SUNY Buffalo researchers will use IBM Netezza appliance and third-party software to seek cures for multiple sclerosis.
Researchers at the State University of New York (SUNY) at Buffalo are harnessing “big data” technology from IBM and another firm in the fight against multiple sclerosis.
The scientists will use IBM’s Netezza analytics appliance, combined with software from Revolution Analytics, to analyze huge databases and seek correlations among genetic, clinical, and environmental factors that might help reveal the causes or the acuity of MS in particular individuals.
The insights that the researchers derive from this approach might help pharmaceutical companies develop new drugs or might help physicians and patients better manage the disease, said Shawn Dolley, VP of big data, healthcare, and life sciences for IBM, in an interview with InformationWeek Healthcare.
The SUNY Buffalo scientists have been using Netezza, a massively parallel computing system, for the past two years and have published some papers based on that research, Dolley said. But the addition of Revolution Analytics’ application will greatly increase the number of variables they’re able to include in their analyses, he said.
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The big difference between what the researchers were doing earlier and what they’re able to do now is that, instead of using computers to test a particular hypothesis, they will use the Big Data approach to spread as wide a net as possible.
“The SUNY Buffalo people have said with the decreased cost of the IBM Netezza and its amazing processing power, they’re going to let the computer discover what the relevant phenotypes are and look at every combination of every possible variable across a large number of patients,” Dolley said. Phenotype refers to the physical characteristics of a patient that result from the interaction of his genetic makeup with the environment. According to an IBM press release, the researchers will be able to study more than 2,000 genetic and environmental factors that might contribute to MS. The reason for this scattershot approach is that scientists still understand relatively little about this condition, which affects 400,000 people in the U.S. MS is now regarded as a type of auto-immune disease, but environmental, genetic, and infectious factors might play roles in MS.
The UB researchers will incorporate patient data including medical records, lab results, MRI scans, and patient surveys, as well as genomic datasets obtained from the National Institutes of Health and other sources. Among the specific factors to be examined are patients’ gender, geography, ethnicity, diet, exercise, sun exposure, and living and working conditions.
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