With its proprietary, top-down view of the immune system and purportedly the world’s largest proprietary data devoted to clinical immunologics, it aims to catalyze significant improvements in disease detection, diagnosis and treatment.
Less than two years since its founding, Immunai left stealth mode in its bid to fully map the entire immune system. With its proprietary, top-down view of the immune system and purportedly the world’s largest proprietary data devoted to clinical immunologics, it aims to catalyze significant improvements in disease detection, diagnosis and treatment.
The company uses largely proprietary technology to leverage single-cell analysis and machine learning to uncover patterns within the immune system that are biologically relevant among diseases and treatment modalities.
Exhausted CD8 cells are a good example, Danny Wells, Ph.D., one of the scientific founders, told BioSpace.
“In chronic viral infections and HIV, high levels of exhausted CD8 cells mean the immune system failed to fight the disease, but they also play a role in cancer. In that disease, they are a sign your immune system is wearing itself out trying to fight. Checkpoint inhibitors help relieve them. There are many more examples to be discovered that can unlock new therapeutic areas in autoimmune diseases, viral diseases and cancer,” Wells said.
Immunai’s approach is grounded in peer-reviewed work Wells and colleagues published last July in Nature, discussing how PD-1 remodels the immune system of the tumor after treatment. “Our hypothesis was that the drug affected the immune cells that had entered the tumor, but we found it actually drove a new immune response from the immune system,” Wells said.
As the paper explained, “The expansion of T cell clones did not derive from pre-existing tumor-infiltrating T lymphocytes; instead, the expanded clones consisted of novel clonotypes that had not previously been observed in the same tumor.” Specifically, the T-cell response to the checkpoint blockade appears to have been derived from novel T cell clones that only recently entered the tumor.
“That’s important because it suggests we can understand how a patient is responding to a therapy by measuring their blood,” Wells said. The alternative is to perform a tissue biopsy.
“This has shaped the vision for our company,” Wells continued. “We’re finding the effects of these (therapeutic, immunomodulating) molecules are very broad spectrum and not what we expected. We strongly believe our high dimension technology, applied to the peripheral immune system, gives insights less invasively and over time, to enable really deep insights into how a drug is working.”
It’s important to note that in immuno-oncology, the drugs are biologics. They are cells taken from the patient, sometimes engineered, and expanded. So, although the pharmaceutical developer has characterized these cells, “We’re bringing advances that let us determine which of that type of cell, once returned to the body, are the ‘drug’ and which are part of the patient’s immune system. Therefore we can study how subpopulations of the therapy are working in the patient,” Wells explained. That often means detecting 1 gene amongst 20,000.
“With those insights, we can identify new combinations to increase efficacy and decrease resistance,” he said.
To enable such insights, Immunai developed a vertically-integrated platform for multi-omic single-cell profiling.
“Legacy platforms let you measure a few different genes in immune cells, and flow cytometry can measure maybe 10 marker on a cell. That gets you part of the way there, but there are tens of thousands of genes and hundreds of surface markers,” Wells said. In contrast, Immunai’s approach replaced a siloed view of the immune system to provide the full picture, “so you can imagine the immune system in ‘full color’ as we say. That unlocks a whole new world of discovery.”
By profiling the cells using single-cell technologies, Immunai derives more than a terabyte of data from a single blood sample. Its machine learning algorithms map that data to hundreds of cell types and states to create immune profiles based on highlighting differentiated elements. Finally, the company’s database of immune profiles can be applied to support biomarker discovery and to generate additional insights about the immune system based on the subtle changes in cell type and state-specific expression that help distinguish that from normal expression.
Biopharmaceutical companies, therefore, can identify the subtle nuances in cell abundances, cell function, mechanisms of action and biomarkers for toxicity response to more accurately measure the efficacy of immunotherapies.
Currently, Immunai is focused on oncology. “In the next few months, we also will be studying different type of immuno-oncologic drugs and different therapeutic areas, like myocardiology,” Luis Voloch, founder and CTO, told BioSpace.
Immunai is working with more than 10 medical centers, as well as multiple partners in big pharma, biotech and academia.
“Our partners send us frozen cells and we perform all the analyses, handling the lab-to-computational pipeline,” Voloch said. Generating biologically relevant data typically takes a few weeks.
The company recently received $20 million in seed funding from Viola Ventures and TLV Partners based upon its technology and founders who hail from Harvard and MIT, Stanford University, Palantir, the Parker Institute for Cancer Immunotherapy and New York University.
Upcoming milestones include scaling the peripheral blood analysis platform for thousands of samples while continuing to show clinical relevance. Additional plans include increasing its R&D staff, both in the lab and computationally.
