Volunteering Computers for Science

Users Make Their Home PCs Available to Chase Medical Breakthroughs

Indian border security guards, who regularly contract malaria, are required to carry repellents and masks.

Agence France-Presse/Getty Images

The next cure for a major disease is as likely to be discovered on a computer as on a laboratory bench—and scientists are enlisting ordinary citizens to volunteer to help crunch the data.

Advances in computer science have enabled medical researchers to test how proteins fold, genes interact and pandemics spread in complex digital simulations of natural environments. As these simulations become more intensive and widely used, however, computers at academic institutions and other research facilities can't keep up with the demand for medical processing power.

Instead, scientists are tapping into a vast network that allows the research to be parceled out in tiny workloads that can be performed on anyone's household computer when it's not otherwise being used. So far, hundreds of thousands of people in countries around the world have volunteered their computers' processing power to help advance the cause of medical research.

Here's how it works: Volunteers download an application onto their home computer that links them into a network that includes other citizen volunteers and research scientists. The network assigns each computer a small bit of a project's puzzle to solve. The process, which continues as long as the computer is turned on but idle, typically takes several hours, but can vary depending on the project and the individual computer's power. When complete, the results are automatically sent back to the network's server.

In 2003, epidemiology researcher Nicolas Maire and his colleagues at the Swiss Tropical Institute in Basel began simulating how potential malaria vaccines would affect populations where the disease is most prevalent. They ran the program on a network of several dozen of their institute's computers. But as the research team graduated to the second phase of their project in 2006, adding more variables, complex interactions and data to their model, it became clear that they needed more processing power.

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