Episode

Episode 18: Why Does mRNA Keep Breaking AI Models?

Podcast
From Models to Medicine
Published
Jul 29, 2026
Duration seconds
2408
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/kami-think-tank/episodes/Episode-18-Why-Does-mRNA-Keep-Breaking-AI-Models-e3mcg0n
Audio
https://anchor.fm/s/110164688/podcast/play/123141591/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-6-27%2F51845afb-f550-bc78-841f-c1a08fc61199.mp3
JSON
/v1/public/podcasts/from-models-to-medicine-7769799/episodes/episode-18-why-does-mrna-keep-breaking-ai-models
Markdown
/podcast/from-models-to-medicine-7769799/episode-18-why-does-mrna-keep-breaking-ai-models.md

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Summary

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.