Silicon Valley Girl: AI, Tech and Career Growth - How AI Is Breaking the Rules of Biology | Dr. Priscilla Chan, Chan Zuckerberg Initiative

Episode Date: November 7, 2025

In this episode of Silicon Valley Girl, Marina Mogilko sits down with Dr. Priscilla Chan, co-founder and co-CEO of the Chan Zuckerberg Initiative, to explore how AI is reshaping the future of medicine.Together with Mark Zuckerberg, they’ve committed 99% of their wealth to building Biohubs and developing the world’s first virtual cell models — AI systems that can simulate life at the cellular level. This breakthrough technology could accelerate drug discovery, reduce clinical trial risks, and make personalized medicine a reality.Priscilla shares the moment in the clinic that changed her view of medicine forever, what it means to combine frontier science with frontier AI, and how she’s helping shift healthcare from treatment to prevention.Links: Follow my Newsletter: https://siliconvalleygirl.beehiiv.com/My Instagram: https://www.instagram.com/siliconvalleygirl/ YouTube: https://www.youtube.com/@SiliconValleyGirlLinkedIn: linkedin.com/in/marinamogilkoX: https://x.com/siliconvalleymm

Study and play. Come together on a Windows 11 PC. And for a limited time, college students get the best of both worlds. Get the Unreal College deal, everything you need to study and play with select Windows 11 PCs. Eligible students get a year of Microsoft 365 premium and a year of Xbox GamePass Ultimate

with a custom color Xbox wireless controller. Learn more at Windows.com slash student offer. While supplies last, ends June 30th, turns at AKA.m.m.S. college PC. Own it all. Pay off your home, travel for life, drive a Ferrari. In celebration of the world premiere of the Monopoly

Big Board Buckslot machine by Aristocrat Gaming, Yamava Resort and Casino at San Manuel is giving one person a $1.6 million dream package. The biggest prize in Yamava's history. Club Serrano members can earn daily instant prizes and secure a spot in the finale May 29th. Don't pass go and own it all. Only at Yamava, celebrating its 40th anniversary. You win?

Details at Yamava.com must be 21-20. Please gamble responsibly. Monopoly is a trademark of Hasbro. Hasbro is not a sponsor of this promotion. Science is going to be fundamentally different in like five years. What would it mean for me as a patient? This is the part I'm so excited about. This is Priscilla Chang, a Harvard graduate who went to UCSF School of Medicine to study pediatrics.

She treated children at UCSF until one moment in the clinic changed everything. It was honestly scary and really shook my understanding of medicine. In 2015, alongside her husband, Mark Zuckerberg, they launched the Chan Zuckerberg Initiative with the most ambitious goal. Our mission is to cure or prevent all disease. And we used to say by the end of the century, but I think it's much sooner. I would say like in the next year.

Ten years later, they've invested over $7 billion, built three biohubs, and are committed to creating AI models that map human cells, unlocking how disease begins and how it could end. And once we do that, we'll be the first diseases that you think will be cured. She's betting on a future

where science, data, and AI converge to end sickness as we know it. The only question is, how soon can we make that future real? Okay, perfect. All right. Priscilla, thank you so much. I have a personal story that I wanted to share. Okay. In 2015, you and Mark shared that you were pregnant with your first baby,

but also that you've experienced miscarriages. Yeah. And I was going through the same process. But for me, it started in 2015, and we only were able to have a baby in 2019. Oh, God bless. And I think you were the first public couple to share something like this on social media. And that kept me through the process. Oh, you're going to make me start off by crying.

I just really wanted to share this. And I am so grateful that you started talking about this problem because when you're going through it, it feels like you're just alone in it. Now with social media, people are sharing more and more. But when you're in it and when the doctors tell you, oh, it was your fault or whatever, because some doctors told me that. It's the worst. Thank you so much. Oh, I'm so glad. Being brave and sharing.

And now you have two kids. And now I have two kids. It's just like, yeah, I mean, I'm so glad that all worked out. And I felt the same way. I was like, I'm completely alone. I don't know anyone who has gone through this. Actually, Beyonce also had this problem. So you, me and Beyonce are in the same group.

