SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--Nodality, Inc., an innovative biotechnology company advancing discovery, development and use of transformative therapies by revealing functional systems biology, announced today results of the Company’s comprehensive research study to identify cell markers (biomarkers) of disease activity and treatment success in rheumatoid arthritis (RA) patients. The study findings demonstrated that Nodality’s SCNP technology, which measures functional pathways at the single cell level, can be used to identify biomarkers of responsiveness to treatment with tumor necrosis factor inhibitors (TNFIs). RA affects an estimated two million Americans, and TNFIs constitute the most commonly prescribed therapy. Approximately half of patients respond to treatments such as TNFIs, leaving a substantial unmet need to identify which patients are more likely to respond to current therapies. Optimizing use of currently available therapies could potentially delay tissue damage and progression of disease.
“I look forward to the final results of this program, one of the most comprehensive of its kind. Our technology, based on immune-biology, can predict which RA patients will respond to specific therapies and reveal the mechanisms of drug resistance, thus informing alternative therapeutic strategies.”
SCNP provides the core technology foundation for Nodality’s programs dedicated to improving clinical medicine by increasing the efficiency of therapeutic R&D programs, enhancing life cycle management for commercialized drugs, and introducing new predictive diagnostics. The study results were featured in an oral presentation titled, Comparison of functional immune signaling profiles in peripheral blood mononuclear cells (PBMC) from rheumatoid arthritis (RA) patients versus healthy donors (HD) using Single Cell Network Profiling (SCNP) (Abstract W7.02.04), at the 15th International Congress of Immunology (ICI) in Milan, Italy, taking place August 22 to 27, 2013. The findings were presented by S. Louis Bridges, Jr., M.D., Ph.D., Marguerite Jones Harbert-Gene V. Ball, MD Professor of Medicine, Director, Division of Clinical Immunology and Rheumatology, University of Alabama School of Medicine.
“Nodality’s research program demonstrates the great promise and potential in gaining a better understanding of disease biology and applying this to the development of prognostic and predictive biomarkers for autoimmune diseases such as RA,” commented Alessandra Cesano, M.D., Ph.D., Chief Medical Officer of Nodality. “I look forward to the final results of this program, one of the most comprehensive of its kind. Our technology, based on immune-biology, can predict which RA patients will respond to specific therapies and reveal the mechanisms of drug resistance, thus informing alternative therapeutic strategies.”
The Nodality research program compares healthy and diseased peripheral blood cells at the single cell level, studying samples obtained through the national Treatment Efficacy and Toxicity in Rheumatoid Arthritis Database and Repository (TETRAD). Nodality anticipates completing its research program and announcing the key findings later this year.
Laura Brege, Nodality’s President and Chief Executive Officer, stated, “ICI has provided an important opportunity to showcase one of our key programs in immunology, further validating our broadly enabling SCNP platform. This platform has led to major collaborations in immunology addressing significant unmet needs among patients, as well as new predictive diagnostic modalities in blood cancers. Ultimately, Nodality’s goal is to accelerate and make more efficient the development of new therapeutic agents for serious diseases affecting large patient populations within immunology and oncology, two areas of continuing significant unmet clinical need.”
Additional program results were featured in a second oral presentation at the ICI Congress in a presentation titled, Functional proteomic interrogation of immune cell crosstalk and the effects of cytokine-targeted inhibitors using Single Cell Network Profiling (SCNP) (Abstract W7.02.03).
Nodality is a next-generation life sciences company that is advancing drug discovery, therapeutic development, and precision medicine by delivering critical and clinically actionable information to reveal biology, define disease, and improve health. Nodality's unique, innovative, and proprietary platform, Single Cell Network Profiling or SCNP, enables the promise of precision medicine by unlocking the potential of therapeutics and by matching therapies with the right patients. SCNP enables functional characterization of disease-associated signaling at the individual patient level, enabling optimization of treatment tailored to target the biology driving the disease. Nodality is applying SCNP to develop molecular diagnostics to improve clinical decision-making in cancer and autoimmune diseases, with the lead products targeting treatment management in hematological malignancies. Nodality is also collaborating with Pharma partners on patient stratification & companion diagnostics development, drug & disease profiling, determination of mechanism of action, mechanism-based competitive differentiation, whole blood PD assays, and biomarker discovery & development. These applications can result in increased probability of success, reduced timeline for clinical development, and differentiation from competitors in the marketplace. Nodality established multi-year pharma strategic collaborations with UCB Pharma S.A. (Euronext Brussels: UCB) and Pfizer (NYSE: PFE) in 2012 utilizing its SCNP technology to assist the development of several compounds focusing initially on immunology disorders.
About Single Cell Network Profiling
Single Cell Network Profiling (SCNP) is a proprietary technology licensed from Stanford University to characterize cell signaling networks in immunology and cancer. SCNP, by measuring functional signaling network behavior at the level of the single cell, has several advantages over other currently used molecular technologies. These include unprecedented insight into the presence and clinical meaning of functional cellular heterogeneity in otherwise molecularly and phenotypically homogeneous tissues, including the identification of rare cell subsets such as drug-resistant and stem cells. As such, the technology has widespread application in preclinical drug development, clinical drug development and diagnostic development.