[Patients torn to pieces.] / Pazienti fatti a pezzi.

ABSTRACT

Dissecting bodies is a common practice in many cultures. But in "big data medicine", the art of dissecting the human body has become an obsession. Indeed, modern biotechnology allows us to see and measure the molecular components of every single cell. But how can we put this immense number of bits and pieces back together again and see the patient as a whole? The first turning point is that proposed by René Descartes, who, inspired by dreams and visions, conceived the idea of unifying all scientific disciplines through the pervasive application of mathematics. Descartes formulates four basic rules, the second (top-down method) and third (bottom-up method) of which become crucial in modern data analysis. An instructive case study considered here is that of pulmonary tuberculosis, where the Cartesian approach of decomposing problems into smaller and smaller "pieces" - from organism to organ and from cellular lesion to the microscopic level - has led to the cure of the disease through antibiotics. This success story inspired Paul Ehrlich who, with the concept of the "magic bullet", defined modern pharmacology. However, this paradigm is being challenged today by multifactorial diseases and big data medicine, where the enormous availability of clinical and molecular data must be integrated to arrive at a therapeutic decision. The Cartesian approach shows its limitations today, as witnessed by the similar difficulty in fields other than medicine, illustrated here by the case of choosing to produce a successful television series based on user profiling. The take-home message is that the amount of data collected does not automatically guarantee success but that, instead of being data-driven, a collective "human" overview and assessment is inevitable. That is, close collaboration between clinicians and data analysts, integrating expertise, is needed to address challenges in the diagnosis and treatment of complex diseases through imagination and not mere extrapolation.