In this opinion paper we make the statement that hybrid models in oncology are required 4 as a mean for enhanced data integration. In the context of systems oncology, experimental and clinical 5 data need to be at the heart of the models developments from conception to validation to ensure 6 a relevant use of the models in the clinical context. The main applications pursued are to improve 7 diagnosis and to optimize therapies.We first present the Successes achieved thanks to hybrid modelling 8 approaches to advance knowledge, treatments or drug discovery. Then we present the Challenges than 9 need to be addressed to allow for a better integration of the model parts and of the data into the 10 models. And finally, the Hopes with a focus towards making personalised medicine a reality. 11 Mathematics Subject Classification. 35Q92, 68U20, 68T05, 92-08, 92B05. 12