
About this episode
Robert Langer is a professor at MIT and one of the most cited researchers in history, specializing in biotechnology fields of drug delivery systems and tissue engineering. He has bridged theory and practice by being a key member and driving force in launching many successful biotech companies out of MIT. Support this podcast by supporting these sponsors: – MasterClass: https://masterclass.com/lex – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter https://twitter.com/lexfridman, LinkedIn https://www.linkedin.com/in/lexfridman/, Facebook https://www.facebook.com/lexfridman, Medium https://medium.com/@lexfridman, or YouTube https://www.youtube.com/lexfridman where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584, follow on Spotify https://open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL, or support it on Patreon https://www.patreon.com/lexfridman. Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 – Introduction 03:07 – Magic and science 05:34 – Memorable rejection 08:35 – How to come up with big ideas in science 13:27 – How to make a new drug 22:38 – Drug delivery 28:22 – Tissue engineering 35:22 – Beautiful idea in bioengineering 38:16 – Patenting process 42:21 – What does it take to build a successful startup? 46:18 – Mentoring students 50:54 – Funding 58:08 – Cookies 59:41 – What are you most proud of?
Transcript
10,646 words · 2 speakers
Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.
Page updated · transcript and summary are machine-generated