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Citizen Scientists Combine To Identify Effective Cancer Treatments

Citizen Scientists Combine To Identify Effective Cancer Treatments
technology

Now interested people can help fight major diseases from the comfort of their own home, on their own time.

John Pugh, BI
  • 18 november 2012

When Zooniverse, a citizen science site that hosts collaborative research projects, first looked to the skies in 2007 it was attempting to streamline the way we categorize galaxies by asking ordinary people to lend a hand. Just 14 months after launch they had 60 million classifications by hundreds of thousands of participants. The academic world has never been the same. Now Zooniverse is turning the power of crowdsourced research inwards to help understand how cancer cells respond to various treatments through a collaboration with Cancer Research UK.

The Cell Slider project is similar to Zooniverse’s previous endeavors in that volunteers will analyze images in ways that computers cannot, and in greater numbers than if only professionals were tasked with the research. The smartly designed website asks users to identify what kind of cells they see in an image – white blood cells, connective tissue or irregular cells. If they identify the appearance of mutations, they are prompted to count how many there are, what proportion of them are stained yellow, and how intensely they are stained.

It might seem difficult at first to identify what’s what if you’re not a microbiologist, but the site provides a helpful tutorial that guides users through the process of what to look for. In addition to the intuitive interface, each participant can access their personal profiles, which enables them to track their progress over time. To date, the project’s users have analyzed over 160,000 slides. Each image is viewed at least five times to reduce the inaccuracies that inevitably result from using nonprofessional analysts, and a portion of the slides have been looked at by experts to calibrate the results.

The objective of the project is to match the users’ analyses with how patients responded to a particular treatment. This will allow researchers to identify which treatments work best on certain types of cells and prescribe personalized treatments shown to be effective against the specific tumor type the patient has. Currently the Cell Slider project focuses solely on breast cancers, and if it proves to be a success, they plan to expand the scope to include other cancer types.

A whole new level of scientific discovery opens up for researchers willing to use this kind of research. By breaking down tasks into well-designed and publicly approachable chunks, projects that could take years are condensed into months or even weeks, saving money and, in this case, lives. Similar problems that involve visual interpretation and lots of data, such as the strengths of tropical cyclones, could be turned into games that incentivize users with badges, levels, status and rewards. The time devoted to such projects by participants could be even counted as volunteering. If researchers take leads from this and other citizen scientist contribution models like SETI@home, where people donate computer processing time to search for the existence of alien lifeforms, and fold.it, a puzzle-style game that explores how cell proteins fold in order to source more effective medications, there is no limit to what we can collectively achieve.

Cell Slider

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