CAMBRIDGE, Mass.– April 13, 2018– GNS Healthcare (GNS), a leading precision medicine company, will present results from a recent study on Friday, April 13th at the International Liver Congress™ 2018 in Paris.
The analysis focused on the progression of Nonalcoholic Steatohepatitis (NASH), a type of advanced liver disease. Specifically, the objective was to build predictive models of survival to the onset of cirrhosis or a clinical event, such as a liver transplant or disease complication. Using its causal machine learning platform, REFS, GNS built two different types of models: models that included data from invasive diagnostic measures (like biopsies) and models that did not.
At the conclusion of the study, the models that did not include invasive diagnostic measures performed just as well at predicting the onset of cirrhosis or clinical events as those that did. The results demonstrate how machine learning has the ability to model and predict, using non-invasive data sets, risk of clinical disease progression in patient with advanced fibrosis due to NASH.
NASH is a liver disease involving inflammation and liver cell damage. It is often underdiagnosed as patients experience non-specific symptoms and there are no medications currently approved by the U.S. Food and Drug Administration (FDA) for treatment. Some estimates predict that by 2020, NASH will become the leading reason for liver transplants in the U.S.
“We may now have the ability to understand disease progression in a way we never have before. By leveraging the power of artificial intelligence, we have the potential to better understand the disease with an ultimate goal of preventing the need for invasive testing,” said Colin Hill, Chairman, CEO, and co-founder of GNS Healthcare. “Advanced fibrosis due to NASH is becoming more prevalent so the need to understand it at a patient level is more crucial than ever.”
The poster (#466) will be viewable at the conference Friday, April 13th, and the abstract can be found on the International Liver Congress website here. The study was conducted in collaboration with Gilead Sciences.
REFS™ (Reverse Engineering & Forward Simulation) is GNS Healthcare’s patented causal learning and simulation platform. Unlike traditional artificial intelligence platforms, REFS analyzes data sets beyond correlation, instead inferring causal mechanisms between variables to answer questions such as: How will the patient respond to this treatment? What if we choose one intervention over another? REFS is the only commercially available platform that infers causal mechanisms from patient data at scale from traditional healthcare and emerging data sources to bring the promise of precision medicine within reach.
About GNS Healthcare
GNS Healthcare solves healthcare’s matching problem for leading health plans, biopharma companies, and health systems. We transform massive and diverse data streams to precisely match therapeutics, procedures, and care management interventions to individuals, improving health outcomes and saving billions of dollars. Our causal learning and simulation platform, REFS, accelerates the discovery of what works for whom and why.