Pod Insights Silicon Valley Girl: AI, Tech and Career Growth How AI Is Breaking the Rules of Biology | Dr. Priscilla Chan, Chan Zuckerberg Initiative About this episode 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.
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0:00 Speaker 00 This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. It boosts your job post to help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a $75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs.
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0:59 Speaker 02 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.
1:07 Marina Mogilko? 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.
1:17 Speaker 02 It was honestly scary and really shook my understanding of medicine.
1:22 Marina Mogilko? In 2015, alongside her husband Mark Zuckerberg, they launched the Chan Zuckerberg Initiative with the most ambitious goal.
1:29 Speaker 02 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...
1:37 Marina Mogilko? 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?
1:55 Marina Mogilko? 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?
2:06 Speaker 02 Okay.
2:07 Marina Mogilko? Perfect.
2:08 Speaker 02 Okay.
2:09 Marina Mogilko? Priscilla, thank you so much. I have a personal story that I wanted to share.
2:13 Speaker 02 Okay.
2:13 Marina Mogilko? In 2015, you and Mark shared that you were pregnant with your first baby, but also that you've experienced miscarriages.
2:20 Speaker 02 Yeah.
2:20 Marina Mogilko? And I was going through the same process.
2:22 Speaker 02 Oh.
2:22 Marina Mogilko? But for me, it started in 2015, and we only were able to have a baby in 2019.
2:27 Speaker 02 Oh, God bless.
2:28 Marina Mogilko? And I think you were the first public couple to share something like this on social media. And that kept me through the process.
2:36 Speaker 02 Oh, you're gonna make me start off by crying.
2:39 Marina Mogilko? 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.
2:57 Speaker 02 It's the worst.
2:57 Marina Mogilko? But thank you so much.
2:58 Speaker 02 Oh, I'm so glad.
3:00 Marina Mogilko? Being brave and sharing it.
3:01 Speaker 02 And now you have two kids.
3:02 Marina Mogilko? And now I have two kids.
3:03 Speaker 02 It's just like, I, 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.
3:20 Marina Mogilko? I feel like 20% of all women experience some kind of variation of this problem. It's very common. It's just, it's not talked about that much.
3:27 Speaker 02 But I think the exciting part is like, one way or another, people will have their families.
3:33 Marina Mogilko? Yeah.
3:33 Speaker 02 Yeah.
3:34 Marina Mogilko? So, thank you for that. And so when you had Maxine, you decided to commit 99% of your wealth into CZI, this initiative.
3:42 Speaker 02 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 gonna do to actually like, prepare for 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?
4:23 Marina Mogilko? And what's your mission with CZI?
4:25 Speaker 02 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 the 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.
5:05 Speaker 02 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.
5:39 Marina 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?
5:52 Speaker 02 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. We 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
6:33 Speaker 02 for scientists. We built the bio hubs where we bring together scientists, engineers, biologists, physicists, all different backgrounds to solve a common problem together. And we went from one bio hub 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 gonna 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."
7:13 Speaker 02 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." And that has been a complete step change for us and incredibly exciting. I get so much energy doing this work.
7:56 Speaker 00 This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. It boosts your job post to help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a $75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs.
8:26 Speaker 04 Low energy, unfocused, foggy? You might be dehydrated. Gatorade Zero powders have been scientifically designed to help improve hydration balance in the body with a clinically proven electrolyte blend and no artificial colors or flavors. Great tasting hydration, no matter where you're going. Shop now online or at retailers nationwide. Gatorade hydrates better than water. Is it in you? Symptoms noted are signs of mild to moderate dehydration. Consult a healthcare professional if symptoms persist.
8:55 Marina 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?
9:05 Speaker 02 Well, I trained as a pediatrician at UCSF. And UCSF is, you know, a very fancy academic.
9:13 Marina Mogilko? Delivered both babies there because they're pro natural birth. I was researching, so I drove from Los Altos Hills to UCSF.
9:20 Speaker 02 Incredible.
9:21 Marina Mogilko? During contractions, but it was the best.
9:22 Speaker 02 You probably delivered at the fancy, beautiful new hospital too.
9:25 Marina Mogilko? Yeah.
9:27 Speaker 02 I'm so glad.
9:28 Marina Mogilko? It's the best.
9:28 Speaker 02 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 I 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
10:11 Speaker 02 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 PDF and be like, how do I translate that to medicine or treatment or what I need to do for this kid? It was so limited.
10:35 Marina Mogilko? Yeah.
10:36 Speaker 02 And that's when I realized that being able to move basic science forward, that's where hope comes from for these kids.
10:43 Marina Mogilko? Yeah.
10:43 Speaker 02 And so, you know, just pulling on that thread led me to really think about, how can we make an impact in biology?
