28: Artificial Intelligence, Synthetic Biology, Machine Learning, and A.I. Development Biotechnology Startup Discussion with LabGenius Founder and CEO Dr. James Field

May 8, 2018

Podcast: Play in new window | Download (Duration: 45:13 — 26.4MB) | Embed

Subscribe: Apple Podcasts | Spotify | Amazon Music | Android | Pandora | iHeartRadio | Podcast Index | TuneIn | RSS | More

A.I. , Synthetic Biology, Discovering Protein compounds, LabGenius, and Developing EVA an AI Evolution Engine for Discovering Protein Components.

James and I talked about his inspiration, the key points that changed his life, how he developed the company, how to best make use of your team, how to notice and find the right type of investors, and much, much more. James is the CEO and founder of LabGenius where he combines A.I. with synthetic biology in a unique and interesting way. We get into all of this in the podcast.

What LabGenius has built

“LabGenius has developed EVA – an autonomous AI-driven evolution engine for the discovery of high-value protein components. The company uses its platform technology to develop new products in partnership with world-leading multinationals. LabGenius is based in Central London and run by a passionate team of synthetic biologists, data scientists and engineers. ” Source

About James

“James completed his EPSRC-funded PhD at Imperial College London where he developed a platform for targeted drug delivery using re-engineered protein nanocages. Prior to his PhD, James completed a BS in Biology with Microbiology (1st Class) and an MRes in Systems and Synthetic Biology (Distinction), at Imperial College London.

James is an active member of the synthetic biology community having participated in the iGEM competition both as an undergraduate (2009), advisor (2011) and judge (2016).

In 2017, James was awarded the BBSRC Innovator of the Year award for early career impact. In 2018, James was featured on Forbes’ 30 Under 30 list for Science & Healthcare. James is also a fellow of the prestigious Synthetic Biology Leadership Excellence Accelerator Program (LEAP).

Outside of work, James enjoys time with his daughter, reading science fiction, and drinking loose leaf Earl Grey tea.” Source

Hyperlinked Timestamped Show Notes (only clickable on this website):

  1. [ 02:00 ] How he handles being told no, and how he thinks about achieving his objective.
  2. [ 03:00 ] What made him interested in Synthetic and Protein engineering (i.e. Beauty of the world and complex solutions).
  3. [ 04:00 ] His thoughts on crisper and crisper-like technology, and its limited use.
  4. [ 04:35 ] How IGEM was really critical in his career, and a little bit of his background.
  5. [ 05:30 ] How IGEM changed his trajectory, and where he was going before IGEM.
  6. [ 08:15 ] What about himself was critical to his success.
  7. [ 10:30 ] Describing his startup and the way he thinks about LabGenius, A.I., and Protein engineering.
  8. [ 12:00 ] How people and his team come into the equation with EVA.
  9. [ 12:40 ] The first problem he tried solving with this technology.
  10. [ 14:15 ] Where he gets all of the data to feed his A.I. tech.
  11. [ 14:50 ] A simple analogy on how the system works.
  12. [ 16:50 ] The many industries that he thinks it would be used in very successfully, and the challenges that stop widespread use.
  13. [ 19:10 ] His thoughts on an upper limit of what we can understand, and what part he thinks A.I. will play. He spreads the germ.
  14. [ 22:30 ] Narrow A.I. and general A.I.
  15. [ 24:05 ] How LabGenius has changed and stayed the same as he developed it. The mistakes he made, the lessons he has learned in building a deep tech company and using PhD people correctly, and commercialization.
  16. [ 26:00 ] How deep tech is different from other companies.
  17. [ 27:15 ] His thoughts on the deep tech time range and how to think about revenue.
  18. [ 29:25 ] How financing affected his company and how he thinks about finding the right people.
  19. [ 30:15 ] The three different types of investors.
  20. [ 32:45 ] How to find the right type of investor.
  21. [ 35:35 ] How science doesn’t know borders, and how deep tech investors share this view.
  22. [ 36:15 ] Some of the things the investors have mentored him in.
  23. [ 37:45 ] The value of looking at investors as people versus just money bags.
  24. [ 39:30 ] How he would advise people to think and reflect so as to make the most of who they are.
  25. [ 40:20 ] Where his company is going next.
  26. [ 41:20 ] How to follow along and an open invitation to communicate.
  27. [ 42:10 ] Listener question: What are his thoughts on bio hackers and the change in available technology?

Comments are closed.

Categories