In the project we develop new machine learning methods for predicting the effects of drug combination treatments in complex diseases such as cancer, and implement novel clinical decision support tools that guide treatment decisions to optimize combinatorial therapies. This is expected to lead to increased treatment efficacy, individualization of therapy and reduced drug use and side effects, as well as reduced use of ineffective drugs and lower financial stress that the health care providers and the patients currently experience. The proposal is based on the top-level international expertise of the consortium on machine learning, systems pharmacology, tensorial data, and translational applications.