Journal Club: Finding New Antibiotics with Machine Learning, What Coronavirus Structures Tell Us
The a16z Show26 Apr 2020

Journal Club: Finding New Antibiotics with Machine Learning, What Coronavirus Structures Tell Us

a16z Journal Club (part of the a16z Podcast), curates and covers recent advances from the scientific literature -- what papers we’re reading, and why they matter from our perspective at the intersection of biology & technology (for bio journal club). This inaugural episode covers 2 different topics, in discussion with Lauren Richardson:

0:26 #1 identifying new antibiotics through a novel machine-learning based approach -- a16z general partner Vijay Pande and bio deal partner Andy Tran discuss the business of pharma; the specific methods/ how it works; and other applications for deep learning in drug discovery and development based on this paper:

  • "A Deep Learning Approach to Antibiotic Discovery" in Cell (February 2020), by Jonathan Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina Donghia, Craig MacNair, Shawn French, Lindsey Carfrae, Zohar Bloom-Ackermann, Victoria Tran, Anush Chiappino-Pepe, Ahmed Badran, Ian Andrews, Emma Chory, George Church, Eric Brown, Tommi Jaakkola, Regina Barzilay, James Collins

11:43 #2 characterizing the novel coronavirus causing the COVID-19 pandemic -- a16z bio deal partner Judy Savitskaya shares what we can learn from the protein structures; the relationship to the 2002-2004 SARS epidemic; and more based on these two research articles:

You can find these episodes at a16z.com/journalclub.

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.


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