AMICA maps human immune system with AI
Artificial intelligence is not just about generating text and other media. Believe it or not, it has more important functions in other industries.
Specifically, healthcare has been progressing significantly due to this technology. A New York-based healthcare tech firm is accelerating that development further with AMICA.
READ: The potential effects of AI healthcare
AI healthcare firm Immunai says it is “the world’s largest cell-level immune knowledge base,” which CEO Noam Solomon compares to having a “Google Map for our immune system.”
How does AMICA work?
We’re excited to be included on @CBInsights 130+ AI startups reinventing healthcare in the drug R&D category! With AMICA, the largest immunological database of its kind, we are poised to answer some of the most pressing questions in immunology to advance drug discovery. pic.twitter.com/9BVI1MrHBl
— Immunai (@Immunaitech) June 23, 2022
Medical technology firm Labiotech spoke with Immunai co-founder and CEO Noam Solomon to learn more about AMICA.
The acronym stands for “Annotated Multiomic Immune Cell Atlas.” Immunai started AMICA development with single-cell RNA sequencing.
Next, they measured the immune system’s cellular expression and function. Solomon explained the process further to MIT News:
“Then, we started working with pharmaceutical companies and hospitals to profile the immune systems of patients undergoing treatments to really get to the roots mechanisms of actions and resistance for therapeutics.”
These methods enabled Immunai to accumulate a vast amount of data that they turned into “a Google Map for the immune system.”
AMICA significantly improves drug discovery by informing an optimal dose and schedule, suggesting the right drug combinations, and determining whether someone should take a specific medicine.
Solomon told Labiotech biotech and pharmaceutical firms are moving away from drug discovery investments, opting for later-stage assets cleared in phases 1 and 2.
“I think that if this is going to continue, we’re going to see less innovation, and that’s not good for patients,” he explained.
“I hope that with platforms like Immunai, where we are aiming to improve the statistics, to improve the phase 1 success rate, to improve the phase 2 success rate, it will lead to better ROI.”
“Then, we’re going to see further investments in the early phases, because that’s very important to invest in innovation and to improve patients’ outcomes from the beginning.”
More importantly, Immunai wants a future where lab experiments yield impactful treatments for patients.
“Scientists can cure nearly every type of cancer, but only in mice,” the Immunai CEO explained to MIT.
“We’re demonstrating that our algorithms can repeatedly beat the top benchmarks in identifying the top preclinical immune features that match patient outcomes.”
