Dr. Priscilla Chan

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191 appearances 1 recordings 1 series first heard Jul 2026 last heard 9 Jul

Dr. Priscilla Chan’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

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The a16z Show · Mark Zuckerberg & Priscilla Chan: How AI Will Help Cure Disease · 9 Jul 2026 podcast

And then in San Francisco, we're looking at deep imaging and transcriptomics.

And that work, the locations are not by accident.

We also look at the partner universities because we have folks who come to the biohubs to do this work, collaborative, interdisciplinary, and sort of unconstrained by the traditional lab.

But we also build off of the labs at these academic institutes that support the work.

And so that's how we sort of choose the grand challenge and the locations.

And then the sort of layering and the large language models and AI coming into the picture has been so interesting because we were already building tools to measure interesting data, building the data sets.

But we didn't really know what to do with them yet.

And large language models coming onto the scene were like, wow, we can make sense of all of this now.

We want there to be like an explosion of a community who are building these, just the new wave of what it means to be deploying precision medicine.

Like, I think for rare diseases and common diseases alike, you're really talking about individual biology that we sort of lump together.

And we often don't know how it happens, right?

We know that you have this mutation or the worst nightmare is you have a variant of unknown significance.

What does that even mean?

Yes, horrible.

And you're like, you tell someone you kind of know something, but we don't know what it means.

But if you look at the way we've been able to look at variants and look at single-cell transcriptomics, we're starting to be able to say, okay, this variant actually impacts this set of downstream cells.

And then we start looking at the proteins that get expressed and how it looks similar or different to what a healthy cell would look like.

Then you can start targeting, okay, like, let's look at that as a target.

And you both know the specificity of the target you want to build based on the ability to connect mutation to protein expression, as well as to be able to predict off-target effects.

What are the side effects?

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