I feel like 20% of all women experience some kind of variation of this problem. It's very common. It's not talked about that much. But I think the exciting part is like one way or another, people will have their families. Yeah. So thank you for that. And so when you had Maxine, you decided to commit 99% of your wealth into CZI, this initiative. Yeah.

So when we had Max, you've probably experienced this too. Everything sort of becomes very real. Like the future is not some abstract time in the distant future. You're like, I have this baby. She's coming now. Like, what are we going to do to actually like prepare? her. And, you know, we did the normal nesting stuff too. But what we really wanted was to do our part in building a future where she could be healthy and thrive. And that's why we started the Chan

Zuckerberg Initiative to figure out, like, what could we bring to the table? What could we do to build a future where kids are part of a world that's even better than what we have today? And what's your mission with CZI? Our mission with CZI and now BioHub, is to cure or prevent all disease. And we used to say by the end of the century, but through a bunch of work that we've done and these AI coming online with large language models, we've been able to see a pathway to this becoming a reality

much sooner than the end of the century. I would say like in the coming decades, it really comes down to whether or not we can make every scientist faster and more efficient and to take more risks. Like that's so important. And no one organization, not our organization, not any other organization, is going to do it alone. And our strategy is how do we build tools to make every single scientist better and to be able to test their riskiest, bravest ideas? And that's how we're going to be able to move this forward in a pace that hopefully will blow all of our minds.

And what we're doing at the biohub is we want to combine frontiers. science with frontier AI work to really bring together a world where we are able to push forward science to have direct impact on people's lives much, much sooner. This mission sounds amazing, but also so brave, right? We're going to cure all diseases. So when you stated this 10 years ago versus now, like how has people's reaction changed when LLMs came around? It's such a great question because 10 years ago, people looked at us like, you're nuts. How do you even do that? And it was exactly that reaction that we said, okay, tell us why we're wrong.

Tell us why that won't happen. And that really forced people to pause and instead of just a knee-jerk reaction, think through like, why is that not possible? And that really prompted people to say, well, we need better tools. We need better data set. We need new techniques in the lab. We need to have different types of people. people come in to solve this problem together. And then we said, okay, if that's the problem,

then let's go do it. And so we started building tools for scientists. We built the biohubs where we bring together scientists, engineers, biologists, physicists, all different backgrounds to solve a common problem together. And we went from one biohub to four in the past 10 years. And all of that, we were making steady progress. And we also built one of the large, just data sets around single cell biology. But again, we built that not knowing where it was going to go. And then two years ago, we both had this data set, cell by gene, coming together. And then people were like, you know, like, what about large language models? And I was like, I don't know what that is. Like, let me look that up. I am a physician by training, not a engineer

or a machine learning expert. And so I looked at it up. I was like, wait a minute. This is actually perfect. I see the pathway to taking the incredible amount of data that can come out of biology labs and actually extract meaningful knowledge. And that was, you know, maybe two years ago. Now today you say it, and some people are still skeptical, but a lot of people look at it and say, okay, I can see how you can get there. And that has been a complete step change for us and incredibly exciting. I get so much energy doing this work. Ambition comes in all shapes and sizes.

At First Citizens Bank, we roll with your goals because we're built for what you're building. Fit for your ambition for Citizens Bank. When you need to build up your team to handle the growing chaos at work, use Indeed-sponsored jobs. It gives your job post the boost it needs to be seen

and helps reach people with the right skills, certifications, and more. Spend less time searching and more time actually interviewing candidates who check all your boxes. Listeners of this show will get a $75-sponsored job credit at Indeed.com slash podcast. That's Indeed.com slash podcast. Terms and conditions apply. Need a hiring hero? This is a job for Indeed sponsored jobs. Do you remember the moment when you were like, okay, this is when I need to start doing this? This is when I need to start investing in biology. Was there some personal story behind that?

Well, I trained as a pediatrician at UCSF. And UCSF is, you know, a very fancy academic. Delivered both babies there because they're pro-natural birth. I was researching, so I drove from Los Altos Hills to UCSF. Incredible. During contractions. But it was the best decision. You probably delivered at the fancy, beautiful new hospital too.

