The Chan Zuckerberg Initiative Fights Disease With a New Approach

[MUSIC PLAYING] Well, this is really a great occasion to have a chance to meet with Priscilla Chan and Mark Zuckerberg and discuss the remarkable progress and dedication at the Chan Zuckerberg Initiative. CZI has been around for well over 5 years now, and it also coincides with the 10-year anniversary of you two getting married.

[LAUGHTER]

So to start, how did you conceive this idea of CZI?

Well, I think we both knew that we always wanted to give back, and we knew that we were going to put a lot of time and effort into making sure that we are doing our part in building a better future. And I want to be clear. We chose really big sectors that we're working in -- science, education, cure, prevent, or manage all disease. Huge audacious goals.

And I think the part that we wanted to get smart on is where our niche was going to be, what we could bring that was differentiated in the field to help everyone make progress. And so for the past 5 years, we've really experimented with different models, different ways of building things inside CZI's four walls, outside of CZI's four walls, partnering with folks all across the field to try to figure out where our niches and where we can do our best work.

Well, the part that's dedicated to life science and medicine that you touched on, which is pretty extraordinary, but it was back in 1994 when I came across The Economist saying that all serious diseases would be cured over by 2050. So at least you weren't as bold as that. You said, well, end of the century.

No. And we don't necessarily think that they're all going to be cured. That's why it's cure, be able to prevent upfront, or just be able to manage as ongoing chronic things. Yeah, I mean I think the goal is just if we can help accelerate the field of science then we can just bring in that time when we get to create a better world for our kids' generation and generations after that.

Yeah.

Sure.

There's a rule of thumb, Mark, that you like to share like you overestimate what you can do in a year?

Yeah, that people overestimate what you can get done in a year or two and dramatically often underestimate what you can get done if you work consistently on something over a longer period of time. So in tech, they say 10 years. I think science is a somewhat longer time.

But there are a lot of really brilliant people obviously working in the field, so we just view our goal as basically building tools. And especially with my background as an engineer and built this company and built operations at scale, being able to deliver tools that all scientists can use to just accelerate towards the state of being able to either cure, prevent, or manage all diseases, it seems like it's worth going at.

I don't know, maybe 2050 is too ambitious, but I'm still optimistic that by the end of this century we can make progress.

Well, what's interesting is this fusion of background from engineering, computing to medicine and you as a pediatrician, but it's really actually striking how the two of you came together with different backgrounds and it represents the future of life science and medicine in so many respects. Actually, tools is a really important point because many people think it's all about breakthroughs whereas you've taken a different track.

Another thing that's big that you've done is this Advanced Biomedical Imaging Institute, which I'd like to hear more about. Obviously, AI it's a sweet spot of deep neural networks and imaging, maybe you can just give more color about this new biomedical -- you've been on it already but you're taking it to another level, I take.

For the next 10 years a lot of the focus for the different work that we are going to try to fund is going to be about basically measuring human biology in action. So the Imaging Institute is one example of this. One of the major scientific focuses for this Imaging Institute is to be able to map out the location of every protein in a cell.

This is a long-term problem. It's going to be something that we're going to need to be working on for 10 or 15 years. The way that I think about this as an engineer is if you're trying to get, write some code and get it to work but you don't have the ability to debug it and step through line by line, how it's going and seeing how things are interacting, it just takes you a long time -- you're guessing.

And so having that tool of being able to see an immune cell interact with something that's trying to fight or watch cells replicate live or watch proteins interact inside cells live, I think there can be really valuable tools as just examples for scientists to be able to test different hypotheses and have a deeper understanding of how this worked.

Another area that you've also delved into is this Kempner Institute, really a bio-inspired AI where you're going back and forth between natural human intelligence and artificial intelligence, maybe you can talk a bit about that?

The idea there is basically to study the foundational basis of intelligence by studying at the same time machine learning and the advances that are made there and biological intelligence and the crossover between the two and trying to basically understand a little more of a theoretical foundation for this, because in all machine learning work that we do it's a highly empirical field.

