Hello and welcome to the inaugural episode of the A16Z Journal Club.

I'm Lauren Richardson, one of our bio-editors, and in this episode we'll cover two topics.

First, a novel machine learning-based approach to identify new antibiotics.

And second, we'll discuss two articles characterizing the novel coronavirus causing the

current pandemic.

Journal Club will cover a variety of articles every few weeks, so stay tuned here and will announce its own feed soon.

First up is my conversation with A16Z general partner, VJ Ponde, and Deal partner on the Bio team, Andy Tran.

We dive into a deep learning approach

to antibiotic discovery by Jonathan Stokes,

Regina Barzley, James Collins, and colleagues.

In this article published in Cell, the authors create a novel

machine learning-based method to identify new antibiotic drugs from two large databases.

They then validated one of their candidates, a drug named Hallison, showing that it has excellent antibiotic properties, both in vitro and in two different mouse models of bacterial infection.

Excitingly, Hallison has a distinct structure and appears to have a distinct mechanism of

action from other antibiotics, which is important given the problem of antibiotic resistance

and the need to find new drugs. Our discussion of the paper covers the business of antibiotics,

the methods, and how deep learning can identify novel drug structures,

and other applications for deep learning in drug discovery and development.

But we begin with what made this paper appeal to us.

And the first voice you'll hear is VJs.

A huge tear away from this article was the breadth of experimental work that was done to demonstrate

the accuracy of the predictions involved. And so while there has been a lot of work about using

...