This Program Project comprises four individual projects, which will: implement evidence-based sequential multiple treatment assignment strategies for patients predicted to have insufficient response to their initial neoadjuvant targeted and/or chemotherapy, (Project 1); qualify non-invasive imaging methods as early markers of non-response (Project 2); characterize the biology of non-responders to inform treatment selection (Project 3); and develop a portfolio of agents and decision tools for treatment re-assignment matched to biology of non- responding tumors (Project 4). The overarching goal of the Information Technology (IT) and Systems Integration Core is to develop an informatics infrastructure for the storage, integration and dashboard visualization of clinical, molecular and imaging data collected within the proposed I-SPY 2+ Program Project framework. Specifically, we will review and leverage the existing I-SPY 2 data infrastructure to design and implement a functional user interface that will enable role-based access and integrated visualization of data within and across projects with the I-SPY 2+ Program Project framework. This dashboard visualization will be extensible and capable of providing relevant data summaries and reports in support of all Projects in the Program. In addition, the dashboard will provide flexible integration of algorithms from other environments such as R code generated by the Bioinformatics and Statistics Core for longitudinal modeling of non-response based on imaging (Project 2) and molecular biomarkers (Project 3), and will allow for visualization of predictive modeling results of breast cancer data within and across project teams within the I-SPY 2+ Program Project Framework via secure, role-based access. Integration of tools to report patient adverse event and quality of life will reduce the time spent extracting information manually from disparate sources, reduce errors, and potentially allow real-time monitoring. Collectively, the capabilities enabled by the data visualization dashboard will be a critical component towards achieving the overall Program Project goal of building and implementing robust, evidence-based decision algorithms to enable treatment to be adapted for individual women with high risk breast cancer.