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Startup Aims To Create An AI Map Of The Immune System

The New York based startup Immunai is launching with $20 million in seed money, as it builds its team and platform the MedTech hopes that it can enable new methods of diagnosing and treating disease to improve patient outcomes.u00a0 u201cAll human diseases involve the immune system. We are on a mission to decode the immune system to improve health.u201du00a0

The company was founded and formed by researchers and computer engineers from MIT, Harvard and Stanford University, and the company has set the goal of comprehensively digitally mapping out the entire immune system, starting with each cell type’s function and potential interactions with the body and disease making use of artificial intelligence and deep machine learning. 

Immunai has used their single cell analysis technique to examine millions of immune cells and has formed a large clinical immunological data set which is aimed at furthering cell therapies and cancer immunotherapies. According to the MedTech this kind of detailed profiling could help research and development identify certain nuances that might affect a treatment’s mechanism of action, provide biomarkers for response and potential toxicity. 

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

Using it’s end to end single cell platform that enables high resolution profiling of the immune system at an industrial scale, the company is exploring the origin of cancer fighting T-cells and the effect of PD-1 blockades.

“If we can characterize the immune system at a deep level of granularity and consistency, we can unlock insights that will dramatically enhance our understanding of health, disease and therapeutic development. For cancer and well beyond.”

“We are implementing a complicated engineering pipeline. We wanted to scale to hundreds of patients and thousands of samples,” said Danny Wells. “Right now, in the world of cancer therapy, there are new drugs coming on the market that are called checkpoint inhibitors. [We’re] trying to understand how these molecules are working and find new combinations and new targets. We need to see the immune system in full granularity.”

The company’s combination of hardware and software is suggested to allow researchers to do just that, according to Wells. “It’s a vertically integrated platform for single cell profiling,” he said. “We go even further to figure out what the biology is there and figure that out in a new combination design for the trial.”

“Our mission is to map the immune system with neural networks and transfer learning techniques informed by deep immunology knowledge,” said Luis Voloch, in a statement. “We developed the tools and know-how 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.”

“This whole approach that we have around looking at all of these indications — we believe that the right way and most powerful way to study these diseases is to look at the immune system from the top down,” said Voloch. “Looking at all of these different scenarios. From the top, you see these patterns than wouldn’t be available otherwise.”

The company is currently also exploring strategic partnerships with academic research institutions, biopharmaceuticals, and biotechs to expand the use of their technology and data platforms to discover biological insights, advance therapeutic discoveries and accelerate research and development. 

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