Precision medicine in oncology is becoming reality thanks to the next-generation sequencing of tumours and the development of targeted inhibitors enabling tailored therapies. Many clinical trials base their strategy on the identification of mutations to deliver the targeted inhibitor that counteract supposedly the effect of a mutated gene. Recent results have shown that this gene-centered strategy can be successful, but can also fall short in stopping progression. This is due to the many compensation mechanisms, cross-talks and feedback loops that enable the tumoral cell to escape treatment. Taking into account the regulatory network is necessary to establish which inhibitor or combination of inhibitors would achieve the best therapeutic results. Mathematical modelling of biological networks, together with high-quality pathway databases collecting our knowledge of the molecular circuitry of normal and tumoral cells, hold the hopes of an enhanced future for precision medicine in oncology.