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Sisällön tarjoaa Sonal Chokshi and Andreessen Horowitz. Sonal Chokshi and Andreessen Horowitz tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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mRNA for Flu Vaccine? AI Protein-Folding Goes Open Source

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Manage episode 299015313 series 2544228
Sisällön tarjoaa Sonal Chokshi and Andreessen Horowitz. Sonal Chokshi and Andreessen Horowitz tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
In today’s episode we have two short segments, both on bioscience topics: [0:00] Moderna has started clinical trials for a flu vaccine, called mRNA-1010, that is based on the same mRNA technology that Moderna and Pfizer used for their COVID vaccines, and that several other companies including Sanofi and Glaxo all are actively working on for the influenza use case. Our experts are general partners Vineeta Agarwala and Jorge Conde of the a16z bio team, who have joined us on many of our vaccine-related episodes, which you can find at a16z.com/vaccines. They discuss what comes next for the clinical trials of this mRNA-based flu vaccines, why companies aren't planning to use the faster and more-targeted mRNA technology for COVID's Delta variant, and how mRNA vaccines will change not only our approach to flu shots but to other respiratory viruses. [9:53] Google’s DeepMind AlphaFold, in partnership with the European Molecular Biology Laboratory, is publicly sharing its entire protein structure database -- with predicted protein structure models for ~20,000 proteins expressed by the human genome -- meaning that all its data will be freely and openly available to the scientific community. (We previously discussed DeepMind's AlphaFold protein-folding AI on this show in episode #48.) General partner Vijay Pande of the a16z bio team helps us answer the question: Why does it matter that a huge database of very accurate predicted protein structures is now freely available?
  continue reading

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Artwork
iconJaa
 
Manage episode 299015313 series 2544228
Sisällön tarjoaa Sonal Chokshi and Andreessen Horowitz. Sonal Chokshi and Andreessen Horowitz tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
In today’s episode we have two short segments, both on bioscience topics: [0:00] Moderna has started clinical trials for a flu vaccine, called mRNA-1010, that is based on the same mRNA technology that Moderna and Pfizer used for their COVID vaccines, and that several other companies including Sanofi and Glaxo all are actively working on for the influenza use case. Our experts are general partners Vineeta Agarwala and Jorge Conde of the a16z bio team, who have joined us on many of our vaccine-related episodes, which you can find at a16z.com/vaccines. They discuss what comes next for the clinical trials of this mRNA-based flu vaccines, why companies aren't planning to use the faster and more-targeted mRNA technology for COVID's Delta variant, and how mRNA vaccines will change not only our approach to flu shots but to other respiratory viruses. [9:53] Google’s DeepMind AlphaFold, in partnership with the European Molecular Biology Laboratory, is publicly sharing its entire protein structure database -- with predicted protein structure models for ~20,000 proteins expressed by the human genome -- meaning that all its data will be freely and openly available to the scientific community. (We previously discussed DeepMind's AlphaFold protein-folding AI on this show in episode #48.) General partner Vijay Pande of the a16z bio team helps us answer the question: Why does it matter that a huge database of very accurate predicted protein structures is now freely available?
  continue reading

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