Immunai is based in New York. A biotech startup company combines multi-omic single-cell analytics and structure learning to determine novel. Immunological observations that lead to the discovery and development of more effective and targeted immune therapies.
Immunai was funded $60 million in Series A funding. The investment contributed by Schusterman Family Investments, Duquesne Family Office, Catalio Capital Management, and Dexcel Pharma, with participation in existing investors Viola Ventures and TLV Partners.
Eased by this new funding, it’s now ready to expand into the development of entirely new therapies based on its data and ML’s strength and breadth.
The startup’s unique edge combines the most important and most vital data set of its type available, made in cooperation with world-leading immunological research organizations, with its machine learning technology to deliver analytics at an unprecedented scale.
Noam Solomon, the Immunai’s co-founder and CEO said, implicates the immune system in nearly every illness, making their technology critical for identifying, diagnosing, and treating the disease from cancer and infectious disease autoimmune disorders. Since Immunai’s founding in 2018, they have been mapping the immune system through observational genomics, using multi-omic single-cell technologies and machine learning to understand better how the immune system operates.
Immunai has already shown that its platform can help identify optimal points for existing therapies with the Baylor College of Medicine. They assisted it with a cell therapy product for treating neuroblastoma (a type of cancer that spreads from immune cells, often in the adrenal glands).
The General Partner, Dr. Kenan Turnacioglu, at Catalio Capital said, it’s progressively clear that the immune system is even more challenging than they imagined, and advancing their understanding combining contemporary techniques with practical data approaches. It reflects this intersection in Immunai’s founding team and leadership, and they are excited to be working with Immunai on this next stage of growth. As they bring together the smartest cares for the fields of single-cell genomics, machine learning, immunology, and data engineering to collect on this task.
By: K. Tagura
Author statement:
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