Immunai Raises $60M to Decode the Immune System with Machine Learning and AI – AlleyWatch
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.Immunaihas 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 companys 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. Immunais team of computational biologists and immunologists work with our partners at pharmaceutical companies to figure out the implications of what Immunai has found, whether its 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 dont have access to any comprehensive, granular insight into how the immune system works, how it responds to the drugs or therapies theyre 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, weve 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 were doing. Companies have been trying to understand the immune system for years, but have been limited by traditional bulk sequencing technologies, which dont provide nearly enough data. By analyzing gene expression levels, protein markers, TCR and BCR fragments, and other single-cell omics, weve 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 worlds 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?
Immunais 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.
Whats 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. Weve 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 didnt expect from the pandemic was being able to raise $60M without meeting the lead investors face to face. This is something that frankly, I didnt expect happening, and definitely didnt 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 weve put it together.
What are the milestones you plan to achieve in the next six months?
Were going to use this new financing round to build and improve our platform. With our expansion into functional genomics, well 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. Were 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. Were 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 youre building and bring it to market quickly. Lean Startup is one of the most important business books Ive read; its critical for any business, but particularly for one with a limited runway. Whats 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?
Were transitioning from observational genomics to functional genomics. Were concentrating on two major projects: improving the ability to target new checkpoints and validate targets for cell therapies. Just in the last year, weve been able to identify new mechanisms of resistance with partners in record time. At this pace, we hope the work well be able to do in the next couple of years will be groundbreaking and life-saving, but its too early to say specifically where well be.
Whats your favorite outdoor dining restaurant in NYC
Cafe Mogador on St Marks.
Go here to see the original:
Immunai Raises $60M to Decode the Immune System with Machine Learning and AI - AlleyWatch
- Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG... - April 12th, 2025 [April 12th, 2025]
- Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry - Nature - April 12th, 2025 [April 12th, 2025]
- Machine learning-based prediction of the thermal conductivity of filling material incorporating steelmaking slag in a ground heat exchanger system -... - April 12th, 2025 [April 12th, 2025]
- Do LLMs Know Internally When They Follow Instructions? - Apple Machine Learning Research - April 12th, 2025 [April 12th, 2025]
- Leveraging machine learning in precision medicine to unveil organochlorine pesticides as predictive biomarkers for thyroid dysfunction - Nature - April 12th, 2025 [April 12th, 2025]
- Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning... - April 12th, 2025 [April 12th, 2025]
- AI and Machine Learning - Bentley and Google partner to improve asset analytics - Smart Cities World - April 12th, 2025 [April 12th, 2025]
- Where to find the next Earth: Machine learning accelerates the search for habitable planets - Phys.org - April 10th, 2025 [April 10th, 2025]
- Concurrent spin squeezing and field tracking with machine learning - Nature - April 10th, 2025 [April 10th, 2025]
- This AI Paper Introduces a Machine Learning Framework to Estimate the Inference Budget for Self-Consistency and GenRMs (Generative Reward Models) -... - April 10th, 2025 [April 10th, 2025]
- UCI researchers study use of machine learning to improve stroke diagnosis, access to timely treatment - UCI Health - April 10th, 2025 [April 10th, 2025]
- Assessing dengue forecasting methods: a comparative study of statistical models and machine learning techniques in Rio de Janeiro, Brazil - Tropical... - April 10th, 2025 [April 10th, 2025]
- Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases - Nature - April 10th, 2025 [April 10th, 2025]
- How AI, Data Science, And Machine Learning Are Shaping The Future - Forbes - April 10th, 2025 [April 10th, 2025]
- Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer... - April 10th, 2025 [April 10th, 2025]
- From fax machines to machine learning: The fight for efficiency - HME News - April 10th, 2025 [April 10th, 2025]
- Carbon market and emission reduction: evidence from evolutionary game and machine learning - Nature - April 10th, 2025 [April 10th, 2025]
- Infleqtion Unveils Contextual Machine Learning (CML) at GTC 2025, Powering AI Breakthroughs with NVIDIA CUDA-Q and Quantum-Inspired Algorithms - Yahoo... - March 22nd, 2025 [March 22nd, 2025]
- Karlie Kloss' coding nonprofit offering free AI and machine learning workshop this weekend - KSDK.com - March 22nd, 2025 [March 22nd, 2025]
- Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals -... - March 22nd, 2025 [March 22nd, 2025]
- Machine learning analysis of cardiovascular risk factors and their associations with hearing loss - Nature.com - March 22nd, 2025 [March 22nd, 2025]
- Weekly Recap: Dual-Cure Inks, AI And Machine Learning Top This Weeks Stories - Ink World Magazine - March 22nd, 2025 [March 22nd, 2025]
- Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of... - March 22nd, 2025 [March 22nd, 2025]
- Machine learning aids in detection of 'brain tsunamis' - University of Cincinnati - March 22nd, 2025 [March 22nd, 2025]
- AI & Machine Learning in Database Management: Studying Trends and Applications with Nithin Gadicharla - Tech Times - March 22nd, 2025 [March 22nd, 2025]
- MicroRNA Biomarkers and Machine Learning for Hypertension Subtyping - Physician's Weekly - March 22nd, 2025 [March 22nd, 2025]
- Machine Learning Pioneer Ramin Hasani Joins Info-Tech's "Digital Disruption" Podcast to Explore the Future of AI and Liquid Neural Networks... - March 22nd, 2025 [March 22nd, 2025]
- Predicting HIV treatment nonadherence in adolescents with machine learning - News-Medical.Net - March 22nd, 2025 [March 22nd, 2025]
- AI And Machine Learning In Ink And Coatings Formulation - Ink World Magazine - March 22nd, 2025 [March 22nd, 2025]
- Counting whales by eavesdropping on their chatter, with help from machine learning - Mongabay.com - March 22nd, 2025 [March 22nd, 2025]
- Associate Professor - Artificial Intelligence and Machine Learning job with GALGOTIAS UNIVERSITY | 390348 - Times Higher Education - March 22nd, 2025 [March 22nd, 2025]
- Innovative Machine Learning Tool Reveals Secrets Of Marine Microbial Proteins - Evrim Aac - March 22nd, 2025 [March 22nd, 2025]
- Exploring the role of breastfeeding, antibiotics, and indoor environments in preschool children atopic dermatitis through machine learning and hygiene... - March 22nd, 2025 [March 22nd, 2025]
- Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations -... - March 22nd, 2025 [March 22nd, 2025]
- 'We want them to be the creators': Karlie Kloss' coding nonprofit offering free AI and machine learning workshop this weekend - KSDK.com - March 22nd, 2025 [March 22nd, 2025]
- New headset reads minds and uses AR, AI and machine learning to help people with locked-in-syndrome communicate with loved ones again - PC Gamer - March 22nd, 2025 [March 22nd, 2025]
- Enhancing cybersecurity through script development using machine and deep learning for advanced threat mitigation - Nature.com - March 11th, 2025 [March 11th, 2025]
- Machine learning-assisted wearable sensing systems for speech recognition and interaction - Nature.com - March 11th, 2025 [March 11th, 2025]
- Machine learning uncovers complexity of immunotherapy variables in bladder cancer - Hospital Healthcare - March 11th, 2025 [March 11th, 2025]
- Machine-learning algorithm analyzes gravitational waves from merging neutron stars in the blink of an eye - The University of Rhode Island - March 11th, 2025 [March 11th, 2025]
- Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods - Nature.com - March 11th, 2025 [March 11th, 2025]
- AI in Esports: How Machine Learning is Transforming Anti-Cheat Systems in Esports - Jumpstart Media - March 11th, 2025 [March 11th, 2025]
- Whats that microplastic? Advances in machine learning are making identifying plastics in the environment more reliable - The Conversation Indonesia - March 11th, 2025 [March 11th, 2025]
- Application of machine learning techniques in GlaucomAI system for glaucoma diagnosis and collaborative research support - Nature.com - March 11th, 2025 [March 11th, 2025]
- Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding - Nature.com - March 11th, 2025 [March 11th, 2025]
- Hugging Face Tutorial: Unleashing the Power of AI and Machine Learning - - March 11th, 2025 [March 11th, 2025]
- Utilizing Machine Learning to Predict Host Stars and the Key Elemental Abundances of Small Planets - Astrobiology News - March 11th, 2025 [March 11th, 2025]
- AI to the rescue: Study shows machine learning predicts long term recovery for anxiety with 72% accuracy - Hindustan Times - March 11th, 2025 [March 11th, 2025]
- New in 2025.3: Reducing false positives with Machine Learning - Emsisoft - March 5th, 2025 [March 5th, 2025]
- Abnormal FX Returns And Liquidity-Based Machine Learning Approaches - Seeking Alpha - March 5th, 2025 [March 5th, 2025]
- Sentiment analysis of emoji fused reviews using machine learning and Bert - Nature.com - March 5th, 2025 [March 5th, 2025]
- Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre... - March 5th, 2025 [March 5th, 2025]
- JFrog and Hugging Face team to improve machine learning security and transparency for developers - SDxCentral - March 5th, 2025 [March 5th, 2025]
- Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning - Nature.com - March 5th, 2025 [March 5th, 2025]
- AI and Machine Learning Operationalization Software Market Hits New High | Major Giants Google, IBM, Microsoft - openPR - March 5th, 2025 [March 5th, 2025]
- FICO secures new patents in AI and machine learning technologies - Investing.com - March 5th, 2025 [March 5th, 2025]
- Study on landslide hazard risk in Wenzhou based on slope units and machine learning approaches - Nature.com - March 5th, 2025 [March 5th, 2025]
- NVIDIA Is Finding Great Success With Vulkan Machine Learning - Competitive With CUDA - Phoronix - March 3rd, 2025 [March 3rd, 2025]
- MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival - Nature.com - March 3rd, 2025 [March 3rd, 2025]
- AI and Machine Learning - Identifying meaningful use cases to fulfil the promise of AI in cities - SmartCitiesWorld - March 3rd, 2025 [March 3rd, 2025]
- Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency... - March 3rd, 2025 [March 3rd, 2025]
- Predicting Ag Harvest using ArcGIS and Machine Learning - Esri - March 1st, 2025 [March 1st, 2025]
- Seeing Through The Hype: The Difference Between AI And Machine Learning In Marketing - AdExchanger - March 1st, 2025 [March 1st, 2025]
- Machine Learning Meets War Termination: Using AI to Explore Peace Scenarios in Ukraine - Center for Strategic & International Studies - March 1st, 2025 [March 1st, 2025]
- Statistical and machine learning analysis of diesel engines fueled with Moringa oleifera biodiesel doped with 1-hexanol and Zr2O3 nanoparticles |... - March 1st, 2025 [March 1st, 2025]
- Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning - BMC Public Health - March 1st, 2025 [March 1st, 2025]
- The Evolution of AI in Software Testing: From Machine Learning to Agentic AI - CSRwire.com - March 1st, 2025 [March 1st, 2025]
- Wonder Dynamics Helps Boxel Studio Embrace Machine Learning and AI - Animation World Network - March 1st, 2025 [March 1st, 2025]
- Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study... - March 1st, 2025 [March 1st, 2025]
- Workplace Predictions: AI, Machine Learning To Transform Operations In 2025 - Facility Executive Magazine - March 1st, 2025 [March 1st, 2025]
- Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire - Nature.com - March 1st, 2025 [March 1st, 2025]
- Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential... - March 1st, 2025 [March 1st, 2025]
- Utilization of tree-based machine learning models for predicting low birth weight cases - BMC Pregnancy and Childbirth - March 1st, 2025 [March 1st, 2025]
- Machine learning-based pattern recognition of Bender element signals for predicting sand particle-size - Nature.com - March 1st, 2025 [March 1st, 2025]
- Wearable Tech Uses Machine Learning to Predict Mood Swings - IoT World Today - March 1st, 2025 [March 1st, 2025]
- Machine learning can prevent thermal runaway in EV batteries - Automotive World - March 1st, 2025 [March 1st, 2025]
- Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes - Nature.com - March 1st, 2025 [March 1st, 2025]
- Data Analytics Market Size to Surpass USD 483.41 Billion by 2032 Owing to Rising Adoption of AI & Machine Learning Technologies - Yahoo Finance - March 1st, 2025 [March 1st, 2025]
- Predictive AI Only Works If Stakeholders Tune This Dial - The Machine Learning Times - March 1st, 2025 [March 1st, 2025]
- Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a... - March 1st, 2025 [March 1st, 2025]