But when you get down to it at a fundamental level people don't really understand how this works, which is kind of a funny place to be in where you can tinker with it and get it to work better and it's fairly predictable in terms of how it works but you want to understand the principles underneath it. And at least I have this belief that if you do understand the principles then you can make even faster progress and make sure that you're pointing it in a direction that will generally be good for humanity and the world.

So that's the goal of this center is basically, there's a lot of great work that can be done in AI that's just focused on the computational and machine learning side, but there is a space in the field to study the crossover with neuroscience and biological intelligence and I think that, to some degree, the advances in AI not only will give us tools to study all the neuroscience and other things but I think it'll also help us understand the way our brains work and hopefully vice versa in order to do a better job of building this.

Yeah, I think with our increasing understanding of genetics and how genetics impact human disease, we still make a huge leap when we go from genetic change to clinical phenotype. There's a huge gap of what's going on. And we make a lot of assumptions or correlations of like, we think we see this, we think this happens, but I think what we're trying to do with our strategy in the next 10 years is actually get a sense of like, there's a ton of proteins molecular pathways that all fire when something changes.

And to the human eye or to even the brightest of scientists, it's just chaos, right?

Right.

And so you can look at it but it looks like chaos. But if you take computation in the advances that computation have promised for the field, you can bring order to it. You can understand what is actually the perturbation that happened that may or may not be associated with the phenotype, what is actually the molecular phenotype of a disease, which brings us so much closer to being able to adjust for it or actually address the change.

Yeah, no, you got a lot there. I mean, it's an impressive way to move this field forward. And the other thing that you've also incorporated besides this pan-disciplinary model is actually getting patient input. So it isn't just human biology that's out there in some siloed way, you're actually getting patient engagement.

I think that's really laudable and we never can do enough of that because we're ultimately trying to cure and prevent these diseases and if you don't have the patients involved, it's missing a major piece.

Yeah. The patient work is incredibly important. If we go back to the culture of science, I think making sure that patients have a voice and helping drive and set the research agenda is really important. I went to one of our early neurodegeneration conferences and I heard a patient with Parkinson's say, everyone thinks about the tremor and yeah, the tremor is there, but you know what really bothers me, it's like I'm so tired. I just don't have the energy.

And that's a really important insight. I think increasingly having patients engaged in your research actually just makes your research go faster. Especially in rare disease, unless you are engaging with patients more broadly, you really only have the few patients that come in that live close by to an academic center. And you also actually with an engaged patient help you understand new paradigms of medicine. And so I think that's important.

First of all, rare disease is not rare. There's lots of people with a rare disease. I think as we increasingly move down the path of precision medicine, diseases that we lump together today -- depression, high blood pressure, are actually all can be broken down into more precise diagnoses. And when you think about it, if you are able to study the whole human spectrum a lot of interesting biological insights come out of it.

Some thoughts about where this is going. So one of the things that would help people at the individual level is if they had a virtual health coach that is their phone talked to them and told them they know they're at whatever risk of a condition and it prevented that from ever happening -- the fantasy in medicine that we've never actualized.

This takes multimodal AI. This is going to be a long road, but do you think it's going to be the case that someday we will have guidance for those who are willing to prevent --

I'm optimistic about that. This is something that we talk about a lot. This is actually the first conversation that you and I had a number of years ago is you're talking about- - and this really inspired me and I think probably set us in some of the direction that we're going in now but the ability to basically have something that is relatively non-invasive or something that you could put inside yourself but could help you measure your health and just instrument things on an ongoing basis and you can wave a wand over it and get a readout.

There are a bunch of technical problems to solve to do something like that. There are a bunch of regulatory and different challenges that you need to make sure we work through the process to make sure it's safe. But it's an interesting area for research. There's quite a spectrum of tools that I think need to get built. So the imaging stuff that we're doing is really quite far down the path of scientific research tools.