Yeah. I'm so glad. It's the best. So that's where I trained. And, you know, hopefully you had a very uncomplicated experience there. But for a lot of people who bring their kids there, it is because no one else has been able to give them an answer or they need a subspecialty that doesn't really exist anywhere else. And as a pediatrician, those were the kids that was taking care of most of the time. And it was honestly scary and really shook my understanding of medicine.

Going into medical school and residency, I was like, if I do a good job and I sort of learn what's being taught, I'm going to be able to help people. And what I learned in the clinic and on the wards is a lot of these kids have things that we don't know the names of. And we don't know how to treat. We barely can describe it. The hope that their parents held on to was the little research that existed on their kids issue. And I looked at it and I looked at, they would hand me these PDFs and I would look at the PDFs and it would look at the PDF and it'd be like, how do I translate that to medicine or treatment or what I need to do for this kid? It was so limited. And that's when I realized that being able to move basic science forward, that's where hope comes from for these kids.

Yeah. And so, you know, just pulling on that thread led me to really think about how can we make an impact in biology. Quick pause here. If you're enjoying this podcast, you will absolutely love my In A Circle newsletter. My newsletter is basically behind the scenes from the heart of Silicon Valley. I'm building a language company, a personal brand, a family. all while navigating tech and creativity. So every week I share real wins, real falls, quick, actionable tips to level up your business

and life. Let's build and grow together. The link is in the description. Join my free newsletter to stay ahead. And with this, you're not focusing on any particular diseases, right? You're just trying to map ourselves and all of that. Or is there some focus? There really isn't.

And the way to think about it is we want to make all scientists better at doing their job and more effective. And we have built, you know, annotation tools. We have built technical wet lab tools to help scientists do their work. And the cell by gene work is what we did when we mapped out individual cells and how they were each different across a human body. You know, you have the same DNA creates your skin cell that creates your heart cell, your liver. it's the same DNA. How does it actually lead to such different outcomes? And what happens when the DNA has a mutation or something goes wrong? How do we understand what happens inside yourself?

And the really cool thing there is if we can understand how it works when it's healthy and what happens when there's an error or something happens from the outside, what is actually the impact? How does the cell look differently because if you understand it at that level, then you can design very specific treatments to actually correct the issue. And so we don't work disease by disease, but we want to work in a world where we can experiment quickly, efficiently on human knowledge. Right now, a lot of the models are like, you know, you can study in flies or mice or rats. But that doesn't always translate to humans. And so we think if we could build a virtual cell model that allows us to do a lot of this experimentation on a human model, but on a computer, then it's cheaper, it's faster for

scientists to do the research. And it applies more directly to the clinic and has more direct impact on people's lives. Before I interview with Priscilla, I got to meet some incredible scientists who are mapping what's happening inside our cell. They're working on something called virtual cells, computer simulations that replicate how real biological cells behave and function. Once we have fully working virtual cells, it will completely change medicine, biology, and even how we understand life, because we'll be able to understand disease before it happens. Drug discovery will be hundreds of times faster. We'll get personalized health because we'll be able to have our digital twins, and biology will basically become programmable. Virtual cells will change everything. So how far do you think we are from

a natural virtual cell. Oh, it really depends on who you ask. If you ask the AI folks, they're like, you know, three years, two years, and they're impatient. If you sort of ask folks with the biology background, there's so many different dimensions. And, you know, we're looking a little further out. But, you know, I would say the way we think about science is going to be fundamentally different in terms of our ability to model the human cell in like five years. What would it mean for me as a patient? What will change in five years? In five years, I think scientists will have an incredible tool. Obviously, like, that's great, but the thing we actually all care about is the impact on people's lives. This is the part I'm so excited about. We need to understand individuals' biology. Right now, we get to have this like, on average, this is what a skin cell does.

