In the systems health theme, we work in close collaboration with clinical investigators. Together with them we go through cycles of reciprocal feedback in which we provide the results of our computational and statistical analysis, and mathematical modelling on their patient data. In this way we try to predict disease onset, progression, and remission mechanisms, and to inform clinical decisions. We do this both at the epidemiological and at individual patient level.
This new paradigm for studying health and disease complements the traditional reductionist approach and will lead to the identification of mechanisms of pathophysiology, selection of novel drug targets and biomarkers, patient risk assessment and, ultimately, to individualized treatment.
Methods and approaches
We apply systems approaches to a variety of different contexts. For example, the investigation of host-pathogen interactions in the context of soft tissue necrotizing infection and sepsis, bacterial diversity and pathogenicity, cancer, cardiovascular diseases and disease risk, inter-individual variability in healthy people, as well applications to animal pathophysiology and well-being.
Our methods involve:
- network analysis
- machine learning techniques
- mathematical modelling