From Models to Medicine

Episode 13: The Microbiome is Messier Than You Think

June 17, 2026·30 min
Episode Description from the Publisher

Jenny Yang 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.

Podzilla Summary coming soon

Sign up to get notified when the full AI-powered summary is ready.

Get Free Summaries →

Free forever for up to 3 podcasts. No credit card required.

Listen to This Episode

Get summaries like this every morning.

Free AI-powered recaps of From Models to Medicine and your other favorite podcasts, delivered to your inbox.

Get Free Summaries →

Free forever for up to 3 podcasts. No credit card required.