The ultimate goal of the MIT/Mayo PS-OC is to develop a multiscale predictive model connecting non-invasive imaging (tissue scale) to predicted therapeutic distribution (tissue-cellular scale) and dynamic molecular cellular response (cellular-molecular scale). To achieve this highly innovative and ambitious goal, we have assembled an interdisciplinary team with expertise in a wide range of cutting-edge analytical, imaging, and computational modeling tools. Although the measurements and some initial data handling and modeling will be performed in each project, the main tasks of the Data Handling and Integration Core include management of the large amounts of diverse data that will be generated in Project 1 and Project 2, extraction of key parameters from these large-scale data sets and images, integration of this information across platforms and scales to identify the key physical parameters governing therapeutic distribution and efficacy, and finally integration of multiple computational models at different scales to develop a multi-scale model linking non-invasive imaging to spatially heterogeneous drug distribution and drug efficacy. To achieve a robust model capable of predicting distribution for a range of therapies across a range of tumors with different parameters, we will utilize therapies ranging from small molecules to drug-conjugated antibodies, and will evaluate these therapies on a diverse set of patient-derived tumor models.