Analyzing Drug Effectiveness through Advanced Computing



The Department of Energy (DOE) national laboratories (Lawrence Livermore, Los Alamos, Argonne, and Oak Ridge) are teaming up with the National Cancer Institute (NCI) for a three-part pilot program designed to integrate supercomputing into cancer patient treatments. The program will stretch the scientific frontiers of supercomputing and lay the foundation for the next major advances in cancer therapy. In the first pilot—Predictive Modeling for Pre-Clinical Screening—scientists aim to use advanced computation to rapidly develop, test, and validate predictive pre-clinical models for precision oncology. This will allow for the identification of promising treatment options, as well as requirements for future technologies needed to support an integrated approach to scalable modeling, machine learning, and large-scale data analysis. Advances achieved in this first pilot will facilitate new therapy options for cancer patients while also impacting the development of future computer architectures.

This first pilot supports both NCI’s and DOE’s missions on multiple fronts. For NCI, it will develop a library of validated prediction tools for projecting drug screen results and improve the efficacy of drug selection for patients; for DOE, it will allow for the application and integration of advanced computing in functional areas such as machine learning and data analysis and simulation. This will ultimately help researchers gain insights into tumor biology and better predict patient responses to cancer treatment.

For more information visit the National Cancer Institute: Center for Biomedical Informatics & Information Technology