a16z 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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