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a16z Podcast: Move Fast But Don't Break Things (When It Comes to Computational Biology)
The a16z Show

a16z Podcast: Move Fast But Don't Break Things (When It Comes to Computational Biology)

Andreessen Horowitz 29m 118 months ago
The a16z Show discusses tech and culture trends, news, and the future – especially as ‘software eats the world’. It features industry experts, business leaders, and other interesting thinkers and voices from around the world. This show is produced by Andreessen Horowitz (aka “a16z”), a Silicon Valley-based venture capital firm. Multiple episodes are released every week; visit a16z.com for more details and to sign up for our newsletters and other content as well!
The mindset of "move fast and break things", while great for code, isn't exactly great for the human body. So adding computation to biology -- especially in the slow-moving pharmaceutical industry, where drug approval can take years -- brings with it both opportunities (like drastically faster discovery and assessment) and challenges (the need for hard evidence, not just soft-ware). But there's more: We don't want just better outcomes for healthcare. We want better outcomes at a cheaper price. And that's where machine learning comes in. The benefits of such computation -- i.e., software -- can provide a powerful, frictionless, and far more cost-effective tool for biopharmaceutical research ... but it requires data. So who provides that data? Is it the pharmaceutical companies, or the payers (insurance)? How are organizations incented to overcome intellectual property silos in sharing their data? Especially since it was only relatively recently, Jeff Kindler (the former CEO of the world's largest pharmaceutical company, Pfizer) reminds us in this episode of the a16z Podcast, that the FDA even allowed data to be put in computers vs. on paper. But there's a reason the self-driving car was pushed out of the software and not the auto industry, argues TwoXAR co-founder and CEO Andrew Radin -- and it has to do with the unique nature of the developer's mindset applied to novel problems. The deterministic nature of Moore's Law -- it's not a matter of if, but when -- plays a role too, observes a16z bio fund general partner Vijay Pande. There are things that big data and simulations will be able to accomplish that a hundred lab experiments on animals can't. Still, the two mindsets will have to merge, so we can move fast ... but without compromising quality, safety, and reliability. That's the big difference between computer science and biology after all. image: mattza/ Flickr Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg 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. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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