Scientists team with business innovators to tackle research hurdles
In a study that represents a potential cultural shift in how basic science research can be conducted, researchers from Harvard Medical School, Harvard Business School and London Business School have demonstrated that a crowdsourcing platform pioneered in the commercial sector can solve a complex biological problem more quickly than conventional approaches—and at a fraction of the cost.
Partnering with TopCoder, a crowdsourcing platform with a global community of 450,000 algorithm specialists and software developers, researchers identified a program that can analyze vast amounts of data, in this case from the genes and gene mutations that build antibodies and T cell receptors. Since the immune system takes a limited number of genes and recombines them to fight a seemingly infinite number of invaders, predicting these genetic configurations has proven a massive challenge with few good solutions.
The program identified through this crowdsourcing experiment succeeded with an unprecedented level of accuracy and remarkable speed.
“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,” said Eva Guinan, HMS associate professor of radiation oncology at Dana-Farber Cancer Institute and director of the Harvard Catalyst Linkages Program. “Given how complicated the immune system is, this has been a particularly formidable biological problem, and building tools for solving it has been hard and time-consuming. We were stunned by the power of these results and their potential application.”
“This study makes us think about how greater efficiencies in academic research can be obtained,” said Karim Lakhani, associate professor in the Technology and Operations Management Unit at Harvard Business School. “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. We’re showing that in certain instances, existing platforms and communities might solve these problems better, cheaper and faster.”
“We’re excited to see that ideas from economics and management fields can be so productively applied to medical research,” said Kevin Boudreau, assistant professor of strategy and entrepreneurship at London Business School. “This progress is heartening, particularly in view of the computational challenges we face in understanding so many diseases. We hope this provides a model of how social scientists and medical researchers can collaborate to solve real-world problems that matter to people.”
via Harvard Medical School – DAVID CAMERON
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