Today’s guest believes that decoding the immune system is at the heart of improving drug efficacy. He is currently focused on this effort as the CEO and Co-founder of Immunai – a company that is building an AI model of the immune system to facilitate the development of next-generation immunomodulatory therapeutics. Noam Solomon begins our conversation by detailing his professional history and how it led to Immunai before explaining what Immunai does and why this work is vital for healthcare. Then, we discover how understanding the immune system will help to improve how drugs work in our bodies, how the team at Immunai accomplishes its goals, the major challenges of working with complex ML models, and some helpful recommendations for processing the high-dimensional nature of biological data. Noam also explains the collaborative landscape of Immunai, how the evolution of technology made his work possible, Immunai’s plans for the future, and his advice to others on a similar career path.

Key Points:

• Unpacking Noam Solomon’s professional journey that led to his founding of Immunai.
• What Immunai does and why this work is vital for the healthcare industry.
• How understanding the immune system will help to improve drug efficacy.
• Exploring how Noam and his team use AI to accomplish their goals.
• The standardization of data and other challenges of working with complex ML models.
• Techniques for handling the high-dimensional nature of biological data.
• How ML experts collaborate with other domains to inform and build Immunai’s models.
• The technical advancements that have made Noam’s work possible.
• His advice to other leaders of AI-powered startups, and imagining the future of Immunai.
• How to connect with Noam and his work.

Quotes:

“First, let’s talk about the problem, which is today, getting a drug from IND approval to FDA approval—which is the process of doing clinical trials—has less than a 10% chance of success, usually about a 5% chance, takes more than 10 years, and more than $2 billion of open immune therapy.” — Noam Solomon

“Different people respond differently to the same drug, and the reason they respond differently is because their immune system is different.” — Noam Solomon

“You first need to fall in love with the problems. Many ML people—physicists, mathematicians, computer scientists—we love building models; we love solving puzzles. In biology, you need to really fall in love with the question you are trying to answer.” — Noam Solomon

“It’s a great decade for biology.” — Noam Solomon

Links:

Noam Solomon on LinkedIn

Noam Solomon on X

Immunai

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