The level of complexity in developing combination immune-oncology (IO) therapies could be unprecedented since it is likely that different modalities (biologicals, small molecules, gene therapies, vaccines) targeting diverse biological pathways (IO and non-IO) will be combined in different cancer types. A major challenge is that choosing successful combinations cannot be done randomly, but requires intelligent guidance. Further, the potential number and types of IO combinations cannot possibly be tested clinically. A Quantitative Systems Pharmacology (QSP) approach for developing combination immune-oncology therapies can be used to better predict effective drug combinations, especially to more accurately correlate the physiological differences between preclinical models and human patients. A QSP IO Consortium has been brought together with leading biopharmaceutical companies in a pre-competitive environment to cooperatively develop a robust Immuno-oncology Simulator, based on state-of-the-art QSP science and methods.