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Ground Truths

Podcast Ground Truths
Eric Topol
Facts, data, and analytics about biomedical matters. erictopol.substack.com

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  • The Holy Grail of Biology
    “Eventually, my dream would be to simulate a virtual cell.”—Demis HassabisThe aspiration to build the virtual cell is considered to be equivalent to a moonshot for digital biology. Recently, 42 leading life scientists published a paper in Cell on why this is so vital, and how it may ultimately be accomplished. This conversation is with 2 of the authors, Charlotte Bunne, now at EPFL and Steve Quake, a Professor at Stanford University, who heads up science at the Chan-Zuckerberg Initiative The audio (above) is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.TRANSCRIPT WITH LINKS TO AUDIO Eric Topol (00:06):Hello, it's Eric Topol with Ground Truths and we've got a really hot topic today, the virtual cell. And what I think is extraordinarily important futuristic paper that recently appeared in the journal Cell and the first author, Charlotte Bunne from EPFL, previously at Stanford’s Computer Science. And Steve Quake, a young friend of mine for many years who heads up the Chan Zuckerberg Initiative (CZI) as well as a professor at Stanford. So welcome, Charlotte and Steve.Steve Quake (00:42):Thanks, Eric. It's great to be here.Charlotte Bunne:Thanks for having me.Eric Topol (00:45):Yeah. So you wrote this article that Charlotte, the first author, and Steve, one of the senior authors, appeared in Cell in December and it just grabbed me, “How to build the virtual cell with artificial intelligence: Priorities and opportunities.” It's the holy grail of biology. We're in this era of digital biology and as you point out in the paper, it's a convergence of what's happening in AI, which is just moving at a velocity that's just so extraordinary and what's happening in biology. So maybe we can start off by, you had some 42 authors that I assume they congregated for a conference or something or how did you get 42 people to agree to the words in this paper?Steve Quake (01:33):We did. We had a meeting at CZI to bring community members together from many different parts of the community, from computer science to bioinformatics, AI experts, biologists who don't trust any of this. We wanted to have some real contrarians in the mix as well and have them have a conversation together about is there an opportunity here? What's the shape of it? What's realistic to expect? And that was sort of the genesis of the article.Eric Topol (02:02):And Charlotte, how did you get to be drafting the paper?Charlotte Bunne (02:09):So I did my postdoc with Aviv Regev at Genentech and Jure Leskovec at CZI and Jure was part of the residency program of CZI. And so, this is how we got involved and you had also prior work with Steve on the universal cell embedding. So this is how everything got started.Eric Topol (02:29):And it's actually amazing because it's a who's who of people who work in life science, AI and digital biology and omics. I mean it's pretty darn impressive. So I thought I'd start off with a quote in the article because it kind of tells a story of where this could go. So the quote was in the paper, “AIVC (artificial intelligence virtual cell) has the potential to revolutionize the scientific process, leading to future breakthroughs in biomedical research, personalized medicine, drug discovery, cell engineering, and programmable biology.” That's a pretty big statement. So maybe we can just kind of toss that around a bit and maybe give it a little more thoughts and color as to what you were positing there.Steve Quake (03:19):Yeah, Charlotte, you want me to take the first shot at that? Okay. So Eric, it is a bold claim and we have a really bold ambition here. We view that over the course of a decade, AI is going to provide the ability to make a transformative computational tool for biology. Right now, cell biology is 90% experimental and 10% computational, roughly speaking. And you've got to do just all kinds of tedious, expensive, challenging lab work to get to the answer. And I don't think AI is going to replace that, but it can invert the ratio. So within 10 years I think we can get to biology being 90% computational and 10% experimental. And the goal of the virtual cell is to build a tool that'll do that.Eric Topol (04:09):And I think a lot of people may not understand why it is considered the holy grail because it is the fundamental unit of life and it's incredibly complex. It's not just all the things happening in the cell with atoms and molecules and organelles and everything inside, but then there's also the interactions the cell to other cells in the outside tissue and world. So I mean it's really quite extraordinary challenge that you've taken on here. And I guess there's some debate, do we have the right foundation? We're going to get into foundation models in a second. A good friend of mine and part of this whole I think process that you got together, Eran Segal from Israel, he said, “We're at this tipping point…All the stars are aligned, and we have all the different components: the data, the compute, the modeling.” And in the paper you describe how we have over the last couple of decades have so many different data sets that are rich that are global initiatives. But then there's also questions. Do we really have the data? I think Bo Wang especially asked about that. Maybe Charlotte, what are your thoughts about