10:50 Marina 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. Or is there some focus?
11:25 Speaker 02 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 lab tools to help scientists do their work. And the cell by gene work where is what we did when we mapped out individual cells and how they were each different across the 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?
12:10 Speaker 02 How 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 us 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,
12:53 Speaker 02 but that doesn't always translate to humans. And so we think if we can 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.
13:16 Marina Mogilko? Before our 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 an actual virtual cell?
13:53 Speaker 02 Oh, it really depends on who you ask. Um, 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 a 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.
14:21 Marina Mogilko? What would it mean for me as a patient? What will change in five years?
14:25 Speaker 02 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 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.
15:10 Speaker 02 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, that's our best guess.
15:34 Marina Mogilko? Yeah.
15:34 Speaker 02 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 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, they should, it should fall, 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.
16:17 Speaker 02 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, I, I know we're gonna be able to live in. Once we can understand the biology at a more granular level as well.
16:36 Marina Mogilko? And once we do that, will be the first diseases that you think are gonna be cured?
16:41 Speaker 02 Oh, this is such an interesting question. Honestly, I don't really have, uh, uh, 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.
17:26 Speaker 02 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's, it sounds like science fiction, but it's not.
17:51 Marina Mogilko? Yeah.
17:52 Speaker 02 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.
18:09 Marina 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?
18:18 Speaker 02 Oh, cold is interesting. I would say you probably don't want to wait for your immune cell to be reengineered 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. Uh, and I think there's a lot more you can do actually in um uh helping address like actual infectious diseases too. But I think the thing I want to really expand everyone's imagination on
19:02 Speaker 02 is that the immune system is not just good for infectious disease. It's actually critical in keeping all of our organs healthy.
19:10 Marina Mogilko? I was just talking to some of your scientists and they told me you were able to map zero point one percent of the cell to build this virtual model. Does this number get us somewhere or we still need to map at least like fifty percent to understand what's going on?
19:24 Speaker 02 There's so much more work to do, um, luckily it just gets faster and faster. It took us um ten years to map, you know, around a hundred million cells. But it's taken us months to map a billion cells. So the rate of the ability to map and understand uh different dimensions of the cell has accelerated.
19:45 Marina Mogilko? Is that because of AI or because you already have the data set?
19:48 Speaker 02 It's because the, 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, 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's 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.
20:32 Speaker 02 There are just so many more angles of that we haven't been able to probe and understand. So a lot more needs to happen. But the really exciting thing uh for us is we pair our AI labs with our wet labs. And so that conversation between those two teams, they aren't siloed.
20:55 Speaker 02 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, we 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 researcher, so they can build that more efficiently. And then vice versa, they can, 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 E T. 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.
21:41 Marina Mogilko? It's fascinating. So even with like cardio diseases, right? When you said clear plaques, that
21:45 Speaker 02 Yeah.
21:46 Marina Mogilko? that's something the immune system could do.
21:47 Speaker 02 Totally.
21:48 Marina Mogilko? And you're building a virtual immune system, right?
21:50 Speaker 02 Yes.
21:51 Marina Mogilko? Can you talk about it? What does it mean?
21:53 Speaker 02 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 a 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 our bio hub in Chicago.
22:38 Speaker 02 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.
22:47 Marina Mogilko? I wore.
22:47 Speaker 02 Or you've worn one?
22:48 Marina Mogilko? I was trying my glucose to see how I react to certain foods.
22:51 Speaker 02 Okay, very cool, right? And so, and you could just wear it and it gives you
22:56 Marina Mogilko? For a week.
22:57 Speaker 02 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 wanna know that 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 uh different uh parameters and actually understand all different diseases based on this virtual immune system. And uh that's an example of sort of how the wet lab empowers the uh AI modeling and the AI modeling improves the wet lab.
23:42 Speaker 02 And um it's it's incredible.
23:45 Marina Mogilko? So it's something I'm trying to imagine twenty forty. So I'm wearing sort of glucose monitor, I'm wearing this immune monitor, right? Or
23:53 Speaker 02 Yeah, so let's
23:54 Marina Mogilko? And it tells me like something
23:55 Speaker 02 Am I, i- is it okay if I make something up?
23:57 Marina Mogilko? Yeah.
23:58 Speaker 02 Okay, we're we're in make believe now.
23:59 Marina Mogilko? Yeah.
23:59 Speaker 02 But I think it's possible.
24:00 Marina Mogilko? Yeah.
24:01 Speaker 02 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 wanna know exactly when that happens, not when you have a flare and your kidneys aren't working right or your joints are hurting. We wanna know like the first signal.
24:32 Marina Mogilko? Yeah.
24:32 Speaker 02 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.
