Immunai is mapping the immune system at unprecedented scale and granularity. The map, paired with machine learning, looks at how the immune system will respond to drug targets, offering an affordable way to prevent expensive drug failures. 

The ultimate goal is to market immune treatments for diseases like cancer faster than ever before. 

In this week’s conversation, Noam Solomon, CEO and co-founder of Immunai, covers the data gap in drug discovery and how machine learning (ML) can solve it, how to de-risk early-stage drug discovery, predictions for AI, and more.

00:41-01:05: About Immunai
01:05-01:37: Why map the immune system?
01:37-02:36: Are you taking a step back to study the problem in order to move forward?
02:36-03:41: How difficult is it to map the immune system?
03:41-05:21: What is your AMICA platform?
05:21-07:16: Where does your data come from? 
07:16-09:01: How do you account for differences between patients?
09:01-11:27: What are the biggest challenges to drug development?
11:27-13:59: How can AI improve drug development?
13:59-14:47: Will AI advances speed up drug development?
14:47-15:58: Is the use of AI applicable in all diseases and conditions?
15:58-17:40: What sets your approach apart from other companies using AI?
17:40-18:46: What partnerships does Immunai have? 
18:46-20:16: What are pharma companies looking for from Immunai?
20:16-23:09: How can AI help with clinical trials?
23:09-24:24: Can AI help with preventative care?
24:24-26:22: Google Maps for the immune system
26:22-27:10: What will we see from AI in drug discovery in the short term? 
27:10-27:58: What are the next steps for Immunai?

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