Kayla Abbassi, Senior Account Manager
Due to the complexity of the immune system, pharma companies cannot accurately predict how drugs will affect each person’s immune cells, making it harder for doctors to improve patient outcomes. In May 2020, Immunai launched to provide an all-in-one solution to this problem.
By comprehensively mapping the immune system with single-cell genomics and AI, Immunai is providing pharma companies with a better understanding of how individual immune systems work and respond to therapy, enabling them to power new therapeutic discoveries, accelerate drug development, and improve patient outcomes. Immunai leverages single-cell technologies to profile immune cells and machine learning to map incoming data to hundreds of cell types and states, building the largest proprietary data set in the world for clinical immunological data.
Unlike other companies that use polymerase chain reaction (PCR) or bulk sequencing technologies, Immunai analyzes RNA at the single-cell level, which allows researchers to measure the immune system at scale. From just one blood sample, Immunai generates a terabyte of data, effectively disrupting legacy companies by analyzing 10,000x more data for each cell. Then using AI and machine learning algorithms, Immunai identifies and understands novel elements within hundreds of different cell types and applies those learnings across different diseases.
Immunai most recently entered a collaboration with Baylor College of Medicine to build more effective, targeted cancer therapies. Baylor is leveraging Immunai’s technology to analyze natural killer T (NKT) cells and genetically modify them into immunotherapies that can target a variety of cancers, with a focus on solid tumors. Results from an ongoing clinical trial recently published in Nature Medicine showed the immunotherapy was effective for patients with neuroblastoma, a form of childhood cancer.