Immunai decloaks with $20M in seed funding to map immune system with machine learning – MedCity News

Immunai decloaks with $20M in seed funding to map immune system with machine learning – MedCity News

AI, machine learning

A company developing means to use machine learning to map the immune system and thus aid the development of cell therapies and cancer immunotherapies is emerging from stealth mode with a hefty round of seed funding.

New York-based Immunai said Thursday that it was launching out of stealth, with a $20 million round of seed funding led by Viola Group and TLV Partners. The company, founded by a former Harvard University postdoctoral researcher, CEO Noam Solomon, and chief technology officer Louis Voloch, who was previously a machine learning engineer at Palantir, aims to better detect, diagnose and treat disease by using machine learning to map out immune cells and better detect, diagnose and treat disease.

“When looking at only a specific disease or patient cohort, one gets a limited and siloed view of the immune system,” Solomon said in a statement. “By using machine learning and applying it to our proprietary diverse database of single-sequencing data paired with rich clinical data, our platform identifies common patterns that are not visible when looking at the narrower disease-specific view.”

The company said its software would enable drugmakers to identify subtle nuances in cells, mechanisms of action and biomarkers for toxicity response in order to accurately measure the efficacy of immunotherapies, as well as to better understand subgroups of patients receiving cell therapies. It said it can derive more than a terabyte of data from a single blood sample, while its database and algorithms map it to hundreds of cell types and states to create immune profiles. Identifying subtle changes in cell type and expression can help support discovery of biomarkers.

Immunai is part of a growing field of academic research – and startups that grow from it – using artificial intelligence and machine learning to aid drug discovery and development. Such efforts have also been employed in the race to find treatments for Covid-19. In March, scientists at Oak Ridge National Laboratory and IBM used a supercomputer to screen more than 8,000 drug compounds in a matter of days, identifying 77 with potential activity against the disease and the virus that causes it, SARS-CoV-2.

Photo: Andrzej Wojcicki, Getty Images

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