I know there are other tools that will be helpful for helping to cure, prevent, and manage diseases that might be a little bit more clinical over time. Today we're a little bit more focused on the research side, but some of these things have crossover value in terms of people, especially like you were talking about with rare diseases, you have people who are particularly motivated to try new tools or approaches and that in turn gives the researchers and the doctors more data on how to approach things.

But, I don't know, I'm pretty optimistic about what you're talking about. I'm not sure exactly when that will come, but I do think it just seems like the field is steadily solving the problems that would stand in the way of things like that being able to exist.

Well, I think part of doing that is in over the course of the day our bodies are so dynamic it's actually understanding the full spectrum of normal human physiology. And so a lot of the work that we're doing, even around the single-cell work, and imaging is explaining what is even possible, what is the full range of normal and what are variants that are of no concern, and what are the variants of concern.

And I've had to train myself to take off my physician hat because I'm like, as a physician, I only want the data if I know what I'm going to do with it. As a researcher, I think it is very important to understand the full range of the human experience to be able to then build those tools.

And I will say one thing that I'm acutely aware of in biomedical research is that a lot of folks aren't represented in the research. I think right now if you just look at who participates in the research, it's predominantly Caucasian men in their middle ages, and so you're leaving out a lot of folks. I think being a woman is not a rare disease, so we should be able to understand how a woman's body changes and evolves over the course of her lifetime.

People of color are dramatically underrepresented in our research base. Very close to my heart -- we have no idea what's going on with kids. They're not just little adults. And so really making sure that as we build this base, a very important reference on which we want to be able to build the next generation of medicine, we just need to make sure that people are fully represented and we can actually reference back to their biology, not abstraction of a relatively small subset of people.

Certainly, I completely concur with the importance of these diversity, equity, inclusion features that you've been really advocating at CZI, at the bio hub, everything that you've been doing. One of the things that is really extraordinary about this time that we live in is that these advances are occurring and it seems like, for example, the mRNA vaccines -- oh, well, they just took 10 months. Well, they took 30 years.

You see cancer immunotherapy, and you say, oh, well, now this is really great for certain types of cancer, but it took 30 years. So what is impressive here is the long view that you've basically devoted these first 5 years, so some building blocks. And as you said you're starting to get some yardsticks, some measurements of how you can develop milestones for the future, but you're not trying to say that there's going to be breakthroughs in 10 months.

And maybe you can just speak to that because you're thinking about your grandchildren and where this is all going to land in many decades from now, right?

Overnight successes take a lot of work. And so a lot goes into every single breakthrough that happens overnight.

MARK ZUCKERBERG: For us and our approach here, I'd say part of this is we're lucky in that and that we're relatively young in doing this work. So we can easily have an outlook, hoping that we're going to get to do this work for many, many decades.

So I think that's partially a feature of starting sooner rather than waiting until our careers were further along to start with philanthropy -- but that's one piece. And then the other is just looking at the landscape of funding for science overall.

If you were looking at what should the portfolio be of scientific investments, I think you'd want some amount that's just a base that's spread pretty broadly. But then I think that you'd also want a small number of projects that are relatively concentrated but bigger and larger investments.

In the field, one of the things that I'm excited about is there are starting to be more people who are funding work like this, and I think that's really exciting too. But at least when we were getting started, that seemed like there was a little bit of a gap there. So we'll keep on evolving our approach and just seeing what it looks like the overall portfolio of the country or the world scientific investment is and where it looks like -- there might be gaps.

But we're very grateful for the work that everyone else is doing in the field. And just because other people are taking different approaches it doesn't mean that we think that that's wrong. I think that a lot of the fact that we're taking this approach is because some of the other approaches that are in some ways even more important are already handled, so it opens up space to try different things.

We are indebted to you-- that is the biomedical community for your investment in us. We hope that we're going to come through to achieve that goal. I don't know what will happen.

Me neither. That's the good part, though.

If we actually prevent, cure, and manage all diseases by the end of the century, then what?

Deep existential questions.

MARK ZUCKERBERG: Although there's always going to be a next thing. But I think this is a good one to work on.

Terrific. Thanks very much.

Thank you for everything that you do.

Thank you.

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