a16z Podcast: Breaking Into Bio
The a16z Show
a16z
4.2 • 1.2K Ratings
🗓️ 2 May 2018
⏱️ 42 minutes
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| 0:00.0 | The content here is for informational purposes only, should not be taken as legal business, tax, |
| 0:05.6 | or investment advice, or be used to evaluate any investment or security, and is not directed |
| 0:10.3 | at any investors or potential investors in any A16Z fund. For more details, please see A16Z.com |
| 0:16.8 | slash disclosures. |
| 0:18.7 | Hi, and welcome to the A16C podcast. Whether you're an academic seeking to move out of research |
| 0:24.3 | and into industry or simply interested in working at a bio startup, this episode of the podcast is for |
| 0:30.1 | you, from how to build a brand in the space when you don't have one, to identifying what the |
| 0:34.7 | problems that really need solving are and how to build a company around it. |
| 0:39.1 | This episode of the podcast is based on an event held at Andreessen Horowitz with Atul Butte, |
| 0:43.6 | a distinguished professor and director of the Institute for Computational Health Sciences at UCSF, |
| 0:49.1 | Daphne Kohler, founder and CEO of InCitro, formerly professor at Stanford and co-founder of Coursera, |
| 0:55.7 | and is moderated by A16Z Bio-General partner, Vijay Ponday. |
| 1:00.5 | So first I want to talk about, for those thinking about founding your own startup, |
| 1:04.7 | you know, how do you connect the dots from going from academia to a company? |
| 1:08.0 | A lot of times people have really amazingly interesting technology, but there's this big gap between technology to a company. A lot of times people have really amazingly interesting technology, |
| 1:12.6 | but there's this big gap between technology to a product and product to a company. What criteria |
| 1:17.0 | would you be advising people to look at to say, you know, this is something where I really |
| 1:20.7 | think I should turn into a startup. How do you reach that bar? So it's tempting to start |
| 1:24.7 | companies, right? The thing is, though, that especially in bio and medicine, we see so many superficial |
| 1:29.4 | companies. |
| 1:30.2 | One of the harder things, compared to just generic machine learning, AI types of platform |
| 1:34.6 | companies, in this field, you have to go deeper. |
... |
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