data deficiency? There's a lot of data, but do you really have what we need before we bring them all together for this kind of single model that will get us some to the virtual cell?Charlotte Bunne (05:41):So I think, I mean one core idea of building this AIVC is that we basically can leverage all experimental data that is overall collected. So this also goes back to the point Steve just made. So meaning that we basically can integrate across many different studies data because we have AI algorithms or the architectures that power such an AIVC are able to integrate basically data sets on many different scales. So we are going a bit away from this dogma. I'm designing one algorithm from one dataset to this idea of I have an architecture that can take in multiple dataset on multiple scales. So this will help us a bit in being somewhat efficient with the type of experiments that we need to make and the type of experiments we need to conduct. And again, what Steve just said, ultimately, we can very much steer which data sets we need to collect.Charlotte Bunne (06:34):Currently, of course we don't have all the data that is sufficient. I mean in particular, I think most of the tissues we have, they are healthy tissues. We don't have all the disease phenotypes that we would like to measure, having patient data is always a very tricky case. We have mostly non-interventional data, meaning we have very limited understanding of somehow the effect of different perturbations. Perturbations that happen on many different scales in many different environments. So we need to collect a lot here. I think the overall journey that we are going with is that we take the data that we have, we make clever decisions on the data that we will collect in the future, and we have this also self-improving entity that is aware of what it doesn't know. So we need to be able to understand how well can I predict something on this somewhat regime. If I cannot, then we should focus our data collection effort into this. So I think that's not a present state, but this will basically also guide the future collection.Eric Topol (07:41):Speaking of data, one of the things I think that's fascinating is we saw how AlphaFold2 really revolutionized predicting proteins. But remember that was based on this extraordinary resource that had been built, the Protein Data Bank that enabled that. And for the virtual cell there's no such thing as a protein data bank. It's so much more as you emphasize Charlotte, it's so much dynamic and these perturbations that are just all across the board as you emphasize. Now the human cell atlas, which currently some tens of millions, but going into a billion cells, we learned that it used to be 200 cell types. Now I guess it's well over 5,000 and that we have 37 trillion cells approximately in the average person adult's body is a formidable map that's being made now. And I guess the idea that you're advancing is that we used to, and this goes back to a statement you made earlier, Steve, everything we did in science was hypothesis driven. But if we could get computational model of the virtual cell, then we can have AI exploration of the whole field. Is that really the nuts of this?Steve Quake (09:06):Yes. A couple thoughts on that, maybe Theo Karaletsos, our lead AI person at CZI says machine learning is the formalism through which we understand high dimensional data and I think that's a very deep statement. And biological systems are intrinsically very high dimensional. You've got 20,000 genes in the human genome in these cell atlases. You're measuring all of them at the same time in each single cell. And there's a lot of structure in the relationships of their gene expression there that is just not evident to the human eye. And for example, CELL by GENE, our database that collects all the aggregates, all of the single cell transcriptomic data is now over a hundred million cells. And as you mentioned, we're seeing ways to increase that by an order of magnitude in the near future. The project that Jure Leskovec and I worked on together that Charlotte referenced earlier was like a first attempt to build a foundational model on that data to discover some of the correlations and structure that was there.Steve Quake (10:14):And so, with a subset, I think it was the 20 or 30 million cells, we built a large language model and began asking it, what do you understand about the structure of this data? And it kind of discovered lineage relationships without us teaching it. We trained on a matrix of numbers, no biological information there, and it learned a lot about the relationships between cell type and lineage. And that emerged from that high dimensional structure, which was super pleasing to us and really, I mean for me personally gave me the confidence to say this stuff is going to work out. There is a future for the virtual cell. It's not some made up thing. There is real substance there and this is worth investing an enormous amount of CZIs resources in going forward and trying to rally the community around as a project.Eric Topol (11:04):Well yeah, the premise here is that there is a language of life, and you just made a good case that there is if you can predict, if you can query, if you can generate like that. It is reminiscent of the famous Go game of Lee Sedol, that world champion and how the machine came up with a move (Move 37) many, many years ago that no human would've anticipated and I think that's what you're getting at. And the ability for inference and reason