Combinatorial therapeutic discovery in cancer through the integration of network medicine and statistical genomics

The heterogeneity of cancer explains why so many of the new targeted therapies have failed to live up to their early promise and only work in a small fraction of patients. In addition, patients that do initially respond to therapy often become refractory over time, as their tumor evolves resistance. In order to deal with this complexity and to discourage the development of resistance, drugs will have to be prescribed in intelligent synergistic combinations, which are modified over time to match the geneti c and phenotypic changes occurring within the tumor. While the scope for this type of intervention is currently limited, due to the relatively small number of approved targeted therapies, this picture is set to change dramatically over the next 5-10 years . Thus, one of the key challenges in oncology over the next decade will be learning to manage the growing arsenal of targeted therapies in an intelligent manner, in order to maximize patient outcomes. If this can be achieved, it will help transform this o nce deadly disease into a chronic condition, which can be managed through the judicial selection of powerful synergistic combinations of drug and regular monitoring, in a manner similar to AIDS. While the rapid adoption of NGS in clinical diagnostics and a rich phase III pipeline of targeted cancer drugs support this vision of the future, the biggest bottleneck will be the development of intelligent bioinformatics solutions that can organize, integrate, and analysis this complex data in a holistic manner, allowing the clinician to squeeze the maximum clinical benefit out of his/her limited (but growing) arsenal of drugs. This project will develop a unified bioinformatics framework that can help change this paradigm; enabling the clinician to tailor patien t-specific treatment programs, that co-ordinate the different treatment programs, that co-ordinate the different treatment options available, in a synergistic manner, in order to more effectively manage disease.