GNS turns to Big Data to crack multiple myeloma
GNS Healthcare has teamed up with Dana-Farber and Mount Sinai to build a Big Data-driven computer model of multiple myeloma. The project will combine GNS' computing power with data from next-generation sequencing to support the development of personalized medicines.
Big Data and major computing grunt are at the heart of the initiative. GNS will apply its supercomputer-powered REFS (Reverse Engineering and Forward Simulation) platform to the wealth of data generated by technologies like next-generation sequencing. This combination of multi-layered genomic data and serious computing power has only become possible recently, and researchers are excited about the potential.
GNS CEO Colin Hill is optimistic that the technology can lead to better patient health outcomes. "The data and the technology are really in a different place now. We are talking about remaking the whole medical landscape," Hill told Xconomy. The collaborators are aiming to develop more accurate models of disease progression. "We're now in a position with these rich data sets to really pinpoint the most efficacious drug targets," Hill said.
Such knowledge could support the creation of more targeted therapeutics that deliver big blows to the disease without too many side effects. And existing therapeutics stand to benefit too, with the improved understanding of genetic factors possibly allowing for the tailoring of treatment regimes to individuals. Even incremental gains in health outcomes could have a big impact on the lives of the 20,000 Americans diagnosed with multiple myeloma each year. At present 60% of people are dead within 5 years of being diagnosed with the blood cancer.
Researchers at Dana-Farber are keen to slash this figure using insights gained in the collaboration. Dana-Farber is already using gene profiling and proteomic studies to improve understanding of multiple myeloma, and feels REFS can accelerate progress.
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