24:45 Marina Mogilko? That's amazing. I would wanna wear it for every disease, right? Even for cold, like, oh, you're getting something, there's a bug.
24:50 Speaker 02 Yeah.
24:51 Marina Mogilko? Go home.
24:52 Speaker 02 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.
25:00 Marina Mogilko? Then that's the best.
25:01 Speaker 02 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
25:19 Marina Mogilko? Yeah.
25:19 Speaker 02 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 where science is.
25:33 Marina Mogilko? So you said, the things that you're fascinated about. What keeps you up at night with all this?
25:39 Speaker 02 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, that's my whole job.
25:56 Marina Mogilko? And for everyone who's watching, who's a future scientist or wants to be a doctor, what would be your advice?
26:02 Speaker 02 This is probably the most exciting time to go into this work. And so, do it.
26:08 Marina Mogilko? How do you see, because we go to all the L L Ms to ask for health advice, right? How do you see this change? The way people study now, maybe because maybe you would say they need to go deeper into science because this is where all the progress happens versus just general practice.
26:26 Speaker 02 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 experience taking care of patients.
26:47 Speaker 02 Deep in the science, that's actually magic because they understand what the patient faces. And they help the biologist ask the right questions. Like, that's actually very powerful and very cool.
27:00 Marina Mogilko? That's the job of the future, right? Something that's going to be in great demand.
27:04 Speaker 02 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 intention. There's also a different need because right now, for instance, looking at skin moles, like skin chex or retinal issues, AI is really good at it. Like, and if you look at the head to head, it is an improvement with than 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.
27:48 Speaker 02 And you are, you walk alongside patients going through all different chapters of their life. And that's always going to be in need.
27:58 Marina Mogilko? Was there a moment when discovery felt deeply personal for you in the past 10 years?
28:03 Speaker 02 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?
28:20 Marina Mogilko? Oh, we don't?
28:21 Speaker 02 We don't. It's magic.
28:23 Marina Mogilko? Okay.
28:23 Speaker 02 And so
28:24 Marina Mogilko? I thought it was like hormones, but we don't know when it starts, right? Like, when the hormones start.
28:28 Speaker 02 We don't know how the whole cascade gets triggered.
28:31 Marina Mogilko? Oh, wow.
28:32 Speaker 02 Um, and so we actually did a whole project around that.
28:38 Speaker 02 But we also have a portfolio called Rare is One, where we bring rare disease groups um 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, um 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.
29:16 Marina Mogilko? Yeah.
29:16 Speaker 02 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 mom, 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.
29:41 Marina Mogilko? Wow.
29:41 Speaker 02 Not even a cure, not preventing her disease, just naming it so she didn't feel so alone and so powerless. Like, that is something that, like, motivates me.
29:53 Marina Mogilko? This is fascinating. Wait, do you think there are any diseases that we'll be able to cure with this technology in our lifetime? Or what is the most probable disease to be cured?
30:02 Speaker 02 I actually think many diseases will be cured within our lifetime. Um, because, you know, I trained at UCSF from twenty twelve to twenty fifteen. And diseases that were incurable death sentences have very reasonable and effective treatments now. And, you know, twenty fifteen was ten 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 gonna live a healthy life.
30:46 Speaker 02 Like, that sounds like, also sounds like science fiction.
30:50 Marina Mogilko? And it's not just him, right? It's also future babies who might be born.
30:53 Speaker 02 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 gotta 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.
31:26 Marina Mogilko? That is fascinating that you are doing this work with, with the resources. And are you waiting for something to happen where you'd say, my mission is fulfilled?
31:35 Speaker 02 I don't have an idea of what that might be like. Um, I think that there's always more interesting work to do.
31:43 Marina Mogilko? So you're always, always pushing. My last question is for every mom who's watching.
31:47 Speaker 02 Okay.
31:48 Marina Mogilko? Who also wants to build something. But, you know, kids take a lot of time. What would be your advice? How do you balance this?
31:54 Speaker 02 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. I don't mix those things and that's it. And that's okay with me. I, you know, the more fun, social stuff, that will come later when the kids have left the house.
32:18 Marina Mogilko? Love it.
32:19 Speaker 02 Yeah.
32:19 Marina Mogilko? 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 gonna speed it up uh, totally and we'll go, we'll get some great results in five years.
32:29 Speaker 02 Thanks for shining a light on science.
32:31 Marina Mogilko? Yeah, thank you.
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Previous Google’s AI Search Expert: How to Get Ahead Before AI Changes Everything | Robby Stein Next CEO of Microsoft AI: The Next 10 Years Will Change Humanity Forever | Mustafa Suleyman Page updated October 31, 2026 · transcript and summary are machine-generated