One of the driving forces behind precision medicine is the dual ease of access to objective data and on-the-fly calculation that is characteristic of "big data". The digitization of health data, which is becoming an increasingly important part of patient care and treatment, is making it more and more feasible. Nevertheless, if the medical field, like others before it, is set to be transformed by on-demand calculations based on data that has become more accessible because it has been digitized, we need to question the very substratum of a real or supposed Big Data revolution. Indeed, it is first and foremost the nature of the data to which we now have massive access (big data) that contains the uses, hopes and limits of the emergence of new medicine in the big data era. This article highlights five characteristics of health data to help us understand the challenges of Big Data in healthcare, and to make a wide range of applications possible in this field.