AI transforms software development, creating trillions in value by shifting developers from coding to orchestrating AI agents and enabling rapid legacy code modernization.
AI's energy demands are overwhelming digital computing; analog architectures, mirroring biological efficiency, offer the only sustainable path to ubiquitous intelligence and AGI.
Asset price inflation and construction bottlenecks push homeownership out of reach, forcing fintech to innovate the entire housing funnel for generational wealth.
AI acts as a co-investigator, accelerating scientific discovery and reshaping economic growth by enhancing research, decision-making, and cross-disciplinary insights.
Big Tech finances AI infrastructure with a debt surge, sparking market stability fears, while quantum drones and "tech bio" unlock new frontiers, and crypto faces outflows.
"Where Are All the Trillion Dollar Biotechs" by Lada Nuzum - This post discusses the economic challenges and contradictions within the biotechnology industry.
"The Structure Between China and the United States" by Dan Wang - This book is referenced for its analysis of the relationship between China and the US, particularly in the context of technological and industrial states.
Articles & Papers
"The Biotech Paradox: Why the Business of Biotech is Collapsing While the Technology is Exploding" (Implied by episode discussion and guest's background) - This topic underpins the entire episode, discussing the disconnect between scientific advancement and economic struggles in biotech.
People Mentioned
George Yancopoulos (Co-founder of Regeneron) - Mentioned as a figure from biotech's early days, highlighting the historical cost of patient trials.
Dan Wang (China Analyst) - Quoted for his characterization of China as an "engineering state" and America as a "lawyer state" in the context of innovation.
Benjamin Franklin - Referenced as a founding father representing America's innovative spirit.
Leonard Shaffer (Co-founder of Regeneron) - Mentioned alongside George Yancopoulos as scientists defining the future of biotech.
Michael Fishbach (Stanford Scientist) - Discussed for his work on new modalities in biology and potential mechanisms for aging.
Irvin Weissman (Stanford Professor) - Cited as an example of a scientist whose new cancer targeting mechanism was quickly followed by Chinese biotech.
Carl June (Early Developer of CAR-T therapy) - Mentioned for his questioning of why investigator-initiated trials for cell and gene therapy are not more prevalent in the US.
Brian Johnson - Referenced for his "Blueprint" or "Don't Die" protocol related to personal health and longevity.
Organizations & Institutions
Regeneron - Mentioned as an early biotech company to highlight the historical cost of patient trials.
Amplify - The venture capital firm where Elliot Hershberg is a partner, focusing on platform companies.
FDA (Food and Drug Administration) - Discussed extensively regarding its role in drug development, regulation, and the potential for modernization.
Genentech - Used as a historical benchmark for early biotech success.
Amgen - Mentioned alongside Genentech as an example of early biotech success.
Human Genome Project - Referenced as a scientific endeavor that promised precision medicine.
CFDA (China Food and Drug Administration) - Discussed in the context of China's regulatory processes for drug development.
Moderna - Mentioned for its cancer vaccines, highlighting platform-based product development.
BioNTech - Mentioned alongside Moderna for its cancer vaccines.
Eli Lilly (Lily) - Discussed for its development of GLP-1 drugs, including semaglutide for Alzheimer's trials.
Novo Nordisk - Mentioned as a key player in the development of GLP-1 drugs.
Pfizer - Referenced for terminating its GLP-1 program due to perceived patient reluctance for chronic injectables.
Merck - Mentioned as an early pharmaceutical company that established vertically integrated research labs.
Novartis - Mentioned in the context of the development of Cosentyx, a TNF alpha antibody.
AbbVie - Mentioned in the context of Humira, a successful TNF alpha antibody.
Gilead Sciences - Mentioned in the context of Veklury (Remdesivir), a drug used for COVID-19.
Stanford University - Referenced as a source of scientific talent and innovation.
Medicare - Discussed as a primary payer for age-related diseases and its implications for incentivizing preventative care.
Courses & Educational Resources
a16z Podcast (YouTube, Apple Podcasts, Spotify, X @a16z, Substack a16zsubstack.com) - The podcast itself, with various platforms for further engagement.
Websites & Online Resources
a16z.com/disclosures - Provided for more details on investments and disclosures related to the podcast content.
Other Resources
GLP-1 drugs (e.g., Semaglutide, Rybelsus) - Discussed as a significant drug class with broad societal impact, potentially bending the curve on aging and chronic diseases.
CAR-T therapy - Mentioned as a type of cell and gene therapy.
CRISPR - Discussed as a gene-editing technology and its potential applications.
Recombinant DNA Technology - Highlighted as a foundational technology in biotech.
mRNA Vaccines - Cited as a transformative technology for vaccine development.
Monoclonal Antibodies - Discussed as a key therapeutic modality, particularly in cancer treatment.
Small Molecules - Referenced as a traditional therapeutic modality.
Epigenetic Editors - Mentioned as a potential future therapeutic modality for aging.
Gene Editors - Mentioned as a potential future therapeutic modality for aging.
Gene Therapies - Discussed as a potential future therapeutic modality for aging.
TNF alpha antibodies (e.g., Humira, Cosentyx) - Discussed as a class of drugs where being first to market wasn't the sole determinant of success.
PCKSK9 inhibitors - Mentioned as a class of drugs that could be included in an "aging stack."
SRNAs (Small interfering RNAs) - Mentioned as a potential preventative medicine.
Orphan Drug Act - Discussed for its role in incentivizing the development of drugs for rare diseases and the proposal for a similar incentive for common/age-related diseases.
Investigator-Initiated Trials (IITs) - Discussed in the context of regulatory processes in the US, China, Australia, and New Zealand.
Virtual Cells - Mentioned as a potential future application of AI in drug development.
In silico toxicity studies - Discussed as an area where AI is currently being applied in preclinical drug development.
Next-generation sequencing - Mentioned in the context of platform-based cancer vaccines.
RNA cancer vaccines - Discussed as a personalized therapeutic approach.
Sarcopenia - Discussed as a condition related to muscle loss in the elderly, with potential for drug development.
Caloric Restriction - Mentioned as a method to extend lifespan, with discussion on its effectiveness and application to human diets.
Lipitor - Cited as an example of a blockbuster drug from the "lipidator era."