Review of the state-of-the-art in the field of compound combination modelling.
Significance of quality control of large-scale combination screening data.
Strategies for modelling combination effects using publicly available resources.
Importance of chemical and biological data integration for predictions.
Technical and scientific challenges of data integration in this context are discussed.