Facebook, Google and Amazon will come together with Cancer Research UK and the Citizen Science Alliance this weekend at an event where 40 'hackers' will develop a smartphone game that aims to help the public find a cure for cancer.

GameJam will bring Cancer Research UK’s scientists together with computer programmers, gamers, graphic designers and other specialists to turn the charity’s gene data and the Citizen Science Alliance’s data analysis technology into a game, with the working title GeneRun, that will enable citizen scientists to analyse the data.

The event has received support from Facebook UK, which has provided expertise from its London engineering team and invited its contacts at universities to attend. Google is providing financial support and hosting the event in London’s Tech City and Amazon Web Services has offered to supply participants with free technology resources and expertise and will provide the platform to host the final game free of charge.

CRUK will then appoint, and pay, an agency to build the game and aims to launch it next summer.

Research into possible genetic causes of cancer produces a lot of data which needs to be analysed by the human eye to detect subtle changes that machines cannot.

Professor Carlos Caldas, senior group leader at the CRUK Cambridge Institute, University of Cambridge said: “By harnessing the collective power of citizen scientists we’ll accelerate the discovery of new ways to diagnose and treat cancer more precisely.”

Citizen Scientists reduce analysis time

It is the second project that CRUK has worked with the Citizen Science Alliance on. Cell Slider launched last October and is a website that asks members of the public to compare different tumour samples. So far more than 660,000 images have been analysed. Early results of the Cell Slider project suggest that for some trials the data analysis time has reduced by more than 12 months.   

Dr Harpal Kumar, chief executive of CRUK said: “By harnessing the collective force of the public, Cell Slider has already shown how we can dramatically reduce the analysis time for some of our clinical trials data from 18 to three months.”

 

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