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  • Challenge: Expanding the immuno-oncology footprint Challenge: Making the integration of computational biology in cancer research routine

Oxford researchers are using the latest methods for integrating mechanistic and machine learning modelling to validate experimental data from animal models and spatiomolecular analysis of clinical specimens. By developing realistic simulations of solid tumour growth, infiltration and therapeutic resistance researchers are able to test hypotheses about the mechanisms driving observed tumour-immune interactions with the aim of predicting responses to treatments including immunotherapy and de-risking future immune-oncology clinical trials.