Industry and Patient Groups Join Forces to Form an Alliance to Accelerate Drug Development

GNS Healthcare has announced that it has joined in the formation of Orion Bionetworks. This unique alliance will work to transform our understanding of and accelerate the drug development process for a wide variety of diseases, beginning with multiple sclerosis (MS). Using patient data from alliance members Accelerated Cure Project for Multiple Sclerosis, the Institute for Neurosciences at Brigham and Women's Hospital, and PatientsLikeMe, GNS will build powerful, predictive, computational models to yield new information about the disease, which will pave the way for more effective treatments for patients and the discovery of new therapies and cures. The initial phase of this effort is made possible by a $5.4 million commitment by Janssen Research & Development, a subsidiary of Johnson & Johnson.

Other crucial alliance groups include the Marin Community Foundation, MetaCell, and program sponsors and supporting partners One Mind for Research, Morrison & Foerster, Recombinant Data and Weber Shandwick. Through Orion Bionetworks, these alliance members will use cutting-edge technology to greatly expand our body of knowledge of diseases, prevention, and treatments.

"In order to leverage the power of computational modeling to predict health outcomes, you first need access to a large set of data to analyze, which is exactly what this multidisciplinary group will provide for us," said Iya Khalil, Executive Vice President and Co-Founder of GNS Healthcare. "Working from rich databases of over 7,000 people with MS, GNS will be able to integrate clinical, biomarker, and imaging data to develop a causal, computational model of MS that has the promise to yield new insights into the underlying biology, and guide the development of more personalized courses of treatment for patients."

Orion Bionetworks will employ GNS Healthcare's REFS (Reverse Engineering and Forward Simulation) platform to reverse engineer computational models from MS data provided by Brigham and Women's Hospital, Accelerated Cure Project and PatientsLikeMe. Supercomputers and their powerful data-crunching capabilities have the capacity to analyze and understand the huge amounts of patient outcomes data that exist within the healthcare system. GNS's platform will utilize the untapped potential of that data to advance our understanding of the disease by expanding access to valuable biological and clinical data and providing new ways to interact with and apply the data. Results from millions of in silico simulations will provide new insights into the fundamental mechanisms of MS, by finding the underlying causal relationships in the data. This, in turn, will help optimize treatment plans for patients.

"MS is a complicated condition for physicians to treat because it has various disease stages and a wide number of treatments. Currently we cannot predict an individual patient's optimal treatment course, and there is no personalization in the selection of treatments," said Philip De Jager, MD, PhD, a physician researcher at the Institute for Neurosciences at Brigham and Women's Hospital. "By connecting all of the available, but underutilized data with the supercomputing power that is available today, we can gain new disease insights to help personalize existing treatments and develop new ones - ultimately helping patients. MS is uniquely ready for the new tools of predictive modeling, which can answer critical questions beyond the reach of individual research efforts."

Jamie Heywood, Co-Founder and Chairman of PatientsLikeMe, added, "It's an honor to be working with the GNS Healthcare team and the alliance members to share insights and learn across the disciplines. Together, we'll be able to study real patient experiences to advance our understanding of MS, and hopefully accelerate the development of effective treatments and better care."

Additional information on the organization and partnership opportunities is available on the organization's website, www.orionbionetworks.org.