In a project led by Dr Iya Khalil, its chief commercial officer and co-founder, GNS Healthcare will use its machine learning platform, REFS, in conjunction with the Answer ALS datasets, which are accessible to clinicians and scientists throughout the ALS research community, according to a media release from The ALS Association.
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 silico experiments 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, the release explains.
The project will be completed 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 release continues.
“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,” comments Dr Lucie Bruijn, chief scientist for The ALS Association.
“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,” Khalil states.
[Source(s): The ALS Association, PR Newswire]