Immunai launches with $20M to map the human immune system

Steven Loeb · May 15, 2020 · Short URL:

The company has already mapped out millions of immune cells and their functions

It hasn't been all that long since we unlocked the human genome, but the effect on healthcare has already been massive. It's even led to a whole new category, personalized medicine, that could very well totally overhaul healthcare we as know it by creating therapies specifically targeted to that specific person.

What if we could do the same thing for our immune system? That's the idea behind Immunai, a company that launched out of stealth on Thursday with $20 million in seed funding led by Viola Ventures and TLV Partners.

The company, founded in December 2018 by ex-Harvard-MIT postdoc researcher Noam Solomon and ex-MIT and Palantir ML engineer Luis Voloch, uses artificial intelligence and machine learning algorithms to better understand the immune system so it can detect, diagnose, and treat disease.

"When I met Luis, I was a math postdoc at MIT and Luis was working to apply machine learning to biology. Together, we wanted to transfer learning methods with AI and define a comprehensive immunological knowledge base. We realized that almost 50 percent of melanoma patients were treated well with immunotherapy, but researchers could not transcend it to lesser-known cancer indications because there’s no real database for cancer or immunity," Solomon told VatorNews.

"The main issue here is that all types of diseases, not just cancer, come back to the immune system and how it functions. And, without a comprehensive understanding of the immune system, we won’t have highly targeted and effective drugs that actually improve our health."

What does is Immunai can extract over a terabyte of data from a single blood sample. Its database and machine learning algorithms can then be used to map incoming data to hundreds of cell types and states in order to create immune profiles by highlighting differentiated elements. Its database of immune profiles can be used for biomarker discovery and insight generation, identifying subtle changes in cell type and state-specific expression that can be used to distinguish them from normal expression.

The company has already mapped out millions of immune cells and their functions, building what it says is the largest proprietary data set in the world for clinical immunological data. It can analyze the evolution of disease, including cancer to autoimmune disorders to cardiovascular diseases.

"We combine single-cell biology with AI to provide pharma companies, hospitals, and clinics with a comprehensive understanding of the immune system to better detect, diagnose, and treat disease," said Solomon.

"We have an end-to-end vertically integrated platform on both the lab and computational side that allows us to analyze tens of thousands of genes to build the largest database for immunology to-date."

Right now, no other companies are doing exactly what Immunai is doing, he told me, though companies have been trying to understand the immune system for years. They, however, "have only been looking at two cells, PCR and TCR, and couldn’t solve the prohibitive batch problem," while Immunai "can take the complexity of the immune system, simplify it and derive insights from it.

"We’re disrupting legacy companies by analyzing 10,000x more data for each cell than they are," Solomon told me. 

Immunai has already signed seven-figure deals with Fortune 100 pharmaceutical companies, and is helping them accelerate their clinical trials for drugs in the immunotherapy and cell therapy space. It has clinical partnerships with over 10 medical centers, as well as multiple commercial partnerships with cell therapy and checkpoint blockade with biopharma companies. It also has long-term partnerships with research institutions including Upenn, UCSF, Baylor, and others.

The new funding will be used, in part, to expand its team of scientists, engineers, and machine learning experts, which currently consists of 30 employees across New York City, Tel Aviv and San Francisco. It will also be used to build out the company's business functions and further develop its technology.

"The goal is to continue growing our database so that we can apply our learning from one disease to another," Solomon explained.

The company's ultimate mission, he told me, is to "make the biggest impact on healthcare with machine learning by giving researchers and clinicians a better understanding of the immune system."

"We believe this is an incredibly interesting and difficult problem to solve. We’ve spent the last year perfecting our technology and building a team of experts across immunology and computer science, so we’re excited to have this opportunity to grow and make an impact on the next generation of drugs that are being developed.fc"

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