A large amount of research work together with recent advances in technology including novel imaging techniques and high resolution genomic studies advocate that tumors are incredibly complex, highly heterogeneous, self-organized biological systems spanning multiple temporal and spatial scales. More specifically, tumors involve processes at i) microscopic level where molecular interactions like signaling and metabolic reactions occur, ii) at cellular and mesoscopic level where cells interact with each other and their local microenvironment, and iii) extend further to tissue-level dynamics. The involved biological processes are strongly coupled and the challenge is to appropriately incorporate them into a complete description, utilizing the available knowledge and data to better understand and predict how tumors evolve.

Because of the complexity and diversity of the mechanisms involved in tumor evolution, mathematical and computational approaches (a.k.a. in silico) aiding in our understanding, become inevitable. We postulate that the construction of a faithful, patient-specific mathematical model that incorporates the underlying mechanisms and the involved interactions and heterogeneity could explain the potential outcomes and provide guidelines for optimal therapy planning, better understanding of tumor pathophysiology and dictate future experiments.

In this direction, the INSEPTION group adopts the Systems Biology strategy to improve understanding of cancer complexity and increase predictive power with personalized clinical relevance, combining novel biological experiments, imaging techniques and advanced in silico methods. The INSEPTION group argues that cancer can only be deeply understood and cured through the collaboration among scientists from different disciplines that could potentially bridge the gap between basic science and the clinic.