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Sengenics is a functional proteomics company that leverages its patented KREX technology to discover autoantibody biomarker signatures for prediction of drug response and severe immune-related adverse events (irAEs). KREX™ was invented and patented by Professor Jonathan Blackburn whilst he was a member of the faculty at the University of Cambridge. Jonathan is the CSO of Sengenics. The key application of KREX™ is the discovery of autoantibody biomarker signatures for prediction of drug response and severe immune-related adverse events (irAEs). KREX™ can also be used to identify autoantibody biomarkers that may be used to diagnose cancer, autoimmune or neurodegenerative conditions years before conventional diagnostic tests. Some autoantibodies that are identified as diagnostic biomarkers may be protective and have potential in themselves as therapeutic biomolecules.
MOBILion Systems is enabling advancements in disease diagnosis and treatment by commercializing instruments that improve multi-omics disease, drug, and biomarker discovery.
Acasti Pharma Inc. is an emerging biopharmaceutical company dedicated to the research, development and commercialization of innovative proprietary active pharmaceutical ingredients (API) for the management of cardiometabolic disorders, from prevention to treatment, through a novel superior approach to lipid regulation. To carry out this mission, Acasti is advancing its portfolio of bioactive ingredients, by purifying and concentrating krill-oil extracts through innovative technology, to produce products targeting the prescription drug and medical food markets.
Pulmatrix Inc is a Lexington, MA-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
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.