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Oncorus, Inc. is a lean early-stage biotechnology company developing a next-generation immunotherapy platform to treat cancer. Oncorus was founded by well-known biotechnology entrepreneurs and is backed by MPM Capital. Oncorus is a leader in corporate philanthropy, and has taken a pledge to donate a portion of product sales to fund promising cancer research and to support cancer care in the developing world. We are located in Kendall Square, Cambridge, MA.
ChemCross.com is a Houston, TX-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
University Technologies International is a Calgary, AB-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Delinia has assembled a leadership team, Board of Directors and Scientific Advisory Board comprised of experienced investors, world-class academicians and industry veterans with proven track records for building exceptional life sciences companies.
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.