Immunai, a startup that develops a proprietary body of immune-centered human tissue analysis, has emerged from the hidden today at $ 20 million. The company will use the capital to drive the development of its technical and business functions and to hire new scientists, engineers and machine learning experts, a spokesman told VentureBeat.
New treatments such as gene cell therapies and cancer immunotherapies promise to revolutionize the field of medicine. However, the complexity of the immune system – trillions of cells divided into hundreds of types and states that interact with different systems and proteins – threatens to hamper research. In 1
Immunai was founded in December 2018 by CEO Noam Solomon, a former Harvard and MIT postdoctoral fellow, and CTO Luis Voloch, a MIT graduate and former machine learning engineer at Palantir. The two have teamed up with members of the Parker Institute, which is working with researchers to accelerate the development of immunotherapies – Danny Wells, a founding data scientist, and Ansuman Satpathy, a professor of cancer immunology – to pursue a platform that lights up Cell populations raises follow-up and pre-treatments.
Immunai’s technology derives over a terabyte of data from a single blood sample and profiles cells at a depth and size that the company claims is “unprecedented”. The samples are compared to a database using AI that maps data to hundreds of cell types and conditions and creates immune profiles based on highlighting various elements and properties.
This approach is similar to that of Human Vaccines Project scientists working to identify biomarkers (i.e. indicators of certain disease states) that predict immune responses to vaccines and cell therapies. Elsewhere, Microsoft and the startup Adaptive Biotechnologies are collaborating to develop algorithms that create a “translational map” for cell receptors on antigens – pathogen molecules that trigger an immune response – and then map these antigens back to diseases.
Clinical trials have traditionally focused on testing thousands or even tens of thousands of subjects and collecting a limited amount of data each, but massive corpora and AI enable millions of data points to be collected about a single person. Solomon’s belief is that this will better uncover the mechanisms underlying disease. “If you only look at a specific disease or patient cohort, you get a restricted and isolated view of the immune system,” he said. “By using machine learning and applying it to our proprietary, diverse database of single sequencing data paired with extensive clinical data, our platform identifies common patterns that are not visible when looking at the narrower disease-specific view.”
The profiles could support the discovery of new biomarkers by recognizing changes in cell type and in state-specific expression. In a peer-reviewed study of the inhibition of a protein called Programmed Cell Death Protein 1 (PD-1 and CD279), which is located on the surface of cells and plays a role in regulating the response of the immune system, the immune Team revealed information about the origin of tumor-fighting T cells.
“Our mission is to map the immune system with neural networks and to transfer learning techniques that are based on sound immunological knowledge,” said Voloch. “We developed the tools and expertise to help every immuno-oncology and cell therapy researcher improve their work, increase the speed at which drugs are developed and marketed, while ensuring that the effects are understood. “
Immunai is headquartered in New York City and has offices in San Francisco and Tel Aviv. In addition to Satpathy and Wells, Dan Littman, professor of molecular immunology at New York University, is the third founding scientist.
Viola Group and TLV Partners led the start-up round.