CAMBRIDGE, Mass. – August 10, 2017– GNS Healthcare (GNS), a leading precision medicine company that applies causal machine learning technology to large and diverse data sets to better match drugs and other health interventions to individual patients, today announced that it has entered into a license arrangement with Alexion for the rights to operate its REFS™ (Reverse Engineering and Forward Simulation) causal machine learning and simulation platform to accelerate rare-disease research and the development of new therapies.
The REFS technology, currently licensed by Celgene and other leading healthcare organizations, will enable Alexion scientists to reverse engineer models from large scale clinical, next generation sequencing and ‘omic data, and simulate those models to arrive at novel therapeutic insights for rare-diseases. The models generated by REFS will learn causal networks underlying pathogenic mutations linked to rare diseases, allowing Alexion scientists to interrogate the models to address “what if?” questions to elucidate biological mechanisms and identify novel targets. Moreover, Alexion, working in partnership with Sema4, will leverage the platform to decode rare-disease “genomic shields” — a buffering mechanism that enables patients with a pathogenic rare-disease mutation to resist the manifestation of the disease – and identify biomarkers of disease and drug response to stratify patient populations.
“We are excited to play a role in the journey to discover transformative therapies for patients with rare diseases,” said Iya Khalil, PhD, Co-Founder and Chief Commercial Officer of GNS Healthcare. “As innovative companies like Alexion harness analytics and big data to answer the toughest questions about disease mechanisms and drug response, REFS unique approach of reverse engineering disease models and simulating “what if?” scenarios unravel novel drug targets and biomarkers to help make these discoveries possible.”
“We are delighted to partner with GNS in applying causal networks across a broad spectrum of rare diseases to decode and address their pathogenic roots,” said John Reynders, PhD, Vice President of Data Sciences, Genomics, and Bioinformatics at Alexion. “I look forward to combining the GNS REFS platform with Alexion’s deep expertise in data sciences to accelerate the discovery of innovative medicines for patients suffering from a rare disease.”
GNS’ REFS platform was recently published in Cancer Research for its role in uncovering novel targets for triple-negative breast cancer. The high rate of validated predictions underscores the power of simulation in REFS, a new approach for quickly generating, at scale, new biological hypotheses relevant for diagnosing and discovering novel treatments for complex diseases, including multiple myeloma, colorectal cancer, and Huntington’s disease.
About GNS Healthcare
GNS Healthcare applies causal machine learning and simulation technology to predict which treatments will work for which patients, improving individual patient outcomes and the health of populations, while reducing the total cost of care. The GNS technology is based on its MeasureBase™ data integration architecture and patented REFS™ (Reverse Engineering and Forward Simulation) causal inference and simulation engine. Health plans, bio-pharmaceutical companies, healthcare providers, foundations, academic medical centers, and self-insured employers use GNS’ cloud-based solutions to solve pressing and costly problems including those surrounding metabolic syndrome, medication adherence, end-of-life care, preterm birth, personalized care pathways in specialty care, oncology, and diabetes, new drug target discovery, patient stratification in clinical trials, and more. GNS solutions focus on reducing adverse events, slowing disease progression, and improving therapeutic effectiveness through precision matching that maximizes impact on individual patient health outcomes while reducing wasteful spending and downstream medical costs. For more information, visit: www.gnshealthcare.com.
MacDougall Biomedical Communications