From Models to Medicine

At KAMI Think Tank, we love cutting through the AI hype to showcase where the technology actually stands and how to use it meaningfully within the life sciences. Now, we're bringing that same clarity with our community to a brand new podcast: From Models to Medicine.Every week, we sit down with a real practitioner in the life sciences, whether they're working in the lab, leading innovation at a biotech, or building tools to better serve scientists. We discuss how they cut through the hype of AI and practically leverage the tool in their scientific workflows. Glad to have you here.

From Models to Medicine is a science podcast hosted by KAMI Think Tank, with 21 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

KAMI Think Tank hosts From Models to Medicine, a science show with 21 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  From Models to Medicine

  Episode 21: Glass Box Wins - What Pharma Actually Trusts in AI

  Aug 19, 202635 min

  In this episode of From Models to Medicine, we sit down with Lavanya Anandan , Head of External Innovation, West Coast at CSL, whose path from bench scientist to Merck Group platform builder to UCSF Innovation Venture startup advisor gives her a rare view of where AI in drug discovery is delivering versus where it's mostly promise. She makes a sharp case that the companies winning in AI-bio aren't necessarily the ones with the best models, and the reason why might surprise you. We get into what big pharma wants from an AI partner, why women's health data scarcity is quietly producing some of the most rigorous AI in biology, and what an unexpected finding in mRNA research tells us about where this whole field might be heading. Articles mentioned in show: https://endpoints.news/can-ai-do-scientific-research-billions-chase-hopes-of-superintelligence/ Maven course: https://maven.com/kamithinktank/ai-literacy-for-life-sciences-healthcare

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  From Models to Medicine

  Episode 20: The Build vs. Buy Question Every Pharma Leader is Wrestling With

  Aug 12, 202641 min

  We chat with Karl Moritz , CEO of Reliant AI, now part of Cohere, whose career took him from NLP research to McKinsey to building AI infrastructure for drug development. Karl reminds us that clinical trial success rates have been stuck years, and the golden age of AI-powered target discovery isn't fixing it. Karl lays out a sharp framework; own the science, rent the AI plumbing, and explains why building your own data ingestion pipeline is as misguided as writing your own operating system. He's also candid about what general-purpose LLMs are actually good for, where purpose-built enterprise tools earn their keep, and why the audit trail question will separate serious AI vendors from everyone else. If you're a pharma or biotech leader trying to make sense of the build vs. buy debate right now, this one is worth your time.

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  From Models to Medicine

  Episode 19: Flow Cytometry, Biomarkers, and the AI Patterns Nobody Is Verifying

  Aug 5, 202633 min

  For this episode, we sit down with Banishree Saha , Global Biomarkers Lead at Takeda, who has worked in fields such as academic liver biology to translational biomarker work, over the course of her 20-year career. She walks us through what biomarkers really are, how flow cytometry went from single-color panels to capturing 40 proteins simultaneously, and why that explosion in data has made systems thinking the only way forward. Banishree talks about AI's strengths and weaknesses, and makes the case that the scientists most at risk from AI aren't the ones who know too much biology. But are the ones who don't know enough to catch when the model is wrong.

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  From Models to Medicine

  Episode 18: Why Does mRNA Keep Breaking AI Models?

  Jul 29, 202640 min

  In this episode, we sit down with Chris Nelson , an mRNA scientist at nCode Bio whose career has taken him from building blood transfusion matching tests now used by the NHS, to cancer genomics at Personalis, to the frontier of mRNA sequence design. Chris breaks down why the untranslated regions of mRNA might actually change how we dose therapeutics, reduce side effects, and engineer cells inside the body entirely. Then we talk about why AI has conquered protein folding but keeps hitting a wall with mRNA. Chris walks us through the data problem, the cost problem, and the modeling choices nCode Bio is making that go against the grain of what most of the field is building. He's also candid about where the big model providers are letting biology down and which scrappy research groups he thinks are quietly building the tools that will actually matter.

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  From Models to Medicine

  Episode 17: Garbage Data, Toxic Exposure, and the AI Gap in Environmental Health

  Jul 22, 202641 min

  In this episode of From Models to Medicine, we sit down with Sarah Daniels , an environmental health researcher, who makes the argument that the chemicals making us sick might also be our best clues for building better drugs. She traces that idea from a 1976 discovery about dioxins all the way to an FDA-approved psoriasis treatment in 2023 — and asks what AI could accelerate if the field finally got its data act together. Sarah brings up where AI in environmental health is genuinely stuck; siloed industry data, models built only for acute toxicity, and a chronic low-dose problem that no one has cracked. She also shares how she used APIs to build her own real-time funding tracker for microplastics research in under a month, and why the gap between what AI promises and what environmental health can actually feed it is one of the most under appreciated bottlenecks in the field right now. Links mentioned in this episode: Historic ARPA-H program funding announcement on Microplastics: https://arpa-h.gov/explore-funding/programs/stomp Sarah's two cents on the ARPA-H Microplastics program: https://engineeredresilience.substack.com/p/a-microplastics-prelude-for-engineered Aggregated trends in microplastics from the non-peer-reviewed literature (Trendspotter App): https://www.engineeredresilience.org/microplastics Stay up to date on latest releases from Sarah's work on Engineered Resilience by signing up for substack: https://engineeredresilience.substack.com/ Report on unexpected health effects observed after LA fires showing how questions remain post-exposure to pollutants: https://www.latimes.com/environment/story/2025-12-17/la-fires-heart-attacks-strange-blood-test-results-spiked Can a Biologist Fix a Radio? - great piece on the necessity to understand biology at the systems-level: https://www.cell.com/cancer-cell/fulltext/S1535-6108(02)00133-2

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