WIKIMEDIA, ANDRE ENGELSThough it affects one out of every nine babies born in the United States, scientists know surprisingly little about what causes preterm birth. To address the issue, two organizations are hedging their bets on big data and genomics, partnering to develop computer models that can predict the risk that a woman’s child will be born before reaching 37 weeks of gestation.
The Cambridge, Massachusetts-based big data firm GNS Healthcare is collaborating with the Inova Translational Medicine Institute (ITMI) at Inova Fairfax Hospital to mine next-generation sequencing data and electronic medical records gathered by Inova using GNS’s analytics platform, with the goal of commercializing preterm birth predictive models and corresponding software.
“The causes of preterm birth are complex and in about half of cases, are unknown,” the GNS and Inova noted in their announcement. “While there is understood to be a genetic component, no individual genes...
Researchers at the ITMI are currently following a cohort of 285 premature babies as part of a larger preterm birth study involving 826 families. “Partnering with our colleagues at GNS provides the best opportunity to build a risk assessment/predictive model that takes into account the many variables, including genomic, clinical, environmental, and behavioral factors, that combine to cause a preterm delivery,” ITMI CEO John Niederhuber said in a statement.
“Using ITMI’s unprecedentedly rich and multimodal preterm birth genomic data set, we will build models that can document the complex interactions underlying preterm birth,” added Colin Hill, GNS Healthcare CEO. “These models will create new ways for clinicians and scientists to understand these interactions and will accelerate the discovery of new diagnostic tools and treatments for this condition, as well as other complex conditions.”
But as Fierce Biotech noted, “there are no guarantees that such big data analysis holds the key to cracking the mysteries of a complex health problem like preterm birth.”