SYS-CON MEDIA Authors: Zakia Bouachraoui, Carmen Gonzalez, Yeshim Deniz, Pat Romanski, Gary Arora

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CytoReason Cements Proof-of-Concept with Machine-Learning-Facilitated Biomarker Breakthrough in Anti-TNFα Treatment Failure in Inflammatory Bowel Disease. New Data Published in Gut

New data published in the prestigious BMJ journal, Gut, outlines the role of a new technological platform approach that has revealed a new blood-based biomarker that is 94% accurate in pretreatment identification of anti-TNFα non-responders in inflammatory bowel disease (IBD), accounting for approximately 30% of patients, confirming validity of the approach.

The application of this platform led to the identification of the TREM1-CCR2-CCL7 axis (which manages the movement of inflammatory monocytes) and plasma cell abundance as accurate pretreatment markers of anti-TNFα response in inflammatory bowel disease (IBD). The study demonstrated TREM-1 expression in peripheral blood to be an accessible and accurate predictor of non-response. The findings demonstrate the platform’s ability to reconstruct previously lost cellular information and isolate an easier to access blood-based biomarker.

The data showcases CytoReason’s ability to provide unique immune-system insights and interpretation that generate new directions for enhanced target identification, improved indication assessment, more effective clinical development and advanced real-world evidence strategies that can be embedded in the development process.

Identifying blood-based biomarkers for IBD has traditionally been extremely difficult to do. The site of disease is the gut, which is a complex tissue, composed of multiple cell types, whose relation to blood in unclear.

“The overall results were impressive in their clarity and output” said Professor Shai Shen-Orr, PhD., Chief Scientist at CytoReason and Director of the Systems Immunology & Precision Medicine Lab in the Faculty of Medicine at The Technion, Israel Institute of Technology. “We demonstrated our ability to recreate and separate out cellular contributions from bulk tissue measurements, discovering a pretreatment upregulated pathway uniquely in anti-TNFα non-responders. Furthermore, we established a clear biomarker relationship between biopsy and blood, which we were able to validate with high accuracy.”

"With more than a decade of research behind our unique platform, I am delighted to further demonstrate our ability to uncover critical immunological insights, vital to R&D teams in the discovery, validation and development of targets and the mitigation of clinical development risks", remarked David Harel, President and Chairman of CytoReason. “This is exciting news for drug developers, who can use our unique approach to exquisitely define research directions. Ultimately, this is great news for the millions of patients who rely on the discovery, development and availability of innovative and effective new therapeutic options.”

About CytoReason
Based on more than 10 years of research, CytoReason’s technology uses a proprietary data and machine learning model to reconstruct cellular information from bulk tissue, to train an immune-specific NLP engine, and to integrate multi-omics data. The company’s platform organizes and standardizes collaborators’ data (gene, protein, cell, and microbiome) and integrates it into CytoReason’s proprietary disease model to generate mechanistic understanding of the immune system, leading to novel insights.

CytoReason’s technology has yielded 2 pending patents, 9 commercial and scientific collaborations and 14 peer reviewed publications. Fully applicable to cancer immunotherapy, autoimmune, neurodegenerative and infectious disease research, CytoReason is at the cutting edge of society’s boldest attempts to improve health outcomes through better understanding of the immune system.

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