Principles of mechanistic modelling. The preconditions for performing mechanistic modelling of diseases, such as SCC in FA individuals, are clinical data derived directly from patients and experimental data obtained either in vitro from patient samples or in vivo. Additional data can be obtained from public databases and repositories (A). A mathematical model of regulatory networks is constructed after filtering and processing of the data on the level of either cells or whole tissues. The model is formalized using non-linear dynamical systems, which are calibrated and validated with the data (B). Next, the model is analyzed for robustness sensitivity, and ability to reflect abrupt phenotypic changes in response to perturbations, and resulting model predictions, e.g., the map between a risk factor and the disease severity, are compared with real-world data (C). The mathematical model can be used to systematically explore different types of treatment options for the SCC of an FA individual. Once validated, the most effective  predicted treatments  may then be applied to patients (D).