Episode Summary
Executive Summary: The episode introduces DeSci (decentralized science) as a crypto-enabled rework of scientific coordination: open data, better attribution, reproducibility, and new funding models. Boris Dayakov and Mikey Fisher argue blockchain can reduce friction in publishing, data provenance, and collaboration, while Alok Tai explains Vibe Bio’s model for financing neglected diseases via community-driven capital allocation and future DAO governance.
Main Topics: What DeSci is and why it matters (Priority: 5/5): DeSci is framed as using blockchain and DAO structures to improve scientific institutions, making science more open, permissionless, and incentive-aligned like open-source software and DeFi. Science’s structural problems (Priority: 5/5): Guests describe traditional science as slow, permissioned, gatekept, and often inefficient in funding, publication, and reproducibility, with academia and industry misaligned around incentives. Funding and capital allocation for science (Priority: 5/5): A major DeSci use case is financing research that falls outside mainstream incentives, including biotech IP, clinical-trial financing, and long-tail disease projects through DAOs and novel capital structures. Publishing, attribution, and reproducibility (Priority: 4/5): Blockchain is presented as a way to track who contributed what, preserve provenance, improve reproducibility, and move beyond PDF-based publishing and citation chains. BioDAOs and the VitaDAO/Molecule model (Priority: 4/5): The conversation highlights VitaDAO and Molecule as early templates for DeSci DAOs focused on longevity and translational biotech, inspiring a wider wave of science-focused DAOs. Vibe Bio and inflection-point financing (Priority: 5/5): Alok Tai explains Vibe Bio’s model for funding under-supported drugs at critical inflection points so promising medicines can generate data, attract follow-on capital, and eventually return value to the community. AI, automation, and the future of scientific work (Priority: 3/5): The speakers see AI as a force multiplier for DeSci, potentially accelerating literature review, experiment planning, reproducibility, and scientific mentorship.
Key Arguments: DeSci builds on open science but adds incentive mechanisms, ownership, and coordination tools that open science alone lacked. Blockchain is useful in science not because of money, but because it enables immutable records, provenance, attribution, and trustless collaboration. Traditional science is too permissioned; DeSci lowers barriers so people can contribute based on data and merit rather than institutional status. Scientific contributions are often poorly credited; DeSci could allow partial ownership, rewards, or airdrops for contributors to datasets and discoveries. Publishing in traditional science is inefficient and extractive: researchers often pay to publish, review for free, and then pay again to read. The long tail of diseases is ignored because funding follows expected commercial upside, not unmet need; patient communities can correct this through DAOs and pooled capital. Vibe Bio’s model is to fund medicines at the hardest point in development—the inflection point—so promising treatments can generate pivotal data and unlock more capital. Patient communities should have a voice in prioritization and capital allocation because they are the ones most affected by neglected diseases. AI may further accelerate DeSci by automating literature review, suggesting experiments, and improving knowledge graphs and reproducibility workflows. DeSci may not replace traditional science immediately, but it can become parallel infrastructure that eventually makes science more decentralized by default.
Data Points: PhD timeline for publishing: 2 to 3 years - Mikey described how long it can take to go from funding to research, peer review, and publication in traditional science. DBDAO model: Fractionalizes large data sets - Mikey said his company incentivizes people to contribute data and share rewards from data sales. Open science age: Around 20 years - Boris noted open science has existed for decades but hasn’t fully transformed the system. Academic publishing margins: Highest margins of any industry - Boris argued that academic publishing is unusually profitable because researchers pay to publish and institutions pay to access papers. Pharmaceutical R&D spending: $80 billion to $100 billion per year - Alok cited annual R&D spending in pharma as a sign of the scale and opportunity for better capital allocation. Overall pharmaceutical investment: $1.2 trillion per year - Alok referenced total annual investment in pharmaceuticals while discussing the size of the market. Rare disease count: 13,000+ diseases - Alok used this to explain how the industry focuses on only a small subset of conditions. Vibe Bio team size: About 9 people - Alok described the organization as a small team split across community/marketing, drug development, and software/engineering. Vibe Bio founding year: 2022 - Alok said the organization was founded after his daughter’s illness highlighted the funding gap. Vibe Bio launch timing: About 9 months ago - Alok noted the company had been operating for roughly nine months at the time of the interview. Potential financing per project: Hundreds of thousands to $1–2 million - Alok described the scale of capital needed to get promising medicines to pivotal data. Cystic fibrosis early patient count: A few thousand patients - Alok used CF to show how underdiagnosis and lack of treatment can make a disease appear smaller than it is. CF patient population growth: Roughly 10x - Alok said awareness and diagnosis expanded after treatments emerged. Vertex market cap: $80 billion - Alok cited Vertex as a major financial outcome from cystic fibrosis drug development. Vertex revenue: About $7 billion annually - Alok referenced Vertex’s top-line revenue in the context of CF-focused drug success. United Therapeutics revenue: Over $1 billion top line - Alok used it as another example of a successful disease-focused biotech. DeSci NYC meetup cadence: Monthly - Mikey mentioned DeSci NYC as an active recurring community hub.
Pivotal Quotes: "DeSci is using blockchain technology to improve the systems and institutions of science and like create new incentives for science." — Boris Dayakov: Core definition of DeSci offered during the opening discussion. "Science is supposed to be a marketplace of ideas and competition... but in a lot of ways, it isn't." — Alok Tai: Explaining why decentralized coordination could restore scientific incentives. "It's like GitHub for science." — Mikey Fisher: Bull case for a future where scientific data, collaboration, and reproduction are as easy as software workflows.
Implications: The episode suggests DeSci could become core infrastructure for biotech, publishing, and research funding, especially for neglected problems. For listeners, it reframes crypto as coordination tech for real-world discovery, not just speculation.