The Inova Translational Medicine Institute (ITMI) at Inova Fairfax Hospital and GNS Healthcare today announced a partnership to develop and commercialize computer models capable of predicting risk of preterm live birth, built using next generation sequencing and electronic medical record data. GNS and ITMI will license the models and corresponding software to academic researchers, health systems, and pharmaceutical/biotechnology companies, paving the way for potentially more effective diagnosis and the reduction in risk of preterm birth.
While there is understood to be a genetic component, no individual genes have been identified as causative, to date.
"We are very excited to partner with the Inova Translational Medicine Institute," said Colin Hill, CEO and co-founder of GNS Healthcare.
"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. 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." The partnership will result in the commercial availability of the preterm birth predictive models and corresponding software, including optional access to the underlying ITMI data. The models will be built from ITMI's massive database, which includes both normal birth and preterm birth family cohorts, using GNS's data analytics platform, REFST (Reverse Engineering and Forward Simulation), and will link genetic and molecular factors with clinical data and health outcomes.
The ITMI database includes whole genome sequencing (SNP, CNV, SV), RNAseq expression, CpG methylation, proteomic, metabolomic, imaging, EMR, clinical phenotypes, and patient survey data for over 2400 individuals. These models will characterize the complex relationships among many variables in order to identify the associations and underlying causal mechanisms of preterm birth and will allow for personalized prediction of preterm birth risk and gestational length.
This, in turn, will help prioritize the testing of potential new diagnostic and treatment plans for at-risk patients.
"We have 826 families in our preterm birth study with 285 babies born at less than 37 weeks of gestation. 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," said John Niederhuber, EVP of Inova Health System and CEO of ITMI.
Joe Vockley, COO and CSO of ITMI added, "ITMI is excited to enter into this research agreement with GNS Healthcare. We see this work in preterm birth as a first step toward building similar prediction models for other complex genomic diseases, such as autism, diabetes and obesity, supported by ITMI's massive familial whole genome sequence databases. Prediction followed by prevention is a key component of translational medicine."