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Big data to aid cancer drug selection

Friday August 24th, 2018

Two major projects will harness the power of big data to significantly improve the choice of drugs for individual cancer patients, British researchers announced today.

In one project, researchers unveiled software that can predict disease-resistance to drugs long before clinical trials begin.

The software, developed at London’s Institute of Cancer Research, was unveiled in Cell Chemical Biology. It works by analysing up to 1,200 possible mutations and whittling this down to nine or ten.

Researcher Dr Teresa Kaserer said: “This will be hugely beneficial in designing new cancer drugs. Instead of reacting to what we see in the clinic – when it’s too late as patients have stopped responding to treatment – we can use our computational method to predict during the drug design stage how resistance will arise.

“It means we can begin designing second-generation treatments much earlier, as well as developing tests to select patients for treatment and monitor them while on the drug. This could be great news for patients, who could be switched to a second-generation drug as soon as a resistance mutation appears.”

In a second project, scientists at the Royal Marsden NHS Foundation Trust, posted on-line a “simple” prognostic tool that can deliver high quality predictions of the risk of long-term recurrent of breast cancer.

The tool can be found at www.cts5-calculator.com

Developer Professor Jack Cuzick, of Queen Mary, University of London,, said: “Hormone sensitive breast cancer is one of the few cancers where late recurrence is common, and predicting who is at high risk is particularly important so that they can continue hormone treatment.

“While our ability to predict this type of cancer is highly likely to improve in the future, we’re providing a simple tool which is available now, and is easily used and well tested.”

Cell Chemical Biology 23 August 2018

Tags: Cancer | Pharmaceuticals | UK News | Women's Health & Gynaecology

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