Snapshot · The Prof G Pod with Scott Galloway
David Ricks estimates that humans have discovered only 10–20% of all knowledge about the human body system, making AI-driven drug discovery extremely difficult today.
Where this was said
At 38:30 · chapter starts 36:55
Jensen Huang's vision of AI as the engine of a 'great age of discovery' in biotech gets a reality check from the CEO of the world's most valuable pharma company. Ricks is not dismissive — Lilly scientists use OpenAI and Anthropic tools daily and he's working with NVIDIA to build better biological datasets. But he draws a sharp distinction: LLMs excel at synthesizing the totality of human written knowledge, and they're good at it because that knowledge base is nearly complete. Biology isn't. Humans have mapped perhaps 10–20% of how the human body actually works, which means training an AI on it produces models that are 'terrible at predicting' outcomes in the remaining 80%. The second limitation: drug discovery ultimately requires physical experimentation. Tirzepatide was the 700th formulation tested — and the 20 of roughly 1,000 preclinical steps that Lilly has automated with AI or machine learning still leave 980 to go. The human experimentation phase — clinical trials — can't be shortcut by AI for the foreseeable future. His estimate: five to seven years before AI meaningfully reduces laboratory experiments, and a full ten-year arc before it genuinely accelerates drug discovery at scale.
AI excels at synthesizing existing knowledge, but drug discovery requires creating new knowledge. Humans have mapped only 10–20% of human biology, so AI models trained on that incomplete dataset produce poor predictions. Meaningful AI acceleration in pharma R&D is a 10-year arc, not a 2-year one.
Tirzepatide, the active ingredient in Mounjaro and Zepbound, was physically the 700th version of a GLP-1 inhibitor Lilly formulated and tested.
David Ricks estimates meaningful AI-driven acceleration of drug discovery is roughly a decade away, not the 2–3 years many tech boosters claim.
The widely cited ego-depletion model — the idea that willpower is a finite resource that gets depleted — failed to replicate in follow-up studies.
Humans are estimated to have 5,000–7,000 thoughts per day, yet can recall essentially none of them afterward, highlighting why in-the-moment emotional tracking matters.
A large Harvard study found that a wandering mind is an unhappy mind — people report greater happiness when their attention is tethered to the present, even if the task is unpleasant.
A key study finding that we have a 'credit card's worth of plastic' in our bodies was likely skewed because researchers used nitrile gloves that shed plastic particles onto the microplastic detector.
Emotionally sensitive people have a hyperactive amygdala, an underactive prefrontal cortex, and a frayed connection between the two — making emotional regulation structurally harder.
Rejection sensitivity can be observed as early as age 2 or 3, suggesting it has strong developmental and likely genetic roots.
A Yale study found that non-judgmental observation of emotions — without rushing to resolve them — reduces activation in the brain, making it a powerful regulation tool.
Dan Gilbert's research found that the psychological immune system — the brain's ability to justify and find satisfaction in choices — activates most powerfully when a decision is perceived as irreversible.
Barry Schwartz's research found that maximizers — people who try to optimize every decision — tend to achieve objectively better outcomes but report lower happiness than satisficers who choose 'good enough.'
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