BLACKSBURG, VA January 15, 2017 — “Solving Immunology?” is the culmination of the “Complex Systems Science, Modeling and Immunity” workshop convened by the National Institute of Allergy and Infectious Diseases (NIAID).
The white paper, a collaboration by 14 prominent immunologists and computational biologists, aims to define the need for systems immunology approaches, mechanistic modeling and data-driven modeling and the value these approaches can add when used in combination with traditional experimentation. This white paper serves as “a roadmap for bridging the immunologist-modeler divide in order to accelerate insight into newly discovered mechanisms of immune system function and the translation of data into individualized treatment for infectious and immune-mediated diseases.”
The balance between health and disease is exquisitely controlled by complex massively and dynamically interacting gene networks, immune signaling pathways, dietary choices, the microbiome with its trillions of gut bacteria, our body’s metabolism, the immune system and nutrition-microbiota-host interplay. When interactions among genes, the environment and the immune system become out of sync, disease follows. Dysregulation of immune and inflammatory pathways is at the core of many diseases facing mankind in the twenty first century. These diseases are multi-factorial, exhibit great patient-to-patient variability, and often are intractable to both traditional “one-size-fits-all” therapy and reductionist insight.
A fundamental challenge for therapeutic development in the post-genomic era is to ascertain what is the optimal way to leverage focused, hypothesis-driven and hypothesis-generating research to understand how immune system behavior in health and disease emerges from molecular, genetic, epigenetic, cellular and environmental modulatory elements.
“Even relatively simple mathematical models can improve insight from existing data. Better integration of mechanistic modeling approaches into immunology research can optimize the choice of what and when to measure, and sharpen the hypothesis generation process,” said Josep Bassaganya-Riera, President and CEO of Landos Biopharma, Inc. (LANDOS), and one of the leading authors of the paper. “We have successfully combined the power of computational modeling with immunology experimentation to characterize new immunoregulatory targets such as PPARs, LANCL2 and NLRX1 in infectious and immune-mediated diseases. Pharmaceutical companies spend billions of dollars every year in validating new therapeutic targets. We envision a role for modeling and informatics as the first step toward identifying and validating new targets for safer and more effective drugs and biologics. LANDOS is committed to leverage the power of high-performance computing, advanced informatics and data science to accelerating the development of therapies for autoimmune diseases.”
This work is a starting point to show traditional immunologists and modelers that collaborative efforts can greatly accelerate the generation of new knowledge about the immune system as well as facilitate discoveries that may not be possible independently.
About Landos Biopharma, Inc.
Landos Biopharma, Inc. is a clinical-stage biopharmaceutical company focused on the discovery and development of first-in-class oral therapeutics for patients with autoimmune diseases. Landos’ lead clinical asset, BT-11, is a novel, oral, locally-acting small molecule targeting the Lanthionine Synthetase C-Like 2 (LANCL2) pathway in the gastrointestinal tract
for treatment of inflammatory bowel disease (IBD) and is in Phase 1 clinical testing for Crohn’s disease and ulcerative colitis. Landos also has a robust pipeline of compounds for other autoimmune diseases. For more information, please visit www.landosbiopharma.com or contact email@example.com or follow us @Landosbio.
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