now to add to this. So Charlotte, one of the things of course is about, well there's two terms in here that are unfamiliar to many of the listeners or viewers of this podcast, universal representations (UR) and virtual instrument (VIs) that you make a pretty significant part of how you are going about this virtual cell model. So could you describe that and also the embeddings as part of the universal representation (UR) because I think embeddings, or these meaningful relationships are key to what Steve was just talking about.Charlotte Bunne (12:25):Yes. So in order to somewhat leverage very different modalities in order to leverage basically modalities that will take measurements across different scales, like the idea is that we have large, may it be transformer models that might be very different. If I have imaging data, I have a vision transformer, if I have a text data, I have large language models that are designed of course for DNA then they have a very wide context and so on and so forth. But the idea is somewhat that we have models that are connected through the scales of biology because those scales we know. We know which components are somewhat involved or in measurements that are happening upstream. So we have the somewhat interconnection or very large model that will be trained on many different data and we have this internal model representation that somewhat capture everything they've seen. And so, this is what we call those universal representation (UR) that will exist across the scales of biology.Charlotte Bunne (13:22):And what is great about AI, and so I think this is a bit like a history of AI in short is the ability to predict the last years, the ability to generate, we can generate new hypothesis, we can generate modalities that we are missing. We can potentially generate certain cellular state, molecular state have a certain property, but I think what's really coming is this ability to reason. So we see this in those very large language models, the ability to reason about a hypothesis, how we can test it. So this is what those instruments ultimately need to do. So we need to be able to simulate the change of a perturbation on a cellular phenotype. So on the internal representation, the universal representation of a cell state, we need to simulate the fact the mutation has downstream and how this would propagate in our representations upstream. And we need to build many different type of virtual instruments that allow us to basically design and build all those capabilities that ultimately the AI virtual cell needs to possess that will then allow us to reason, to generate hypothesis, to basically predict the next experiment to conduct to predict the outcome of a perturbation experiment to in silico design, cellular states, molecular states, things like that. And this is why we make the separation between internal representation as well as those instruments that operate on those representations.Eric Topol (14:47):Yeah, that's what I really liked is that you basically described the architecture, how you're going to do this. By putting these URs into the VIs, having a decoder and a manipulator and you basically got the idea if you can bring all these different integrations about which of course is pending. Now there are obviously many naysayers here that this is impossible. One of them is this guy, Philip Ball. I don't know if you read the language, How Life Works. Now he's a science journalist and he's a prolific writer. He says, “Comparing life to a machine, a robot, a computer, sells it short. Life is a cascade of processes, each with a distinct integrity and autonomy, the logic of which has no parallel outside the living world.” Is he right? There's no way to model this. It's silly, it's too complex.Steve Quake (15:50):We don't know, alright. And it's great that there's naysayers. If everyone agreed this was doable, would it be worth doing? I mean the whole point is to take risks and get out and do something really challenging in the frontier where you don't know the answer. If we knew that it was doable, I wouldn't be interested in doing it. So I personally am happy that there's not a consensus.Eric Topol (16:16):Well, I mean to capture people's imagination here, if you're successful and you marshal a global effort, I don't know who's going to pay for it because it's a lot of work coming here going forward. But if you can do it, the question here is right today we talk about, oh let's make an organoid so we can figure out how to treat this person's cancer or understand this person's rare disease or whatever. And instead of having to wait weeks for this culture and all the expense and whatnot, you could just do it in a computer and in silico and you have this virtual twin of a person's cells and their tissue and whatnot. So the opportunity here is, I don't know if people get, this is just extraordinary and quick and cheap if you can get there. And it's such a bold initiative idea, who will pay for this do you think?Steve Quake (17:08):Well, CZI is putting an enormous amount of resources into it and it's a major project for us. We have been laying the groundwork for it. We recently put together what I think is if not the largest, one of the largest GPU supercomputer clusters for nonprofit basic science research that came online at the end of last year. And in fact in December we put out an RFA for the scientific community to propose using it to build models. And so we're sharing that resource within the scientific community as I think