Lawrence Livermore National Laboratory, Frederick National Laboratory for Cancer Research, GSK, and University of California San Francisco will combine vast data stores, supercomputing, and scientific expertise to reinvent discovery process for cancer medicines
SAN FRANCISCO, Oct 27, 2017 -- Scientists from two U.S. national laboratories, industry, and academia today launched an unprecedented effort to transform the way cancer drugs are discovered by creating an open and sharable platform that integrates high-performance computing, shared biological data from public and industry sources, and emerging biotechnologies to dramatically accelerate the discovery of effective cancer therapies.
The goal of the consortium – Accelerating Therapeutics for Opportunities in Medicine (ATOM) – is to create a new paradigm of drug discovery that would reduce the time from an identified drug target to clinical candidate from the current approximately six years to just 12 months. ATOM aims to transform cancer drug discovery from a time-consuming, sequential, and high-risk process into an approach that is rapid, integrated, and with better patient outcomes -- using supercomputers to pretest many molecules simultaneously for safety and efficacy.
The consortium comprises the Department of Energy’s Lawrence Livermore National Laboratory (LLNL), GSK, the National Cancer Institute’s Frederick National Laboratory for Cancer Research (FNLCR), and the University of California, San Francisco (UCSF). ATOM welcomes additional public and private partners who share the vision.
“The goals of ATOM are tightly aligned with those of the 21st Century Cures Act, which aims in part to enable a greater number of therapies to reach more patients more quickly,” said FNLCR Laboratory Director David Heimbrook. “Although initially focused on precision oncology – treatments targeted specifically to the characteristics of the individual patient’s cancer – the consortium’s discoveries could accelerate drug discovery against many diseases.”
ATOM will develop, test, and validate a multidisciplinary approach to drug discovery in which modern science, technology and engineering, supercomputing simulations, data science, and artificial intelligence are highly integrated into a single drug-discovery platform that can untimately be shared with the drug development community at large.