📊 EV’s Charts of the Week #70

Hi, I’m Azeem Azhar. I convene Exponential View to help us understand how our societies and political economy will change under the force of rapidly accelerating technologies.

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Exponential darling
One of the exponential trends that still takes my breath away, even after I’ve seen it - and shown it - many times in the newsletter and my book, is the tremendous decline of the production cost of genome sequencing since 2001. As the cost per genome fell between 2001 and 2020, the speed of sequencing accelerated steadily throughout the 2000s.

Source: McKinsey

This powerful combination opened doors to new biology and health companies. Among them is Immunai, a startup founded by two machine learning experts who decided to use AI and new sequencing technologies to understand the human immune system better and develop the next generation of drugs. I spoke with one of the founders, Luis Voloch, on this week’s podcast. The conversation will be out later today, subscribe to the podcast feed to receive it as soon as it’s out. Inspired by our conversation, we dig into the fascinating short history of monoclonal antibody therapies.

Zooming in
Monoclonal antibodies (mAbs) is one type of immunotherapy that uses lab-produced antibodies to enhance, mimic or modify the immune system response. The first mAb product was approved in the US in 1986 for the prevention of kidney-transplant rejection. The first chimeric antibodies were approved in the 1990s – meaning, antibodies made up of different species.

Source: BioProcess International

FDA approves
mAb products have picked up the pace of adoption and development over the last decade: in 2021 alone accounting for nearly one fifth of the FDA’s new drug approvals. Empirical knowledge through trial and error is crucial in developing new therapies, and AI and big data have significantly improved this domain over the past several years.

Source: Nature 

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