Solutions

Personalized medicine

Our Bayesian, causal network based methodology exploits supercomputing technologies to integrate massive amounts of data and knowledge from different systems biology levels and clinical sources. This technology allows a unique pharmacogenomic analysis of the relevance of factors and their interaction for the process of a disease and its sequential treatment. Using a joint decision theoretic cost-utility analysis for efficacy and side-effects, this technology gives a new chance to save failed drugs by personalization and aids in the development of personalized niche-busters.



Causal model and interaction of genetic factors methotrexate treatment in leukemia.