Dec 12, 2017

GNS Healthcare Uses Causal AI to Discover Which Multiple Myeloma Patients Will Have Progression Free Survival Benefit from Stem Cell Treatments

Details of the Discovery Leveraging the Multiple Myeloma Research Foundation CoMMpass Study Presented at 59th Annual ASH Meeting

CAMBRIDGE, Mass.– December 12, 2017 – GNS Healthcare (GNS), a leading precision medicine company, together with the Multiple Myeloma Research Foundation (MMRF), have discovered a biomarker that identifies which multiple myeloma patients will benefit from stem cell transplantation. This discovery supports more effective treatment of patients, precisely answering a deeply important, personal, and recurring question in multiple myeloma care. The presentation, titled “Multiple Myeloma Drivers of High Risk and Response to Stem Cell Transplantation Identified by Causal Machine Learning: Out-of-Cohort and Experimental Validation”, was given over the weekend at the 59th American Society of Hematology Annual Meeting (ASH) held in Atlanta, Georgia.

REFSTM, the GNS causal learning and simulation platform, reverse engineered models of 645 multiple myeloma patients, connecting treatments to patient characteristics and outcomes. Without prior knowledge, the REFS platform identified a biomarker, CHEK1, that acts as a causal driver behind a patient’s response to stem cell treatment. Patients with low levels of this gene receive a 22-month Progression Free Survival (PFS) benefit from stem cell transplantation; patients with high levels do not receive a significant benefit. The discovery of the link between a multiple myeloma patient’s genetic profile and treatment response ahead of undergoing a costly, invasive treatment such as stem cell transplantation will bring precision to a difficult medical decision in a high-risk disease.

“The ability to better match multiple myeloma patients with stem cell therapy is a crucial finding in the fight against this terrible cancer,” said Colin Hill, Chairman, CEO, and co-founder of GNS Healthcare. “Our platform, using the MMRF’s patient data, reverse engineered models of the patient mechanisms and simulated stem cell treatment patient by patient. Our discovery revealed who will and who will not respond to stem cell transplantation.”

The ASH presentation and study are part of an ongoing initiative of the MMRF and GNS to identify new multiple myeloma therapies and develop personalized care pathways. Despite a recent increase in the number of therapeutic options for the treatment of multiple myeloma, the cancer is still viewed as incurable. The data used in the model comes from the CoMMpass StudyTM, a longitudinal study of newly diagnosed patients with active multiple myeloma, to map each of the patient’s genomic profiles to clinical outcomes to develop a more complete understanding of patient responses to treatments.

“We believe this work can answer the questions that are most important to multiple myeloma patients and their families and will drive towards more precision-based approaches for all patients,” said Paul Giusti, President and CEO of the Multiple Myeloma Research Foundation.


About REFS
REFS™ (Reverse Engineering & Forward Simulation) is GNS Healthcare’s patented causal learning and simulation platform. Unlike traditional artificial intelligence platforms, REFS analyzes data sets beyond correlation, instead inferring causal mechanisms between variables to answer questions such as: How will the patient respond to this treatment? What if we choose one intervention over another? REFS is the only commercially available platform that infers causal mechanisms from patient data at scale from traditional healthcare and emerging data sources to bring the promise of precision medicine within reach.

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.

Media Contact:
Patty Kellicker
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