On average, this is how your brain cell behaves. But none of us. our average, and each of us has unique biology. But the research won't tell me how my brain would react to a certain medication than your brain would. But we have very distinct biology. The thing I want is for us to be able to do medicine where it's also on the frontier. We can understand based on your genetics, this is how your brain reacts to certain conditions, how it responds to different medications. And because we all have variants within our DNA, that is the part I'm so excited about. Because right now, we either don't understand or we give you a treatment that's our best guess. Yeah. And it causes a lot of suffering. And, you know, what kind of diseases

are this? People often think, okay, we're talking about rare diseases that we don't have treatments for. And it's true. Rare diseases are a really good match for this type of work. But in reality, common diseases are rare diseases. I think things like hypertension and depression, there's these big categories, but actually it should fall down into different sub-diseases because, you know, one person reacts very differently to a blood pressure medication than another. One person's depression reacts very differently to one type class of antidepressants than others. And if we understood each one of our biology, we would either be able to choose the most effective medication right away or design it. And that's the world. I know we're going to be able to live in once we can

understand the biology at a more granular level as well. And once we do that, we'll be the first diseases that you think are going to be cured. Oh, this is such an interesting question. Honestly, I don't really have, like I said, we allow scientists from the outside to take it and solve problems. But I will say, I think the immune system is fascinating because the immune system is built in. It's like in your DNA, it's in your biology. It keeps you healthy. It's critical. And when it's overactive, it also makes you sick. So there's like a very fine balance in the immune system that if we understood how that balance gets out of whack in either direction, we could help a lot of people with autoimmune disease. That would be incredible.

Another application is right now, immune cells are already special cells. They get to go all over your body and solve problems. What if we just enhance that to allow us to engineer immune cells to say, like go to your heart and say, are there plaques in the arteries? Tell us yes or no. And then go do something about it, clean it up. Like those things. cells already exist in your body. And we can, it's, it sounds like science fiction, but it's not. Yeah. It does. It's not. Our New York biohub is working on this very question. And so I think there's so much promise in enhancing the way the immune system works and understanding the different levers that optimize it in each one of us. So basically in 10 years, if everything goes well,

the way we treat cold would be let's extract my immune cell reprogram it, put it back and it treats cold. Is that? Oh, cold is interesting. I would say you probably don't want to wait for your immune cell to be re-engineered for that. But like let's talk about multiple sclerosis or neurodegeneration. Like you want to understand exactly in which pathway you have upregulated interleukin 10 or whatever it is. and you want to be able to dial it back down so that your immune system doesn't attack itself. That would be incredible.

And I think there's a lot more you can do actually in helping address actual infectious diseases too. But I think the thing I want to really expand everyone's imagination on is that the immune system is not just good for infectious disease. It's actually critical in keeping all of our organs healthy. I was just talking to some of your scientists, and they told me you were able to map 0.1% of the cell to build this virtual model. Does this number get us somewhere, or we still need to map at least like 50% to understand what's going on? There's so much more work to do. Luckily, it just gets faster and faster. It took us 10 years to map, you know, around 100 million cells.

But it's taken us months to map a billion cells. So the rate of the ability to map and understand different dimensions of the cell has accelerated. Is that because of AI or because you already have the data set? It's because actually the hardware tools has gotten a lot faster, but also clarity of purpose, right? But the other thing that needs to happen is that's just when we talk about the human cell Atlas data set, that's at the single cell transcriptomics. we are looking at how your DNA is being transcribed to RNA in different cell types. But that's just one dimension. We need to be looking at where the proteins are.

So that's why here at the imaging institute, we're looking at it in a cell map. And we can look at the layout and look at where the protein is being expressed. But still, those cells are frozen and sliced. So then we need to look at it in a living cell. And we need to look at how the cell behaves in different contexts. There's just so many more angles that we haven't been able to probe and understand. So a lot more needs to happen. But the really exciting thing for us is we pair our AI labs with our wet labs.

And so that conversation between those two teams, they aren't siloed. The AI lab can say, okay, we've built this model. We have this blind spot. Or we need to look at this next. The wet lab can say, oh, Well, actually, either we can do it or we know someone who can do it. And then they can also feed information around the metadata of what they're seeing in the lab and share that with the AI researchers so they can build that more efficiently.

