Everything Priscilla Chan said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Priscilla Chan: Medicine currently lacks mechanistic understanding and relies on trial-and-error
“We really have no mechanistic understanding. We're saying, like, okay, you're kind of like these people that we studied, and this drug kind of impacts the pathway that we think is implicated. Let's try and see if anything happens. And time passes, and sometime…”
Chan: AI models will evaluate genetic variants of unknown significance
“And what you really want to do, and I think these models will be able to do is look at those variants and actually model out what is the impact in the different cells, how it influences cellular behavior and whether or not that is Tied to a pathway to disease …”
Chan: Scientists thought CZI's goal to cure all disease was crazy
“When we first set out that, the goal to cure and prevent disease by the end of the century, people, like, honestly, Most scientists couldn't look at us with a straight face. And they're like, you're crazy. Yes. And it was true because if you just decided to sp…”
Chan: Most medical conditions should be treated as rare diseases
“And so those are rare, like, and, but I really think most diseases should be thought of as rare diseases. Because each one of our biology is different.”
Chan: CZI built a 1,000-GPU cluster and plans a 10,000-GPU expansion
“We were the first to really build a large-scale compute cluster. A thousand now where we have plans to move to the 10,000 range.”
Chan: Curing disease requires uniting academia and industry via non-profit neutrality
“The sort of neutral nonprofit nature of our work actually helps harness more people to enter this effort. And to actually achieve the mission of, like, understanding the totality of human biology and to cure, prevent, manage all diseases, you actually do need …”
Chan: Single-Cell Atlases Enable Pre-Trial Prediction of Off-Target Drug Toxicity
“If you have a single cell atlas that looks at all the different cell types some of which actually were not predicted before we modeled them, you can start looking at which cells actually do have receptors for the target you thought you were exclusively targeti…”
Chan: Self-Organized Patient Cohorts Advanced Gene Therapy in Under Five Years
“There's gene therapy that one disease group has moved forward over the course of, like, I want to say, like, three to five years rather than decades, and the speed is so fast. Because the patients themselves have organized the resources that a scientist or a c…”
Chan: Philanthropies lack the clear performance dashboards companies use
“And the thing that in running a philanthropy, I'm incredibly envious of people who run companies is that like you guys can have a dashboard and there's like financial results and people tell you if you're on the right track on the wrong track and there's clari…”
Chan: Connecting AI researchers to wet-lab data collectors improves AI models
“Data is not just data. You guys know this, like you need to know sort of how the data was collected and from where and being able to connect the AI researchers to the folks who are actually gathering the data on a daily basis makes their work better.”
Chan: CZI Billion Cell Project takes months at fraction of historical cost
“Now we're doing the billion cell project and that is taking months and at a fraction of the price.”
Chan: Science has examined only a fraction of billions of human cell types
“We know there are billions of cell types in a human, and we've only truly looked at a fraction of them, and we looked at it in largely healthy cells.”
Chan: Predictive AI will de-risk bold, high-risk biological hypotheses
“Right now, because the wet lab is so expensive and relatively slow compared to sort of Computational experimentation. Like people are choosing like, I need something to hit. So people are going for hypotheses or ideas that are like, you know to use a sports an…”
Chan: CZ Biohub NY engineers immune cells to detect heart plaques
“And our New York biohub, we're doing cellular engineering to say like, Hey, can you go in to this person's heart? Check if they have plaques that are causing problems, read it into your DNA, self lice, And then we can read out the signal as cell-free DNA and g…”
Chan: LLMs provided the breakthrough needed to analyze CZI's biological datasets
“We were already Building tools to measure interesting data. Building the data sets. But we didn't really know what to do with them yet. And large language models coming onto the scene, we're like, wow, we can make sense of all of this now.”
Chan: Virtual cell models provide utility even without perfect accuracy
“But I don't think it needs to be a hundred percent accurate to be useful. Because you just want to be able to de-risk the idea on the front end a little bit. And the more and more you de-risk it, the more efficient it gets, obviously. But it'll be useful if yo…”
Chan: CZI is consolidating biohubs and AI teams into one philanthropy
“Under Alex's leadership, we are going to come together as the biohub, a an operating philanthropy where we are doing the science,”
Priscilla Chan: Cell by Gene powers many transcriptomic-based biological models
“And now Cell by Gene is a corpus of knowledge that a lot of the transcriptomic-based models are based off of and is used regularly by the scientific community.”
Chan: CELLxGENE corpus reached 125M cells with 75% community contribution
“It took us about 10 years to get to a place where we had, we now have one of the largest corpus of RNA transcriptones, a hundred and twenty-five million cells. Cost a lot of money. And the really cool thing we discovered through that process was if we could se…”
Chan: How CZI selects 10-to-15-year scientific Grand Challenges
“When we looked at the Grand Challenges for, on the 10 to fifteen-year time horizon, it needs to be, like, when you look at it, you're like, I see a path. Not everything needs to be solved for us to take it on. In fact, if everything's solved, then that feels l…”
Chan details the specific research focuses of CZI's three Biohubs
“We have three biohubs. We have one in San Francisco, one in Chicago, one in New York. The one in New York works on cell engineering. You know, can we engineer cells To go in and detect signals, read it out, or to take certain actions. In Chicago, we're buildin…”
Chan: CZI funded 25% of CellbyGene, while the community provided 75%
“We only funded about 75% of it. Sorry, that's wrong. We've only funded 25% of it. 75% came from the broader community saying, this is useful, and there's an easy way for us to standardize and build this together.”
Priscilla Chan: Human Cell Atlas is one of the largest single-cell transcriptome databases
“Us funding the Human Cell Atlas, which is now one of the largest databases of single-cell transcriptomes.”