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Jacob Kimmel thinks he can find the transcription factors to reverse aging. We do a deep dive on why this might be plausible and why evolution hasn’t optimized for longevity. We also talk about why drug discovery has been getting exponentially harder, and what a new platform for biological understanding to speed up progress would look like. As a bonus, we get into the nitty gritty of gene delivery and Jacob’s controversial takes on CAR-T cells. For full disclosure, I am an angel investor in NewLimit. This did not impact my decision to interview Jacob, nor the questions I asked him.
Watch on YouTube; listen on Apple Podcasts or Spotify.
SPONSORS
* Hudson River Trading uses deep learning to tackle one of the world's most complex systems: global capital allocation. They have a massive in-house GPU cluster, and they’re constantly adding new racks of B200s to ensure their researchers are never constrained by compute. Explore opportunities at hudsonrivertrading.com/dwarkesh\
* Google’s Gemini CLI turns ideas into working applications FAST, no coding required. It built a complete podcast post-production tool in 10 minutes, including fully functional backend logic, and the entire build used less than 10% of Gemini’s session context. Check it out on Github now!
* To sponsor a future episode, visit dwarkesh.com/advertise.
TIMESTAMPS
(00:00:00) – Three reasons evolution didn’t optimize for longevity
(00:12:07) – Why didn't humans evolve their own antibiotics?
(00:25:26) – De-aging cells via epigenetic reprogramming
(00:44:43) – Viral vectors and other delivery mechanisms
(01:06:22) – Synthetic transcription factors
(01:09:31) – Can virtual cells break Eroom’s Law?
(01:31:32) – Economic models for pharma
By Dwarkesh Patel4.6
475475 ratings
Jacob Kimmel thinks he can find the transcription factors to reverse aging. We do a deep dive on why this might be plausible and why evolution hasn’t optimized for longevity. We also talk about why drug discovery has been getting exponentially harder, and what a new platform for biological understanding to speed up progress would look like. As a bonus, we get into the nitty gritty of gene delivery and Jacob’s controversial takes on CAR-T cells. For full disclosure, I am an angel investor in NewLimit. This did not impact my decision to interview Jacob, nor the questions I asked him.
Watch on YouTube; listen on Apple Podcasts or Spotify.
SPONSORS
* Hudson River Trading uses deep learning to tackle one of the world's most complex systems: global capital allocation. They have a massive in-house GPU cluster, and they’re constantly adding new racks of B200s to ensure their researchers are never constrained by compute. Explore opportunities at hudsonrivertrading.com/dwarkesh\
* Google’s Gemini CLI turns ideas into working applications FAST, no coding required. It built a complete podcast post-production tool in 10 minutes, including fully functional backend logic, and the entire build used less than 10% of Gemini’s session context. Check it out on Github now!
* To sponsor a future episode, visit dwarkesh.com/advertise.
TIMESTAMPS
(00:00:00) – Three reasons evolution didn’t optimize for longevity
(00:12:07) – Why didn't humans evolve their own antibiotics?
(00:25:26) – De-aging cells via epigenetic reprogramming
(00:44:43) – Viral vectors and other delivery mechanisms
(01:06:22) – Synthetic transcription factors
(01:09:31) – Can virtual cells break Eroom’s Law?
(01:31:32) – Economic models for pharma

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