And then vice versa, the folks in the wet lab can say, I have this bottleneck. I can't efficiently look at the tomograms that are coming out of the cryoET. Then they can say, oh, I can build you something to help with that. And so it's that combination of frontier AI and frontier biology that we are hoping comes together in a flywheel to make this work so much faster. It's fascinating. So even with like cardio diseases, right, when you said clearplex, that that's something the immune system could do. Totally. And you're building a virtual immune system, right?

Yes. Can you talk about it? What does it mean? So, you know, I've been talking a little bit about the virtual cell where we're going to model a single cell and how it, respond is both healthy or sick or how responds to changes. The virtual immune system is sort of a next level up where the immune system has lots of cell types. And the cells communicate with each other and they work together as a team. There's no one organ. The cells are just communicating each other and sending signals from far away locations across your body.

Understanding that communication and when the immune system turns on and off is actually really important. And the very cool thing is at our biohub in Chicago. Shana Kelly has actually designed a sensor, really tiny sensor, kind of like the continuous glucose monitor. If you've ever seen anyone wear one of those. Yeah, I was trying my glucose to see how I react to certain foods. Okay. Very cool, right? And so, and you could just wear it.

Yeah, for a week. ongoing information. She built a little sensor like that that reads out the signals of your immune cells talking to each other in a living organism, which is incredible because you want to know the dynamic system of how it works together. So she is building the technology that allows us to measure the communication between the immune system. And then we can take that data and model it in a virtual way where then we can manipulate different parameters and actually understand all different diseases based on this virtual immune system. And that's an example of sort of how the wet lab empowers the AI modeling and the AI modeling

improves the wet lab. And it's incredible. So it's something I'm trying to imagine 2040. So I'm wearing, sort of glucose monitor, I'm wearing this immune monitor. right? Or what do you? Yeah. So let's, let's, let's tell me like something. Am I, is it okay if I make something up? Yeah. Okay. Okay. We're in make believe now. Yeah. But I think it's possible. Yeah. Okay. So say we understand that based on your genetics, you are at risk for lupus. Okay. And it's an autoimmune disease. But we know that lupus gets triggered when a certain molecule increases.

And it, when it gets out of balance. So we want to know. know exactly when that happens. Not when you have a flare and your kidneys aren't working right or your joints are hurting. We want to know like the first signal. So you could wear a patch that looks at that molecule and measures the concentration of it and tells us the moment that molecule starts increasing in a way that represents a disease flare. That's amazing. I would want to wear it for every disease, right? Even for cold. Like, oh, you're getting something. There's a bug. Yeah. Go home. So it's just like, imagine that. Like, that's how you keep someone healthy.

You prevent them from going into flare in the first place. That's the best. And then in the virtual cell model, then you can say, okay, when this person has a flare in lupus, we know that this protein is what is working in an inappropriate way. Then you could design a custom drug to help modify that. so that we don't have those disease effects. Anyways, this is my make-believe land. This is what I daydream about. But I think it's very feasible based on more sciences.

So you said the things that you're fascinated about, what keeps you up at night with all this? I think it is so important to work quickly. I'm not a scientist myself, right? I'm a pediatrician. So my job is to understand the barriers to the work and help eliminate the barriers so that we can work efficiently and effectively.

And that's my whole job. And for everyone who's watching who's a future scientist wants to be a doctor, what would be your advice? This is probably the most exciting time to go into this work. And so do it. How do you see, because we go to all the LLMs to ask for health advice, right? How do you see this change the way people study now? Maybe you would say they need to go deeper into science because this is where all the progress

happens versus just general practice. So we're going to need people on the biology side to continue deepening our knowledge of the biology. And the interesting thing is biologists aren't physicians and they're also not always patients. And so a physician who has experienced taking care of patients deep in the sense. science, that's actually magic because they understand what the patient faces and they help the biologists ask the right questions. Like that's actually very powerful and very cool. That's the job of the future, right, of something that's going to be in great demand. Totally. But then on the other opposite, on the other end of not opposite, I don't want to paint

it like these things are in tension. There's also a different need because right now, for instance, looking at skin moles, like skin checks or retinal issues, AI is really good at it. Like, if you look at the head-to-head, it is an improvement with then just the physician reviewing these things on their own. And so what is the role of the physician? I think the role of the physician is making sure that we are asking the right questions of AI, like looking at this, like, this person's at risk. We should look at the skin.

