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The company uses single-cell tech and AI to discover and develop new therapies and drug combinations
Last year, Immunai, a New York and Tel Aviv-based biotech company, launched with the ambitious goal of mapping the human immune system, using AI and machine learning algorithms to be able to detect, diagnose, and treat disease.
Now, less than a year later, the company, which announced a $60 million round of funding on Thursday, is already taking on an even bigger challenge: reprogramming the immune system, leveraging single-cell tech and AI to discover, and develop, new therapies and drug combinations.
"What we've been doing in the past two plus years is actually figuring out what the different stimuli are, how they affect the immune system, and now we're taking those insights and we're using them to inform our partners on how to make certain immunotherapies more efficient, and which combination therapies would be more effective," said Noam Solomon, Immunai’s co-founder and CEO, told me.
"We can also reprogram specific immune cells to make them more efficient, and find novel targets for immunotherapy."
Immunai can extract over a terabyte of data from a single blood sample. Its database, called Annotated Multi-omic Immune Cell Atlas (AMICA), along with machine learning algorithms, can then be used to map incoming data to hundreds of cell types and states in order to create immune profiles by highlighting differentiated elements. Its database of immune profiles can be used for biomarker discovery and insight generation, identifying subtle changes in cell type and state-specific expression that can be used to distinguish them from normal expression.
The company has mapped out millions of immune cells and their functions, building what it says is the largest proprietary data set in the world for clinical immunological data. It can analyze the evolution of disease, including cancer to autoimmune disorders to cardiovascular diseases.
Now, the company is taking that data and using it to reprogram the immune system, which means, for example, changing T cells in some therapies; the company is able to see how T cells work in response to different types of therapy, and understand what makes some T cells do a better job at fighting cancer. Once it identifies the features that make those T cells better, the company can then to engineer them.
"The platform is already very powerful for generating these hypotheses but one of the things that is critical is for us to move from correlative work to understanding causes. Today, we are already able to see that, in certain types of patients who have received certain types of checkpoint blockades, that some genes are unregulated and others are downregulated, with maybe a difference between responders and non-responders," Luis Voloch, the company's CTO and co-founder, explained.
That work is important for narrowing the scope of questions that experimenters want to ask as they think about their drug programs, but it doesn't tell you with great certainty that something is causal," he said.
"So, the next step is to build out what we call the functional genomics platform where we take the insights that are gleaned from this mapping that we do, and then bring it into a system where we can do in vitro and in vivo validation by procurement systems and examining cells either in culture or in mice, ultimately having our discovery validate targets. We're very excited about the direction we’re headed there."
Immunai is currently working with multiple Fortune 100 pharma companies and has partnered with companies like 10x Genomics and medical and academic institutions such as Baylor, UPenn, Harvard, Memorial Sloan Kettering and Mass General.
The new round, which brings the company’s total funding to date to over $80 million, was led by Schusterman Family Investments, Duquesne Family Office, Catalio Capital Management, and Dexcel Pharma, with additional participation from existing investors Viola Ventures and TLV Partners.
Immunai will use the new money to better support discovery, prioritization, and development of new therapies and drug combinations. It will also use the funding to continue to expand AMICA.
"AMICA is a really critical asset for us already. It is helping us to do a better job with cell annotation and characterization than, we believe, anybody else in the world. As we build it out with clinical data, and lab metadata, etc, it also allows us to start to look across different disease areas, and understand, for example, what makes an effective T cell," said Voloch.
That also means using the funding to invest in procuring the best data to incorporate into AMICA to gain better insights, as well as for hiring, with the goal of doubling its 65 person team over the next year.
"AMICA is differentiated in the fact that we are building an end-to-end platform, and we are very engineering heavy. We have a very large engineering group, people that were trained in the best recertifications and who came from Google and Facebook and Microsoft and Palantir," Solomon said.
"Every sample of tissue that we measure contains over a terabyte of information and we are building a database that has tens of thousands of samples, we will be getting huge amounts of data. So, running complicated algorithms adding data like this requires having specific and very unique approaches. That means having an engineering team like we have is very important and we are very proud of this team," said Solomon.
Going forward, the reprogramming of the immune system will be the company's focus for at least the next few years, as the platform becomes more and more sophisticated.
"Just as an example, imagine what we could do all in vivo studies in one month. I'm not saying that we are doing everything in one month, but I’m saying that a lot of the work will be to optimized for doing more experiments. It will take time; it will probably not be done just in a few months, it will take a few years but I'm happy to say that we are seeing tremendous progress. A lot of the financing will go toward helping us grow."
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