Revisiting the Concept of Human Disease

Current network-based models, their heuristic and epistemological value notwithstanding, only partially explain the unfathomable complexity behind the outbreak of a disease, as they are habitually centered on an integrated representation of the cell biochemical and genetic pathways, and, as such, they discard the contribution of non-genetic factors and microenvironmental constraints. Thereby, since the eighties, the agenda of pharmacology discovery was then dictated by aiming at discovering “relevant” molecules (along with their classical rules of interaction), abstracting from the true, physiological response of cells, tissues and organism. In this perspective, genes assume the fundamental causal role while cells simply act as causal proxies, dispensable because they represent an irrelevant intermediate level between the molecular input and the organismal output. Such framework, both theoretically and methodologically, is no longer tenable. We propose herein a comprehensive model able in capturing the complexity on which the disease relies, thus recognizing a different spatially (multi-level) and timely distributed target array. Moreover, given that a disease is properly a dynamic process and not a steady state, treatments should also be diversified according to the timing of the disease process. This approach can help in detecting pre-disease state or critical transition points from which the illness might access different attractors, leading ultimately to different outcomes. We should thus design systems-oriented drugs that tackle both the multifactorial pathogenic determinants of the disease as well as the intrinsic robustness of the living organism, by promoting a polyvalent-based approach, i.e. the use of multiple drugs or drugs affecting several targets localized at different levels. Additionally, above and beyond classical pharmacodynamics, unconventional mechanisms of action urge to be investigated and integrated within network modelling. Overall, this implies that we should shift from targets to processes, to “redraw” the disease-related landscape, favoring the system displacement from pre-clinical state or true disease-states towards healing pathways.