How AI Is Breaking the Rules of Biology | Dr. Priscilla Chan, Chan Zuckerberg Initiative

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1:21Marina Mogilko: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. 10 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, what will be the first diseases that you think are going to be cured? um 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

2:03Marina Mogilko:okay perfect okay priscilla thank you so much um 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 you've experienced it, 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.

2:40Marina Mogilko: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. But thank you so much for being brave and sharing it. And now you have two kids. And now I have two kids. It's just like, yeah, I mean, I'm so glad that 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.

3:17Marina Mogilko:I feel like 20 % of all women experience some kind of variation of this problem. It's very common. It's just 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 for her?

3:55And, 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.

4:44I 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 frontier 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.

5:36Marina Mogilko: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 are 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.

6:15We need better data set. We need new techniques in the lab. We need to have different types of 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 largest data sets around single cell biology. But again, we built that not knowing where it was going to go.

6:56And 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 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.

7:42And that has been a complete step change for us and incredibly exciting. I get so much energy doing this work.

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9:22Marina Mogilko: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. I'm so glad. It's the best. So that's where I trained. And hopefully you had a very uncomplicated experience there.

10:00But 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 taken 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.

10:42We barely can describe it. The hope that their parents held on to was the little research that existed on their kid's issue. And I looked at it and I looked at it. They would hand me these PDFs and I 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. And so just pulling on that thread led me to really think about how can we make an impact in biology.

11:18Marina Mogilko:Quick pause here. If you're enjoying this podcast, you will absolutely love my Inner 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 our cells and all of that.

11:50Marina Mogilko: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?

12:37How do we understand what happens inside your cell? 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.

13:23And 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.

13:43Marina Mogilko:Before I interviewed 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.

14:14Marina Mogilko:Virtual cells will change everything. So how far do you think we are from an actual 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?

14:52In 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 are 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.

15:39We 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.

16:19I think things like hypertension and depression, there's these big categories, But actually, it should break 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.

17:03Marina Mogilko:And once we do that, what will 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.

17:47That 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 cells already exist in your body. And we can, it sounds like science fiction, but it's not. 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.

18:36Marina Mogilko: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 let's talk about multiple sclerosis or neurodegeneration. 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 like actual infectious diseases too.

19:25But 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.

19:37Marina Mogilko: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 the actually the hardware tools has gotten a lot faster, but also clarity of purpose, right?

20:22But 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, you know, 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.

20:59There'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, OK, 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.

21:43And 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 cryo-ET. 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.

22:08Marina Mogilko:It's fascinating. So even with like cardio diseases, right? When you said clearplex, 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 responds is both healthy or sick or how it 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.

22:48The cells are just communicating each other and sending signals from faraway 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. I wore. Yeah, I was trying my glucose to see how I react to certain foods. Okay, very cool, right? And you could just wear it and it gives you 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.

23:39So 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.

24:12Marina Mogilko: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 think? Yeah, so let's – And it tells me like something. Is it okay if I make something up? Yeah. Okay, we're in make-believe now. Yeah, let's do it. 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. Um, and it, when it gets out of balance. So we want to know exactly when that happens, not when you have a flare and your kidneys aren't working right, or your joints are hurting.

24:57We 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.