Immunai recently announced results from collaboration with Baylor College of Medicine (BCM) in a review published in Nature Medicine.
Immunai and BCM have been working together since 2019, and BCM researchers, led by Andras Heczey and Leonid Matelista, have been developing the first-in-human cell therapy for neuroblastoma that was tested in human patients and showed interim Ph1 results with three responders out of 12.
By analyzing the patient's samples with Immunai's proprietary platform, Immunai was able to identify nuanced insights and a potential gene modifier called BTG1 that may make this cell therapy more durable and, thereby, potentially more clinically efficacious. Even though this new modified drug has not yet been tested on human patients, the lab results seem encouraging.
The following is an interview with Immunai's CEO Noam Solomon:
Jerusalem Post: How do you feel about the big news?
Solomon: The credit should go to the excellent researchers at BCM, led by Andras Heczey and Leonid Matelitsa. They are the ones that developed the drug after years of research. Our contribution was to apply our platform, analyze the differences between responders and non-responders, and identify genetic modifications of the original cells. The collaboration with BCM allowed us to demonstrate the vertically integrated nature of the platform, from immune profiling of the actual cellular therapies with our single-cell multi-modal capabilities, continuing in a granular machine learning-driven differential analysis of genes and proteins, leveraging not only the cells we profiled in this experiment but also the AMICA atlas, which is our extensive proprietary clinical-genomic database for the immune system that enable the granular contextualization of patients samples. After the computational analysis, we were able to do functional validation of the correlative insights with Functional Genomics (FGx), which allowed us to do gene editing in the lab to validate our hypothesis.
Can you explain what is unique about it?
Solomon: The platform is unique in two ways. First, it is a vertically integrated platform that leverages wet-lab immunological, computational and AI capabilities into an "end-to-end solution." If some companies do wet lab work and others offer computational capabilities, our platform is built to integrate both vertically. Second, it is the first company to map the human immune system with single-cell multi-omics, so we decided to put it at the center of our research. We leverage advanced methods to study immune cells with high-content and high-throughput capabilities.
Why is this so important to study the immune system with high-content and high-throughput capabilities?
The immune system is incredibly complex. When we started, people told me it was even infinitely complex. I am a mathematician, and mathematicians like to count complicated things, even different infinities. This is what drew me to the problem: There are trillions of immune cells circulating in our blood, deployed in various organs, and they are manufactured and mature in different organs, and they communicate with one another in a complex way. To cope with this complexity, we need to find ways to measure the immune system with higher content and resolution. Leveraging what is called "single-cell multi-omics sequencing" is a non-trivial undertaking. Still, it allows us to map the human immune system, little by little, and to mine our data for novel and essential therapeutic and clinical insights.
Can you give examples of such insights?
One such example is the discovery of the gene BTG1 as a potential modifier of NKT (Natural Killer T) cells that can enhance the cell therapy anti-tumor activity. We have also identified the optimal dose for a drug in a clinical trial setup and the optimal combination agent for the clinical arm. We have already demonstrated these two examples with our pharma partners via our clinical trial operating system (CT-OS product). Another one of our products is the preclinical development operating system (PD-OS product) which evaluates and predicts the clinical features of drug candidates in the preclinical development phase. An example is using the PD-OS to identify potential toxicity in bispecific engagers or other therapeutics more likely to have safety issues. The PD-OS product is still in development, and we already have pilots with pharmaceutical companies partnering with us as design partners. Through these partnerships, our products evolve.
So your business model is to work with pharmaceutical companies and help them develop their drugs?
Our platform and CT-OS and PD-OS products are being developed through our many partnerships. We work with academic institutions, hospitals, biotechnology, and biopharma companies. Today we work with five of the top 15 pharma companies, and through our partnerships, we leverage our platform capabilities to address the main challenges and unmet needs of the drug development process.
Are they concerned you will compete with them or work with their competitors on their data?
As part of our business development process, we explain our business model to our current and prospective partners: Immunai's business supports biotech and pharmaceutical companies' preclinical and clinical development. We work with our partners and maintain the privacy of their know-how and IP. In some instances, if exclusivity is needed, we support it for the correct commercial terms. The important thing is that we learned how to work with pharmaceutical companies in a sustainable and scalable way.
What do you hope that will happen in the next two years?
We keep growing Immunai and strengthening the platform. We curate and ingest more data into AMICA, and we will likely triple it over the next two years. We will keep professionalizing our products, CT-OS and PD-OS, through our partnerships, and we will publish success stories in the professional literature to improve patient outcomes.
Are you worried about the financial markets?
A good CEO is always worried. However, two aspects reassure me we're on the right path. First, we were fortunate enough to raise substantial financing that can last for another four years from now, which positions us in a comfortable position to build our platform, even if the financial markets will continue to be challenging. Second, our business model allows us to reduce our burn rate and extend our runway. This reduces our dependency on the financial markets and the economic sentiment, and we keep building our platform despite the challenging circumstances.
But beyond that, the financial markets would not change the fact that sick people still need treatments and therapies. In oncology, for example, a drug candidate going to clinical trials has a lower than 10% chance of success in getting FDA approval. Suppose that our platform can help increase this number. In that case, it will be suitable for the patients and good for the pharmaceutical companies, which is true independently of the financial climate.