← AI drug discovery

What podcasts say about AI drug discovery

Every statement, with the speaker, the exact quote and the moment it was said.

What experts have said about AI drug discovery

11 statements · 9 positive · 2 mixed

  1. AI will reduce drug-discovery failures and lower development costs to $600–700 million.

    “the AI is going to reduce the number of failures. And is going to cut the cost to launch, develop, discover, develop a new drug from $2.4 billion, including failures, to $600 to $700 million.”

    Listen at 10:28

    Open the episode · We Gave Away $2,000,000 To 5 AI Builders | MOONSHOTS Live
  2. AI will reduce new-drug development time from 13 years to eight years or fewer.

    “And the time is going to drop from 13 years to 8 years or fewer”

    Listen at 10:45

    Open the episode · We Gave Away $2,000,000 To 5 AI Builders | MOONSHOTS Live
  3. Advanced AI may accelerate drug discovery and disease treatment.

    “We might actually speed up the pace of drug discovery, of solving diseases.”

    Listen at 1:38:40

    Open the episode · AI Debate Ed Zitron, Andrew McAfee, Nate Soares, Roman Yampolskiy
  4. AI can raise ten-year drug-development success probability from 1% to about 75%.

    “I take that candidate and now I've got a probability of success in 10 years that instead of being 1% is now like 75%.”

    Listen at 1:44:11

    Open the episode · David Friedberg: The US Empire Is Declining And Socialism Is Coming Next!
  5. Several AI-discovered drugs will generate more revenue than the legacy economy.

    “If it comes up with five or 10 more drug discoveries, which it inevitably will, very soon, the amount of revenue flowing back into the AI economy from just that will dwarf the legacy world.”

    Listen at 21:07

    Open the episode · NVIDIA's $96.2B Quarter, China's 200,000 Fake Accounts, & OpenAI's New Chip | EP #284
  6. AI-driven structural biology and virtual-cell models will produce new cancer-drug targets.

    “I would expect lots of new targets, lots of new approaches to emerge from both the AlphaFold3 style of protein folding problem and structural biology being solved, as well as virtual cell models”

    Listen at 1:58:50

    Open the episode · NVIDIA's $96.2B Quarter, China's 200,000 Fake Accounts, & OpenAI's New Chip | EP #284
  7. David SinclairPositiveAug 24, 2026· Modern Wisdom

    AI enables individuals to discover drug candidates using a phone

    “almost somebody on their phone can discover a drug candidate”

    Listen at 1:49:56

    Open the episode · “Age Reversal Is Coming.” Inside The First Human Trials - Dr David Sinclair - #1141
  8. David SinclairPositiveAug 24, 2026· Modern Wisdom

    AI can model cells and perform molecular in-silico experiments at trillion-compound scale

    “An artificial AI version of a cell we can do in silico experiments at the molecular level now and dock trillions”

    Listen at 1:50:50

    Open the episode · “Age Reversal Is Coming.” Inside The First Human Trials - Dr David Sinclair - #1141
  9. AI-enabled drug discovery and genomic analysis will produce major breakthroughs.

    “There is some incredible breakthroughs coming.”

    Listen at 8:03

    Open the episode · Moderna’s skin cancer breakthrough, a cheap stock for the Community Portfolio & can you time your investments?
  10. AI generates drug candidates faster than current funding and testing can evaluate them.

    “AI because it's spitting out new drug candidates all the time that we can't test. It takes years to get through. So with money, we could do a lot more trials and put these through different diseases much faster”

    Listen at 2:11:21

    Open the episode · #2537 - David Sinclair
  11. Dario AmodeiMixedFeb 13, 2026· Dwarkesh Podcast

    AI drug discovery will accelerate faster than existing regulatory pipelines can process.

    “AI models are going to greatly accelerate the rate at which we discover drugs. And just the pipeline will get jammed up”

    Listen at 1:42:38

    Open the episode · Dario Amodei — The highest-stakes financial model in history

Statements are attributed to the speaker as said on the episode and reflect their view at the time, not PodLume's. They are not advice.