NEW YORK – New York City-based start-up Immunai aims to combine multiomic measurements with machine-learning analysis to develop immune profiles linked to disease.
The company, which has been operating in stealth mode since 2019, announced last week that it has raised $20 million in seed funding from investors including Viola Ventures and TLV Partners and has established clinical research collaborations with a number of medical centers as well as commercial partnerships with several biopharma companies focused on cancer immunotherapy.
Immunai's platform profiles immune cells via a combination of single-cell RNA-seq, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), VDJ-seq, and a proprietary technology that Luis Voloch, co-founder and chief technology officer of the company, said it planned to publish on in coming months. Using these approaches, the system is able to collect single-cell transcriptomic data as well as measurements of more than 100 surface proteins per cell, Voloch said.
The company then uses machine learning to analyze this data, mapping it to different immune cell types and generating profiles of the populations of immune cells present in a sample that it can correlate to outcomes like disease state or response to treatment.
Immunai sees immunoncology as a major opportunity, said Noam Solomon, a co-founder and the firm's CEO, but he added that it is also interested in applying the technology to conditions including autoimmune disorders and infectious disease.
Currently, he said, the company is focused primarily on building a large immunology database that will allow researchers and customers to investigate immune response across a variety of diseases.
"We are building a large database for immune insights from the single-cell data," Solomon said, calling the approach "almost disease agnostic."
"Surprisingly or not, we have been able to show, that even if, say, you just care about melanoma, the response to anti-PD1 treatment for melanoma, if you look at patients with autoimmune disorders and genes that are relevant for those disorders, you improve your understanding of melanoma response, as well," he said. "We are trying to understand the immune system, and there are parameters of your immune health that will be relevant to your response to COVID-19, your response to cancer treatments, and to the way that you age. We are trying to decode these mechanisms."
The company is building its database through collaborations with various academic research teams, Solomon said, most of them working in some form of cancer immunotherapy.
As an example of the potential of the company's approach, he pointed to a Nature Medicine study published last year by authors including Immunai's scientific co-founders Daniel Wells, senior data scientist at the Parker Institute for Cancer Immunotherapy, and Ansuman Satpathy, assistant professor of pathology at Stanford University.
In the study, the researchers used single-cell RNA-seq and T cell receptor sequencing on 79,046 cells from patients with basal or squamous cell carcinoma before and after treatment with PD-1 inhibitors. They found that existing tumor-specific T cells were activated by anti-PD-1 treatment to only a limited extent and that response to treatment was instead driven by a new repertoire of T cells.
Voloch said Immunai has the capacity to process more than 100 samples per week on its platform and has completed collaborations analyzing samples from on the order of hundreds of patients.
Immunai is also working with a number of pharma companies to build its database and demonstrate its value. Voloch said it is in the process of closing a seven-figure contract with a large pharma company with the potential to significantly expand the contract provided the initial work is successful.
He said the company expects its platform could prove useful for a number of parts of the drug development process, ranging from elucidating mechanisms of action to target discovery to eventually predicting patient response of the development of resistance to treatment.
Regarding the latter questions, Voloch said the company's technology is not currently able to provide this sort of information, "but we believe that in a couple of years we will get there."
Like many firms in the immunology and immunoncology space, Immunai is also exploring how its technology might address the SARS-CoV-2 pandemic.
Voloch said Immunai was looking at whether it could help research into how different immune profiles lead to different immune responses and outcomes in the disease.
The company is one of a number of outfits looking to use immune profiling data to aid disease research or drug and diagnostics development. Seattle-based Adaptive Biotechnologies, for instance, uses its next-generation sequencing-based platform to generate T and B cell profiles of samples while also mapping those cells to their likely antigens. The company offers minimal residual disease monitoring for several blood cancers as well as pharma and biopharma services. It said last week that it was conducting a 1,000-subject study looking for T cell profiles linked to immune response and outcomes among COVID-19 patients.
Several firms have also launched technologies in recent years focused on immune profiling from the proteomic side. Fluidigm has found a market in immuno-oncology for its CyTOF mass cytometry platform which uses metal-linked antibodies combined with time-of-flight mass spectrometry to measure dozens of proteins at the single-cell level. In 2017, the company launched an imaging version of the technology, the Hyperion, which provides spatial information on cells and tissues of interest in addition to protein data.
Last year, Menlo Park, California-based start-up IONPath launched a competing system, the MIBIscope, which, like Hyperion uses metal-conjugated antibodies to measure proteins of interest. The MIBIscope uses multiplexed ion beam imaging (MIBI) to ionize samples for analysis, with that analysis then done on a secondary-ion mass spec with a TOF analyzer. Fluidigm has sued IONPath alleging patent infringement.
Menlo Park-based Akoya Biosciences (which like IONPath was launched to commercialize research from the lab of Stanford University researcher Garry Nolan) is also approaching immune profiling from the protein side with its CODEX platform, which uses oligonucleotide-linked antibodies to detect proteins of interest in tissue samples, enabling highly multiplexed protein imaging at single-cell resolution using conventional fluorescence microscopy.