Precision medicine is an emerging approach that uses individual data to determine the most appropriate therapy for each patient. These data are often captured from various multi-omics sources and arise from mechanisms organized across multiple scales of biological hierarchy. Indeed, biological systems are regulated by processes spanning from the molecular to the population level. The heterogeneity of data sources represents an obstacle in precision medicine. Multiscale modelling is an approach that describes the underlying processes that regulate living systems across multiple scales. Thus, it has the potential to bridge the gap between scales and identify new mechanisms. our research goal is to build in silico tools that help biologists gain insights into complex living systems and assist clinicians in the prediction of the best therapeutic plans for individual patients. To achieve this, we develop systems and multiscale models, using available multi-omics data, and leveraging key collaborations with biologists and medical doctors. For the future, we aim to combine my computational models with artificial intelligence to build intelligent, trustworthy and transparent systems that rapidly predict the response of specific patients to treatment regimens. So far, we are exploring living systems originating from:

• erythropoiesis (red blood cells production),

• blood coagulation,

• infectious diseases,

• tumor growth,

• immune response,

• developmental biology,