Disease Data Intelligence

Disease Data Intelligence

The Disease Data Intelligence group works with patient health, disease predisposition as well as predicting treatment response and quality of life following chemotherapy. Projects include understanding development of childhood cancer (the germline-somatic continuum of mutations that lead to cancer), treatment response prediction in childhood cancer as well as adult testicular cancer, and not least prediction of disease progression in type-2 diabetes. In addition, we have worked with diet studies with an interest in predicting individual weight loss.


Modelling these patient journeys for most projects include patient genetics, information available at diagnosis, longitudinal blood biomarkers and when available other variables such as socioeconomics, diet, lifestyle. In some projects, microbiome and metabolomics data provide an enhanced predisposition landscape for an individual either as causal or proxy information for underlying mechanisms.


Most projects are characterised by the integration of heterogeneous data from various sources in order to find patterns and correlations. Just like military intelligence or business intelligence, the diversity of information sources are used to strengthen findings and build predictive models.


The eventual goal for the group is to understand development of diseases and improve treatments. Collaborations and partnerships are Danish and global, notably with clinical groups in order to partner on influencing treatment decisions.


Ramneek Gupta
DTU Health Tech