Nodality, Inc. Expands Senior Team, Appoints Guy Cavet, Ph.D., as Chief Information Officer, Head of Computational Sciences
SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)-- Nodality, Inc., announced today the appointment of Dr. Guy Cavet as Chief Information Officer and Head of Computational Sciences, effective immediately. In this newly created position, Dr. Cavet will report to Laura Brege, President and Chief Executive Officer. Nodality is a privately held biotechnology company focused on improving the development and clinical use of therapeutics in autoimmune disease and cancer through the application of its proprietary Single Cell Network Profiling (SCNP) technology platform.
“We are very enthusiastic about the key addition of Guy Cavet to our senior team. Guy’s previous responsibilities at Crescendo, Rosetta, and Genentech position him well to lead our bioinformatics team and play a pivotal role in the creation of new product offerings at Nodality,” commented Ms. Brege. “It is an exciting time for us as we expand the use of our technology platform among business partners and advance toward the commercialization of our first companion diagnostic products with oncology applications.”
“I am thrilled to be joining the Nodality team,” said Dr. Cavet. “The company’s unique ability to profile pathway activities and responses at the single cell level opens up huge opportunities for gaining insight into biology and enabling better medicine.”
Prior to joining Nodality, Dr. Cavet served as Vice President, Life Sciences at Kaggle, Inc., and prior to that, as Vice President, Informatics at Crescendo Bioscience, where he built the company’s informatics organization. Earlier in his career, Dr. Cavet was Senior Scientist, Bioinformatics at Genentech, and Group Leader, Computational Genomics at Rosetta Inpharmatics and Merck & Co. Dr. Cavet earned his undergraduate and Ph.D. degrees in Biochemistry from Cambridge University.
Nodality is a next-generation biotechnology 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.
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