HemoShear Therapeutics Physiological Human Tumor Model Pu...
HemoShear Therapeutics Physiological Human Tumor Model Published in Lab on a Chip Journal
CHARLOTTESVILLE, Va., March 6, 2019 /PRNewswire/ -- HemoShear Therapeutics today announced that the Royal Society of Chemistry's Lab on a Chip Journal published data (https://pubs.rsc.org/en/content/articlelanding/2019/LC/C8LC00755A#!divAbstract) on its multi-cellular three-dimensional model of the tumor microenvironment for pancreatic cancer. This paper, co-authored by Daniel Gioeli, PhD, Associate Professor of Microbiology, Immunology, and Cancer Biology at the University of Virginia, demonstrates how this unique model of the tumor microenvironment for pancreatic cancer has the potential to accelerate the discovery and development of drugs for a range of solid cancerous tumors.
"Cancer drug R&D suffers the lowest success rates of all major disease areas because we lack predictive models that reflect the complexity of human tumors," said Dr. Gioeli. "This novel model recapitulates aspects of a human tumor not present in other models, and thus, has the potential to replicate the complex nature and behavior of a tumor. This will enable us to better understand the disease and accurately assess potential treatments."
Working with HemoShear's proprietary REVEAL-Tx™ human biology platform, Dr. Gioeli led the development of the tumor model, which uniquely incorporates multiple human tumor cell types, including endothelial cells, stromal fibroblasts and patient-derived tumor cells that are exposed to mechanical shear forces derived from tumor blood flow to restore the tumor's physiological environment. Of major significance, Dr. Gioeli and HemoShear demonstrated that treatment with therapeutically relevant doses of chemotherapeutics in the pancreatic tumor model yields responses paralleling the patients' clinical responses, which is rarely the case in traditional cell culture and mouse cancer models.
"Cancers are relentlessly dynamic, and our tumor models will allow us to understand the inner workings of tumors, enabling us to systematically assess new ways to disrupt tumor growth," says Brian Wamhoff, PhD, HemoShear co-founder and Head of Innovation. "We look forward to forging partnerships with companies who want to apply our platform to accelerate successful cancer drug discovery and ultimately develop more effective treatments for patients."
Early development and validation of HemoShear's pancreatic and non-small cell lung cancer models was advanced through work funded by a National Cancer Institute SBIR contract and the Virginia Biosciences Health Research Corporation. Dr. Gioeli and HemoShear are now incorporating immune cells in the model for immuno-oncology applications.
About HemoShear Therapeutics
HemoShear Therapeutics discovers novel biological targets and advances drug programs to treat metabolic disorders with significant unmet patient need. HemoShear's drug discovery platform, REVEAL-Tx™, enables the Company's scientists to create best-in-class, biologically relevant human disease models to uncover and explain the underlying mechanisms of disease, translate those discoveries into drug candidates, and predict which candidates will treat patients successfully. HemoShear's proprietary drug discovery programs are focused on rare genetic metabolic disorders. In addition, the Company has exclusive partnerships to discover novel therapeutic approaches in nonalcoholic steatohepatitis (NASH) with Takeda and in gout with Horizon Pharma. For more information visit www.HemoShear.com.
About HemoShear's REVEAL-Tx™ Platform
Existing human experimental disease models do not reliably represent human biology. HemoShear has developed a transformational platform, REVEAL-Tx™, which applies principles of physiological blood flow to tissue from patients to recapitulate disease. REVEAL-Tx™ provides unprecedented insights into complex pathophysiological pathways by replicating human disease with great accuracy. HemoShear's human disease models, in combination with its advanced proprietary computational biology tools, identify novel treatment approaches and reduce risk of failure by enabling scientists to deeply interrogate disease pathways, test hypotheses and select meaningful targets in physiologically accurate disease conditions.
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