I also think it goes back to the original calling and purpose of a physician, which is a healer, and you walk alongside patients going through all different chapters of their life, and that's always going to be in need. Was there a moment when discovery felt deeply personal for you in the past 10 years? Oh, well, you know, the pregnancy stuff is always interesting. We actually did a study on the single cell, expression of the female reproductive organs. Like that's, because we actually don't understand, do you know we don't understand how labor

is triggered? Oh, we don't? We don't. It's magic. Okay. And so we thought it was like hormones, but we don't know when it starts, right? Like when the hormones start? We don't know how the whole cascade gets triggered.

Oh, wow. And so we actually did a whole project around that. But we also have a portfolio called Rarers 1. where we bring rare disease groups together and give them the training and resources to engage in the research process. Those groups are incredible. They are patients or families of patients that are full of hope, but also realistic, that, you know, they can be part of making the science better, but it might not impact their trajectory. Like, those groups are what fuel. their belief in science and belief in the future fuel me.

And sometimes I don't know who's a part of these groups. And one day I got a text message from a friend of my sister who said, say thanks to your sister. And my sister was like, why? And it was because research that her rare disease group did that allowed her to get a diagnosis for something that she had been experiencing. Not even a cure, not preventing her disease, just naming it so she didn't feel so alone and so powerless. That is something that motivates me.

This is fascinating. Do you think there are any diseases that will be able to cure with this technology in our lifetime? Or what is the most probable disease to be cured? I actually think many diseases will be cured within our lifetime because, you know, I treat, UCSF from 2012 to 2015. And diseases that were incurable death sentences have very reasonable and effective treatments now. And, you know, 2015 was 10 years ago. Like, that is a huge difference. And baby KJ at CHOP, baby KJ was born with a mutation that would make it very, very difficult to grow up to have a normal, healthy life. But because we understood.

the mutation and we were able to correct it, he's probably going to live a healthy life. Like, that also sounds like science fiction. And it's not just him, right? It's also future babies who might be born. Exactly. And so I think like the things that are sort of super ripe right now are the ones where we have a very clear understanding of the molecular and genetic basis of why it happens. So I can see the pathway for all those diseases. So we can see, we got to get more diseases to that level of understanding. What is the genetic underpinning? What is the molecular underpinning?

And we need better models and we need scientists to be able to do more risky, bold projects to solve those questions. That is fascinating that you were doing this work with the resources. And are you waiting for something to happen where you'd say, my mission is fulfilled? I don't have an idea of what that might be like. I think that there's always more interesting work to do. So you're always, always flushing. My last question is for every mom who's watching.

I also wants to build something, but, you know, kids take a lot of time. What would be your advice? How do you balance this? I am extremely disciplined about my schedule. And so I have a time that is dedicated to the children, and I have time that's dedicated to work. don't mix those things. And that's it. And that's okay with me. You know, the more fun social stuff, that will come later when the kids have left the house. Love it. Yeah. Thank you so much. And thank you for the work that you're doing. You're definitely changing the world. And hopefully

AI is just going to speed it up totally. And we'll get some great results in five years. Thanks for shining a light on science. Summer is here. And Ralph's is your destination for hot savings. Find unique items at low prices with a wide assortment of products from our exclusive brands. Fire up the grill with cookout classics like burgers and brots and don't forget, delicious produce like fresh melons. Or beat the heat with frozen treats while chilling poolside. Whatever your summer plans, Ralph's makes it easy to enjoy high quality fresh food at affordable prices. Ralph's, serving SoCal for over 150 years. All right, class, settle down.

Today's lesson is on the Arco Rewards app. Try to stay with me. The fundamentals are simple. Earn at least five cents a gallon in rewards, then redeem them later for up to a dollar off every gallon. Now here's where it gets complicated. Oh, wait, it doesn't. It's as simple as downloading the ARCO rewards app to get started.

Class dismissed. Savings of up to $1 per gallon redeemable with $20 rewards dollars in your loyalty account. At participating locations, terms and conditions apply. Thank you.