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Cleveland Clinic`s rich history includes continuous emphasis on research and innovation. In 1921, the founders stated their commitment not only to treating disease and educating the next generations of healers, but also to researching the causes of disease. They realized that understanding the biological basis of disease is necessary to developing new diagnostics and therapeutics.
Spine Team Texas is a Southlake, TX-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Ludesi is a Cambridge, MA-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Brii Biosciences (Brii Bio) is a company committed to serving patients` needs and improving public health in China. Founded in early 2018, the company focuses on accelerating innovation and optimizing access to the latest medicines for Chinese patients. Brii Bio helps global partners drive growth and improve return on investment through better understanding of Chinese healthcare systems and access to the world`s second largest pharmaceutical market. The company`s focus is treatments for chronic illnesses with significant burdens, including infectious diseases, liver and lung diseases, and other illnesses. The company is headquartered in the People`s Republic of China and the United States, with offices in Shanghai, Beijing, San Francisco, and Durham, North Carolina.
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.