Episode

Episode 7: AI at the Bench: The New Wet Lab Workflow

Podcast
From Models to Medicine
Published
May 6, 2026
Duration seconds
2704
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/kami-think-tank/episodes/Episode-7-AI-at-the-Bench-The-New-Wet-Lab-Workflow-e3isfhe
Audio
https://anchor.fm/s/110164688/podcast/play/119471086/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-4-4%2Fc4897bf5-93d8-51d4-2d2b-0afdd99737f9.mp3
JSON
/v1/public/podcasts/from-models-to-medicine-7769799/episodes/episode-7-ai-at-the-bench-the-new-wet-lab-workflow
Markdown
/podcast/from-models-to-medicine-7769799/episode-7-ai-at-the-bench-the-new-wet-lab-workflow.md

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Summary

In this episode of From Models to Medicine , we sit down with Elisa Martin Perez , a postdoc at University of California, Berkeley, to talk about how non-coders are starting to use AI in their day-to-day work. From learning R through conversation to making sense of massive CRISPR screens, Elisa shares how AI is becoming a practical tool for navigating data, checking experimental design, and cutting down on the kinds of manual tasks that quietly consume hours in the lab. We also get into the hesitation many scientists feel around adopting AI, where the technology actually helps (and where it doesn’t), and why it still falls short of running experiments end-to-end. Along the way, we touch on lab logistics, data overload, and what it means to use AI as a thinking partner rather than a replacement.