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Immunai Launches to Fully Map the Entire Immune System to Better Develop Immunotherapies and Cell Therapies

Ex-Palantir engineers and MIT, Harvard & Stanford researchers raise $20M in seed funding to better detect, diagnose and treat disease by mapping out immune cells and their functions with machine learning

New York, New York – WEBWIRE

Today, Immunai launches out of stealth to map the entire immune system for better detection, diagnosis, and treatment of disease. Leveraging single-cell technologies and machine learning algorithms, Immunai has mapped out millions of immune cells and their functions, building the largest proprietary data set in the world for clinical immunological data. The company is also announcing $20M in seed funding, which will be used to further the development of its technology and business functions while expanding its team of scientists, engineers, and machine learning experts.

Cell therapies and cancer immunotherapies have revolutionized medicine in the last few years and are expected to continue for the near future. However, due to the incredible complexity of the immune system -- its trillions of cells partitioned into hundreds of cell types and states and how they interplay with other cells and proteins -- it is prohibitively hard to predict how drugs will affect immune cells. For cell therapies with high manufacturing costs, a slight variation in cell therapy products can have a significant influence on a patient’s response to the therapy. 

Immunai has developed a vertically-integrated platform for multi-omic single-cell profiling that offers a broader view of the immune system in states of health, disease, and treatment to examine the body’s response to stimulus. With Immunai’s platform, pharmaceutical companies can identify more subtle nuances in cell abundances and cell function and mechanisms of action and biomarkers for toxicity response to accurately measure the efficacy of immunotherapies. For cell therapies, in particular, Immunai partners with cell therapy companies to understand cellular products’ sub-populations in unprecedented detail before and after infusion. 

”When looking at only a specific disease or patient cohort, one gets a limited and siloed view of the immune system,” remarked Noam Solomon, CEO of Immunai. “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.” 

How it works:

  • Immunai leverages single-cell technologies to profile cells at unprecedented scale and depth - deriving over a terabyte of data from a single blood sample.
  • Its proprietary database and machine learning algorithms map incoming data to hundreds of cell types and states to create immune profiles based on highlighting differentiated elements.
  • The database of immune profiles support biomarker discovery and insight generation to help answer important questions about the immune system by identifying subtle changes in cell type and state-specific expression and helping distinguish that from normal expression.

“Our mission is to map the immune system with neural networks and transfer learning techniques informed by deep immunology knowledge,” said Voloch. “We developed the tools and knowhow to help every immuno-oncology and cell therapy researcher excel at their job. This helps increase the speed in which drugs are developed and brought to market by elucidating their mechanisms of action and resistance.” 

The company was founded in December 2018 by ex-Harvard-MIT postdoc Researcher, CEO Noam Solomon and ex-MIT and Palantir ML Engineer, CTO Luis Voloch. Immunai’s mission was crystalized shortly after when founding scientists Ansuman Satpathy, currently a professor of cancer immunology at Stanford University, and Danny Wells, founding data scientist and current member of the Parker Institute for Cancer Immunotherapy, joined the team. 

The team has further built out its expertise in machine learning and oncology by recruiting established leaders to help guide the company’s vision. In addition to Satpathy and Wells, Dan Littman, a professor of molecular immunology at New York University, joined as Immunai’s final founding scientist. The company’s Scientific Advisory Board includes Rahul Satija, Matt Hellmann, Regina Barzilay, Eran Segal and Anshul Kundaje. 

The team has already published peer-reviewed work on the origin of tumor-fighting T cells following PD-1 blockade, demonstrating the important findings its immune intelligence can uncover, and has additional publications under review. 

Immunai has raised $20M in seed funding led by Viola Ventures and TLV Partners, and have established clinical partnerships with over 10 medical centers, as well as multiple commercial partnerships with cell therapy and checkpoint blockade with biopharma companies.

For more information about partnering with Immunai, please visit

About Immunai

Immunai is on a mission to fully map the immune system to better detect, diagnose, and treat disease by advancing personalized medicine through a comprehensive understanding of the immune system. The team is composed of genomics, machine learning, bioinformatics, immunology, and software engineering experts, is headquartered in New York City, and has offices in San Francisco and Tel Aviv. The company has raised $20M in seed funding led by Viola Ventures and TLV Partners. 


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