The immune system at its core is a complex system of cells, organs, and tissues. These components work in unison to fight infection in the form of microbes. Developing an understanding of how this intricate system works is critical in ensuring that society as a whole has adequate immune health to combat disease and infection. Immunai has built the largest database for immunology in the world using machine learning and AI to map the entire immune system at a granular and specific level. This data can be leveraged by the healthcare industry to provide better therapeutics that get to market faster. This understanding will also allow biotech companies and pharmaceutical manufacturers to radically personalize therapeutics in the future. Immunai is initially focused on the oncology market but the offering is versatile can be applied to things like autoimmune disorders and infectious diseases like COVID-19.
AlleyWatch caught up with CEO and Cofounder Noam Solomon to learn more about the impact that Immunai is having in the understanding of the immune system, the company’s partnerships, experience fundraising during the pandemic, latest funding round, and much, much more…
Who were your investors and how much did you raise?
This $60M Series A round 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.
Tell us about the product or service that Immunai offers.
Immunai is on a mission to reprogram the immune system to advance personalized medicine to better detect, diagnose, and treat disease. To do so, Immunai has generated the largest proprietary database for immunology in the world, known as the Annotated Multi-omic Immune Cell Atlas (AMICA). This platform incorporates variables such as clinical lab metadata (e.g., processing wait time) and batch data (e.g., hospital), and others; then, it leverages machine learning and artificial intelligence to complete the annotation and characterization of immune cells. Immunai’s team of computational biologists and immunologists work with our partners at pharmaceutical companies to figure out the implications of what Immunai has found, whether it’s a new therapy, a drug combination, or a diagnostic.
What inspired the start of Immunai?
When I met my cofounder Luis, I was a math postdoc at MIT and Luis was working to apply machine learning to biology. Together, we wanted to bring “transfer learning” AI methods to what we believe would solve the biggest problem in society today – disease.
All disease can be traced back to the immune system. But what we realized is that pharmaceutical companies don’t have access to any comprehensive, granular insight into how the immune system works, how it responds to the drugs or therapies they’re developing, and what patients are most likely to benefit. With our scientific cofounders, Ansu Satpathy (assistant professor at Stanford for cancer immunology), Danny Wells (researcher at the Parker Institute for cancer immunotherapy) and Dan Littman (Professor at NYU and HHMI investigator) we realized that with single-cell technologies we would be able to measure and map the immune system with granularity and specificity like never available before.
At Immunai, we’ve combined the brightest minds across single-cell genomics, data science, and engineering to build the largest proprietary database on immunology in the world. We hope our work will lead to a better understanding of how to overcome the key unsolved problems and bottlenecks in immunotherapy discovery and development. We want to enable the development of more effective therapies and combinations for each patient, accelerate the ability to bring these therapies to market, and ultimately, provide better options for patients at a faster pace than ever before.
How is Immunai different?
No one is doing exactly what we’re doing. Companies have been trying to understand the immune system for years, but have been limited by traditional bulk sequencing technologies, which don’t provide nearly enough data. By analyzing gene expression levels, protein markers, TCR and BCR fragments, and other single-cell omics, we’ve compiled 10,000 times more data for each immune cell than others before, giving partners a view of the immune system with a full spectrum of color and dimensionality.
Further, our proprietary machine learning and single-cell analysis that we apply to mine AMICA ™, the world’s largest proprietary Multiomic Immune Cell Atlas, allow us to understand the immune system at scale with unprecedented granularity and consistency. This provides a solution to the prohibitive batch effect problem that our competitors have not been able to solve.
What market does Immunai target and how big is it?
Immunai’s offering can be applied to multiple disease areas – from cancer to autoimmune disorders to infectious diseases like COVID-19. The company is primarily focusing on the oncology market, which is currently set to surpass $469.5 billion by 2026.
What’s your business model?
Immunai partners with biopharmaceutical and biotech companies to answer critical questions like what makes T-cells expand, persist, and penetrate a tumor, which cells are cytotoxic, which cells in a cell therapy drive response, what are the immunological signatures that are more likely to lead to clinical response to different therapies, and more. These partnerships are usually structured as milestone-based collaborations, ranging from prospective clinical trial design and biomarker discovery to earlier target discovery and target validation.
How has COVID-19 impacted your business?
COVID-19 has impacted the way we work and the pace at which we work. We’ve asked our employees who are not working in the lab to work from home and have implemented strict social distancing protocols within the lab. In the biopharma world, business is bigger than ever before, so we have many new partnerships in a variety of disease areas, including Immuno-Oncology, Autoimmunity, Neurodegenerative diseases, and infectious diseases .
What was the funding process like?
Fast but complex. It happened over a few very eventful months, with many important partnerships forged and multiple parties involved in the financing round, which all took place during a worldwide pandemic, of course.
What are the biggest challenges that you faced while raising capital?
The financing round happened as we were closing a few important partnerships, so running both responsibilities as CEO was non-trivial. In the middle of it all, life happened, and we had to deal with family health issues, including the fact that my wife and I had caught COVID, but we were both fine, luckily.
But what I didn’t expect from the pandemic was being able to raise $60M without meeting the lead investors face to face. This is something that frankly, I didn’t expect happening, and definitely didn’t expect would happen so fast.
What factors about your business led your investors to write the check?
Our investors have witnessed the accelerated growth of our platform and are aligned with our vision to reprogram immunity. Machine learning crossed with genomics will unlock the mysteries of the immune system and lead to improved therapies. To actually execute on this vision, a world-class team is required, and we’ve put it together.
What are the milestones you plan to achieve in the next six months?
We’re going to use this new financing round to build and improve our platform. With our expansion into functional genomics, we’ll be funding collaborations with partners to answer the most pressing questions in immuno-oncology, cell therapy, infectious disease, and autoimmunity, including key biology driving clinical endpoints and target discovery.
We also plan to invest heavily in growth and double our team of 70 by year-end. We currently have a large lab in New York with 50 scientists working on sequencing and tech development. We’re looking to add more people to the team to develop new assets and IP.
We also plan to invest heavily in growth and double our team of 70 by year-end. We currently have a large lab in New York with 50 scientists working on sequencing and tech development. We’re looking to add more people to the team to develop new assets and IP.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Understand the essence of what you’re building and bring it to market quickly. Lean Startup is one of the most important business books I’ve read; it’s critical for any business, but particularly for one with a limited runway. What’s the most expeditious experiment you can run to see if your customers actually care about your product.
Where do you see the company going now over the near term?
We’re transitioning from observational genomics to functional genomics. We’re concentrating on two major projects: improving the ability to target new checkpoints and validate targets for cell therapies. Just in the last year, we’ve been able to identify new mechanisms of resistance with partners in record time. At this pace, we hope the work we’ll be able to do in the next couple of years will be groundbreaking and life-saving, but it’s too early to say specifically where we’ll be.
What’s your favorite outdoor dining restaurant in NYC
Cafe Mogador on St Marks.
