Researchers from Harvard Medical School, Harvard Business School and London Business School recently collaborated on a study using crowdsourcing as a problem-solving tool for complex biological issues. Study partner TopCoder, a crowdsourcing platform with a large global community, joined the research team in an effort to capture the potential value of open innovation for conducting basic scientific research.
Opening the challenge of creating a system (that can analyze a wealth of data to predict genetic configurations in the immune system) to the community yielded a program with unprecedented accuracy and results. Two weeks after the contest was opened, 122 different individuals posited solutions. From there the viable options were narrowed to 16, which were more accurate and up to 1,000 times faster than either Arnaout’s or the NIH’s BLAST algorithm. The top five were released under an open source license.
The experiment and study found that bringing different knowledge pools together from social science, economics and computational science developed new, innovative approaches to medical research processes at a fraction of typical costs.
“In a traditional setting, a life scientist who needs large volumes of data analyzed will hire a postdoc to create a solution, and it could take well over a year,” explains Karim Lakhani, of the Technology and Operations Management Unit at Harvard Business School, and one of the authors. “We’re showing that in certain instances, existing platforms and communities might solve these problems better, cheaper and faster.” Eva C. Guinan, HMS Associate Professor of radiation oncology at Dana-Farber Cancer Institute and Director of the Harvard Catalyst Linkages Program adds:
“This is a proof-of-concept demonstration that we can bring people together not only from different schools and different disciplines, but from entirely different economic sectors, to solve problems that are bigger than one person, department or institution.”
Extending problem-solving to the crowd of 450,000 specialists and developers at TopCode exhibits the potential of alternative organizational procedures for increasing cost-effective productivity.
For the full report on the project, more information can be found here.