CAMBRIDGE, Mass., BOSTON and NEW YORK, Nov. 8, 2012 /PRNewswire/ --GNS Healthcare, Inc. (GNS), the leading healthcare data analytics company focused on enabling personalized medicine to improve human health, today announced that it has entered into a collaboration with Dana-Farber Cancer Institute (Dana-Farber) and Mount Sinai School of Medicine (Mount Sinai) to create a data-driven computer model of multiple myeloma, the second most common blood cancer in the U.S. that constitutes approximately one percent of all cancers. Created using GNS's supercomputer-driven REFS (Reverse Engineering and Forward Simulation) platform, the models will be used to help researchers discover novel therapies for the disease and to help determine the best existing treatments for patients.

"We have made encouraging progress at Dana-Farber Cancer Institute in using gene profiling, proteomic and signaling studies in tumor cell samples treated with existing and novel medicines to get a better understanding of myeloma pathogenesis and to develop novel targeted therapies," said Dr. Ken Anderson, Director, Jerome Lipper Multiple Myeloma Center and LeBow Institute for Myeloma Therapeutics at Dana-Farber and Kraft Family Professor of Medicine at Dana-Farber and Harvard Medical School.

"Because of this progress, our team is excited about deploying a powerful, supercomputer driven approach using our multi-layered genomic data to develop computer models to directly define the integrated underlying circuitry of myeloma. We look forward to using these models to identify, create, and implement better treatments for individual multiple myeloma patients," said Dr. Nikhil Munshi, Associate Director, Jerome Lipper Multiple Myeloma Center and LeBow Institute for Myeloma Therapeutics at Dana-Farber and Associate Professor of Medicine, Harvard Medical School.

"GNS will apply its Big Data analytics platform to create a disease-specific computer model that will yield a powerful new resource to the multiple myeloma research and clinical communitywith the ultimate aim of better outcomes for patients," said GNS CEO and co-founder Colin Hill. "This collaboration with Dana-Farber and Mount Sinai will create models that will help transform the tremendous amount of data coming from new technologies, such as next-generation sequencing, into predictive computer models of disease progression and treatment response for scientists and clinicians. This project is one of many examples of our work in challenging, complex and, sometimes rare, diseases."

In this collaboration, GNS will employ the REFSplatform to reverse engineer network models from next-generation genetic sequencing, proteomic, outcomes and other clinical data. Results from millions ofin silico simulations of the REFS models will provide new insights into the fundamental mechanisms of multiple myeloma, enabling the identification of novel intervention points in the disease for specific groups of patients and the development of more effective medicines.

"Prior published work has shown us that approaches like the REFS platform can develop integrated network models of disease that can be used to uncover novel drivers of disease," said Dr. Eric Schadt, Director of the Institute for Genomics and Multiscale Biology, Chair of the Department of Genetics and Genomics Sciences and the Jean C. and James W. Crystal Professor of Genomics at Mount Sinai. "With the wealth of detailed biological data available in this project, we look forward to a close collaboration with GNS to build a predictive model to elucidate novel insights into this complex disease."

About Multiple Myeloma

Multiple myeloma is a cancer of plasma cells, a type of white blood cell normally responsible for producing antibodies. In multiple myeloma, collections of abnormal plasma cells accumulate in the bone marrow, where they interfere with the production of normal blood cells. Most cases of myeloma also feature the production of a paraproteinan abnormal antibody which can cause kidney problems. Bone lesions and hypercalcemia (high calcium levels) are also often encountered. Myeloma is diagnosed with blood tests (serum protein electrophoresis, serum free kappa/lambda light chain assay), bone marrow examination, urine protein electrophoresis and X-rays of commonly involved bones. Myeloma is generally thought to be treatable but incurable. Remissions may be induced with steroids, chemotherapy, proteasome inhibitors (e.g. bortezomib), immunomodulatory drugs (IMiDs) such as thalidomide or lenalidomide and stem cell transplants. Radiation therapy is sometimes used to reduce pain from bone lesions. Myeloma develops in 1-4 per 100,000 people per year. It is more common in men, and for unknown reasons is twice as common in African-Americans as it is in white Americans. With conventional treatment, median survival is 3-4 years, which may be extended to 5-7 years or longer with advanced treatments. Multiple myeloma is the second most common hematological malignancy in the U.S. (after non-Hodgkin lymphoma) and constitutes 1 percent of all cancers.

About REFS

REFS (Reverse Engineering and Forward Simulation) is GNS Healthcare's scalable, supercomputer-enabled framework for discovering new knowledge directly from data. REFS automates the discovery and extraction of causal network models from observational data and uses high-throughput simulations to generate new knowledge.

See the original post here:
GNS Healthcare, Dana-Farber and Mount Sinai Collaborate to Build Computer Model of Multiple Myeloma

Comments are closed.