Immunai is a biotech company using machine learning algorithms that combine single-cell genomics to empower the human immune system’s high-resolution profiling. Based out of New York, this company was established merely three years ago, but it is growing at a breakneck pace with the largest dataset in the world for single-cell immunity characteristics. Recently, the startup managed to raise a whopping $60 million in Series A funding. The total number of funds raised now stands at $80 million. With its machine learning algorithms, Immunai has already powered the existing immunotherapies with an enhanced performance level by bettering the analysis of an individual’s immunity. It is now ready for a new dawn. With the help of the new funding received, Immunai will delve into the arena of creating new therapies altogether with the help of its vast expanse of data and advanced machine learning algorithms.
The human immune system has been a highly researched topic, and with the onset of the pandemic, the reprogramming of immunity has been under the limelight. To get an in-depth analysis of the same, Immunai makes use of the multiomic approach which helps in the layering analysis of the various types of biological data available. What makes Immunai stand out from the crowd is that it uses and combines the richest data sets. These data sets are procured from the best immunological research organizations from across the globe with machine learning algorithms designed to deliver analytics at a never seen before pace.
Immunai has two great co-founders in its ambit: Noan Solomon and Luis Voloch. Both the founders have extreme knowledge in computer science as well as artificial intelligence. Their efforts right from the beginning were aligned towards the usage of machine learning technology in the field of immunology.
Prior to the funding, the main job being done at Immunai was the observation of cells. In contrast, now, they will observe the cells and perturb them to see the aftermath. The machine learning algorithms being used at Immunai allow them to evaluate an approach practically. This makes their model more feasible and influential in the real world.
After successfully understanding the human immune profile, the next step will be to administer new drugs to help fight potential diseases. To understand it better, we can take the example of Google Maps, wherein initially, it takes years to understand the road mapping solely. Similarly, as of now, Immunai is working on understanding the different pathways present in the immune system with the help of machine learning. Once done, the roads and paths underdeveloped or those that haven’t been built can be given a lending hand. This will eventually lead to a healthier world more armed to fight any disease, even like the pandemic that we are faced with within the current scenario.
One major milestone that any immunotherapy needs to achieve is finding the right immunotherapy for the right patient. This poses a herculean task given the complex structure of the human immune system, but with the advancement of the machine learning models, one can expect to overcome this roadblock soon.