GNS Healthcare to combine its powerful, causal machine learning technology with the comprehensive Answer ALS patient datasets

WASHINGTON and CAMBRIDGE, Mass., July 31, 2018 /PRNewswire/ -- The ALS Association is providing new funding to allow GNS Healthcare to use artificial intelligence (AI) to create a comprehensive disease model to advance research into ALS. GNS Healthcare will use its powerful machine learning platform, REFS, in conjunction with the rich Answer ALS patient datasets, which are accessible to clinicians and scientists throughout the ALS research community. The project will be led by Dr. Iya Khalil, chief commercial officer and co-founder of GNS Healthcare.

ALS, also known as Lou Gehrig's Disease, is a progressive neurodegenerative disease that affects nerve cells in the brain and spinal cord. Eventually, people with ALS lose the ability to initiate and control muscle movement, which often leads to total paralysis and death within five years of diagnosis. For unknown reasons, veterans are twice as likely to develop ALS as the general population. There is no cure.

Answer ALS is collecting data from 1,000 people with ALS to build a comprehensive picture of the disease that includes clinical, genetic, molecular, and biochemical information that is openly shared with the global ALS research community. Together, this information will yield thousands of petabytes of new ALS-specific information that requires analysis.

The ALS Association's partnership with GNS Healthcare will transform these petabytes of patient data into mechanistic models, connecting genetic, molecular, and biochemical variables to clinical outcomes that will allow in silicoexperiments to be performed at a rapid rate on the computer.

These rapid, high-throughput computational experiments will explore the numerous factors in the REFS Answer ALS data models that drive disease progression and drug response. Discoveries will then be evaluated and validated with wet lab experiments and, eventually, clinical studies.

Building the powerful, causal machine learning model of ALS disease and developing an easy-to-use, cloud-based, interface will be carried out in two phases. During the first phase, GNS Healthcare will work with Answer ALS to receive and integrate patient clinical data with corresponding motor neuron data to build and strengthen the model structure.

Researchers will then be given an easy-to-use, cloud-based interface to explore the models, simulate potential interventions, better understand the mechanisms of the disease, and conduct virtual computational experiments in concert with their experimental and clinical research.

In the second phase, the model and user interface will be refreshed with patient clinical data until the Answer ALS total cohort of 1,000 patient enrollments is complete.

"The ALS Association has made significant investment in precision medicine for ALS by funding the generation of large comprehensive data collections through strategic initiatives such as Answer ALS, which includes analyses of genetic, proteomic, metabolomic, environmental exposure data, and clinical information from people living with ALS. Using the appropriate tools to mine these data sets is critical to understanding the variability of ALS and how to better design clinical trials. The GNS Healthcare project will begin to address this," commented Dr. Lucie Bruijn, chief scientist for The ALS Association.

The GNS Healthcare model and interface will be accessible to clinicians and scientists within the ALS research community, supporting The ALS Association's value of collaboration to make all ALS research data available to the entire research community. In addition, the model will be continuously refreshed to ensure the data collected is the most up-to-date to allow for streamlined data mining.

The powerful partnership between The ALS Association, GNS Healthcare, and Answer ALS has the potential to reveal invaluable insights into ALS disease. For example, data mining of the datasets will provide critical information about ALS subpopulations, molecular pathways and disease drivers, and patient disease progression trajectories, as well as a better understanding of patient treatment outcomes.

"We are excited to work with The ALS Association on such a critical initiative. The richness of their patient data, coupled with our machine learning technology, will provide the research community with the computer models and newly discovered disease mechanisms needed to unravel the complexities of this devastating disease and, eventually, develop better treatments," said Dr. Iya Khalil, co-founder and chief commercial officer of GNS Healthcare.

Through this initiative, The ALS Association continues its support and collaboration with Answer ALS to accelerate ALS translational discovery to improve the care of people with ALS.

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.