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Until very recently, the study of human disease involved looking at big things \\u2014 like organs or macroscopic systems \\u2014 and figuring out when and how they can stop working properly. But that\\u2019s all started to change: in recent decades, new techniques have allowed us to look at disease in a much more detailed way, by examining the behaviour and characteristics of single cells.

One class of those techniques now known as single-cell genomics \\u2014 the study of gene expression and function at the level of single cells. Single-cell genomics is creating new, high-dimensional datasets consisting of tens of millions of cells whose gene expression profiles and other characteristics have been painstakingly measured. And these datasets are opening up exciting new opportunities for AI-powered drug discovery \\u2014 opportunities that startups are now starting to tackle head-on.

Joining me for today\\u2019s episode is Tali Raveh, Senior Director of Computational Biology at Immunai, a startup that\\u2019s using single-cell level data to perform high resolution profiling of the immune system at industrial scale. Tali joined me to talk about what makes the immune system such an exciting frontier for modern medicine, and how single-cell data and AI might be poised to generate unprecedented breakthroughs in disease treatment on this episode of the TDS podcast.

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Intro music:

\\u279e Artist: Ron Gelinas

\\u279e Track Title: Daybreak Chill Blend (original mix)

\\u279e Link to Track: https://youtu.be/d8Y2sKIgFWc

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Chapters:

0:00 Intro

2:00 Tali\\u2019s background

4:00 Immune systems and modern medicine

14:40 Data collection technology

19:00 Exposing cells to different drugs

24:00 Labeled and unlabelled data

27:30 Dataset status

31:30 Recent algorithmic advances

36:00 Cancer and immunology

40:00 The next few years

41:30 Wrap-up