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From Models to Medicine

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by KAMI Think Tank

15 episodes

Updated Daily

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Podcast Overview

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.

Language

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Publishing Since

3/13/2026

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Recent Episodes

June 24, 2026

Episode 14: The Drug Discovery Problems AI Alone Can't Solve

In this episode of From Models to Medicine, we speak with <a href="https://www.linkedin.com/in/vid-stojevic-32640314/" target="_blank" rel="noopener noreferer">Vid Stojevic</a>, the co-founder and CEO of Kuano, a Cambridge-based company using quantum algorithms and AI to tackle the drug discovery problems that traditional computational chemistry keeps failing. In this episode, he explains why he deliberately ignored the broad platform play and went narrow instead, targeting the specific early-stage problems where getting the physics right changes everything. We get into what a "quantum lens" actually means in practice, why transition states are a better design target than natural substrates, and how Kuano is succeeding on targets that pharma had written off as undruggable. Vid makes a sharp case for how generating synthetic quantum data turns a low-data drug discovery problem into something AI can actually work with. He closes with honest advice on when quantum simulation is the right tool and when it simply isn't.

June 17, 2026

Episode 13: The Microbiome is Messier Than You Think

<a href="https://www.linkedin.com/in/jennyyang259/" target="_blank" rel="noopener noreferer">Jenny Yang</a> is the co-founder and CEO of Outpost Bio, where her team is working to make human microbiology computable. In this episode, she breaks down why bias in ML models is so easy to miss. High overall accuracy can hide terrible performance on specific subgroups, and in healthcare, that gap has consequences. She traces the problem upstream, from skewed training datasets to the way clinical definitions themselves carry historical bias, and explains the real trade-offs involved in trying to correct for it.We also get into what makes the microbiome such a hard problem is that our microbiomes can differ by up to 90% from person to person. Jenny walks us through how Outpost Bio's "lab in the loop" model tightly integrates wet lab experiments with AI to generate better, less biased data from the ground up, and why rigorous external validation is the thing she'd tell every biotech founder to prioritize before anything else.

June 10, 2026

Episode 12: Your Life Sciences Data Isn't Ready for AI

<a href="https://www.kaleidoscope.bio/company" target="_blank" rel="ugc noopener noreferrer">Bogdan Knezevic</a> is the CEO and co-founder of Kaleidoscope Bio, and he's seen enough failed AI implementations to know where they almost always break down. In this episode, he walks us through what minimum viable data standardization actually looks like in practice, why consistent naming conventions and structured data entry matter more than people want to admit, and what every biotech CEO should ask their team before writing another AI budget line.We also get into a guardrails conversation and Bogdan is direct about what happens when autonomous agents operate without proper permissions. He closes with a sharp framework for deciding what to build in-house versus hand off, with some great resource hand-offs.<ul><li><a href="https://blog.kaleidoscope.bio/unlocking-the-importance-of-structure-data-vs-keys/" target="_blank" rel="ugc noopener noreferrer">Data vs keys</a></li><li><a href="https://blog.kaleidoscope.bio/ai-cant-reason-with-context-it-doesnt-have/" target="_blank" rel="ugc noopener noreferrer">AI needs context</a></li><li><a href="https://blog.kaleidoscope.bio/experimenting-your-way-to-success-data-management-in-biotech/" target="_blank" rel="ugc noopener noreferrer">Iterating your way to success via better data management</a></li><li><a href="https://blog.kaleidoscope.bio/where-is-your-biotech-on-the-data-maturity-ladder/" target="_blank" rel="ugc noopener noreferrer">The data maturity ladder</a></li><li><a href="https://blog.kaleidoscope.bio/before-ai-there-was-good-data/" target="_blank" rel="ugc noopener noreferrer">Before AI there was good data</a></li></ul>

15 total episodes available

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What is 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.
How often does this podcast release new episodes?: This podcast updates daily.
Where can I listen to this podcast?: This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
Does this podcast accept guests?: Yes, this podcast regularly features guests.

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