Immunai unveils map of human immune system

By Jenni Spinner contact

- Last updated on GMT

(Image: Getty/wildpixel)
(Image: Getty/wildpixel)

Related tags: Drug development, machine learning, Research

A research team including MIT, Harvard and Stanford researchers has raised $20m in seed funding for their effort to map out immune cells with machine learning.

Immunai has announced it has mapped out the entire human immune system, in order to more effectively and efficiently develop immunotherapies and cell therapies. The technology, which uses single-cell technologies and machine learning algorithms, has led to what the company describes as the world’s largest proprietary data set for clinical immunological data.

Additionally, Immunai announced it has landed $20m (£16.5m) in seed money. The Funding will be used to advance the technology and company’s business functions, and to expand the firm’s staff of scientists, engineers and machine-learning specialist.

According to the company, the complexity of the human immune system makes it extremely difficult to predict how drugs may affect human cells. This vertically integrated platform for multiomic, single-cell profiling reportedly provides a broader view immune system across various states of health, disease, and treatment to examine the body’s response to stimulus.

Noam Solomon, Immunai CEO, said using machine learning technology enables researchers to gain a more comprehensive, useful view of human immunity.

When looking at only a specific disease or patient cohort, one gets a limited and siloed 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 rich clinical data, our platform identifies common patterns that are not visible when looking at the narrower disease-specific view​.”

The Immunai platform leverages single-cell technologies to profile cells at significant scale and depth; the company reports it derives more than 1TB of data from a single blood sample. Next, the database and algorithms map incoming data to hundreds of cell types and states to create immune profiles based on highlighting differentiated elements.

The immune profiles in the database reportedly support biomarker discovery and insight generation to help answer questions about the immune system. It is designed to pinpoint subtle changes in cell type and state-specific expression, and help researchers distinguish that from normal expression.

Immunai chief technical officer Luis Voloch (formerly an engineer with data analytics firm Palantir) said the company’s mission is to successfully map the immune system using neural networks, and to “transfer learning techniques informed by deep immunology knowledge​.”

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​,” Voloch added.

 Solomon and Voloch founded the company in December 2018. Shortly after, the team was joined by Stanford immunology professor Ansuman Satpathy and Parker Institute for Cancer Immunotherapy member Danny Wells.

To date, Immunai reports it has published peer-reviewed work and has other publications under review. It also has formed clinical partnerships with more than 10 medical centers, and commercial partnerships with biopharma companies.

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