Researchers from the University of California (UC) have collaborated with affiliated national laboratory scientists and industry experts to use advanced supercomputing capabilities for the development of new and personalised cancer treatments.

The researchers will exploit the high-performance computing and deep machine learning that would help develop effective cancer therapies more quickly and accurately.

The public-private effort will support the university’s partnership with Lawrence Livermore National Laboratory with the aim of speeding up the process of cancer treatment development that currently takes about five to ten years.

Known as Accelerating Therapeutics for Opportunities in Medicine (ATOM), the collaboration will enable the new drugs to be ready for patient testing within a single year from initial discovery.

Lawrence Livermore National Laboratory Computation deputy associate director Jim Brase said that the new predictive simulation technology will allow researchers to quickly evaluate millions of molecules to test their potential therapeutic efficacies.

“This UC programme has reinvested a substantial portion of the income received from managing the national security labs back into research and training.”

As part of the national Cancer Moonshot, the ATOM project has received a $3m funding from UC for a period of three years.

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The research work will be carried out at UC San Francisco’s Mission Bay campus.

The National Cancer Institute and GlaxoSmithKline (GSK) have also joined the project as partners.

UC National Laboratories vice-president Kimberly Budil said: “This UC programme has reinvested a substantial portion of the income received from managing the national security labs back into research and training, creating a pipeline of skilled researchers for the national labs and long-lasting academic partnerships.”