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Vir brings together cutting-edge innovations with leading scientific expertise and management to take on some of the world`s most challenging infectious diseases for which solutions are non-existent or inadequate. Vir seeks to take a new approach, using breakthroughs in immune programming to manipulate pathogen-host interactions. The company will take a multi-program, multi-platform approach to applying these breakthroughs, guided by rigorous science and driven by medical need.
QUATRx Pharmaceuticals Company is a Ann Arbor, MI-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Eos Biotechnology , Inc. is a South San Francisco, CA-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
E-Scape Bio is a preclinical stage biopharmaceutical company focused on the discovery and development of therapies to treat genetically defined, neurodegenerative diseases.
insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients. At insitro, we are rethinking the entire drug discovery process, from the perspective of machine learning, human genetics, and high-throughput, quantitative biology. Over the past five decades, we have seen the development of new medicines becoming increasingly more difficult and expensive, leaving many patients with significant unmet need. We`re embarking on a new approach to drug development – one that leverages machine learning and unique in vitro strategies for modeling disease state and designing new therapeutic interventions. We aim to eliminate key bottlenecks in traditional drug discovery, so we can help more people sooner and at a much lower cost to the patient and the healthcare industry. We believe that by harnessing the power of technology to interrogate and measure human biology, we can have a major impact on many diseases. We invest heavily in cutting edge bioengineering technologies to enable the construction of large-scale, high-quality data sets that are designed specifically to drive machine learning methods. Our first application is to use human genetics, functional genomics, and machine learning to build a new generation of in vitro human cell-derived disease models whose response to perturbation is designed to be predictive of human clinical outcomes.