you appreciate, one of the real challenges in the field has been access to compute resources and industry has it academia at a much lower level. We are able to be somewhere in between, not quite at the level of a private company but the tech company but at a level beyond what most universities are being able to do and we're trying to use that to drive the field forward. We're also planning on launching RFAs we this year to help drive this project forward and funding people globally on that. And we are building a substantial internal effort within CZI to help drive this project forward.Eric Topol (18:17):I think it has the looks of the human genome project, which at time as you know when it was originally launched that people thought, oh, this is impossible. And then look what happened. It got done. And now the sequence of genome is just a commodity, very relatively, very inexpensive compared to what it used to be.Steve Quake (18:36):I think a lot about those parallels. And I will say one thing, Philip Ball, I will concede him the point, the cells are very complicated. The genome project, I mean the sort of genius there was to turn it from a biology problem to a chemistry problem, there is a test tube with a chemical and it work out the structure of that chemical. And if you can do that, the problem is solved. I think what it means to have the virtual cell is much more complex and ambiguous in terms of defining what it's going to do and when you're done. And so, we have our work cut out for us there to try to do that. And that's why a little bit, I established our North Star and CZI for the next decade as understanding the mysteries of the cell and that word mystery is very important to me. I think the molecules, as you pointed out earlier are understood, genome sequenced, protein structure solved or predicted, we know a lot about the molecules. Those are if not solved problems, pretty close to being solved. And the real mystery is how do they work together to create life in the cell? And that's what we're trying to answer with this virtual cell project.Eric Topol (19:43):Yeah, I think another thing that of course is happening concurrently to add the likelihood that you'll be successful is we've never seen the foundation models coming out in life science as they have in recent weeks and months. Never. I mean, I have a paper in Science tomorrow coming out summarizing the progress about not just RNA, DNA, ligands. I mean the whole idea, AlphaFold3, but now Boltz and so many others. It's just amazing how fast the torrent of new foundation models. So Charlotte, what do you think accounts for this? This is unprecedented in life science to see foundation models coming out at this clip on evolution on, I mean you name it, design of every different molecule of life or of course in cells included in that. What do you think is going on here?Charlotte Bunne (20:47):So on the one hand, of course we benefit profits and inherit from all the tremendous efforts that have been made in the last decades on assembling those data sets that are very, very standardized. CELLxGENE is very somehow AI friendly, as you can say, it is somewhat a platform that is easy to feed into algorithms, but at the same time we actually also see really new building mechanisms, design principles of AI algorithms in itself. So I think we have understood that in order to really make progress, build those systems that work well, we need to build AI tools that are designed for biological data. So to give you an easy example, if I use a large language model on text, it's not going to work out of the box for DNA because we have different reading directions, different context lens and many, many, many, many more.Charlotte Bunne (21:40):And if I look at standard computer vision where we can say AI really excels and I'm applying standard computer vision, vision transformers on multiplex images, they're not going to work because normal computer vision architectures, they always expect the same three inputs, RGB, right? In multiplex images, I'm measuring up to 150 proteins potentially in a single experiment, but every study will measure different proteins. So I deal with many different scales like larger scales and I used to attention mechanisms that we have in usual computer vision. Transformers are not going to work anymore, they're not going to scale. And at the same time, I need to be completely flexible in whatever input combination of channel I'm just going to face in this experiment. So this is what we right now did for example, in our very first work, inheriting the design principle that we laid out in the paper AI virtual cell and then come up with new AI architectures that are dealing with these very special requirements that biological data have.Charlotte Bunne (22:46):So we have now a lot of computer scientists that work very, very closely have a very good understanding of biologists. Biologists that are getting much and much more into the computer science. So people who are fluent in both languages somewhat, that are able to now build models that are adopted and designed for biological data. And we don't just take basically computer vision architectures that work well on street scenes and try to apply them on biological data. So it's just a very different way of thinking about it, starting constructing basically specialized architectures, besides of course the tremendous data efforts that have happened in the past.Eric Topol (23:24):Yeah, and we're not even talking about just sequence because we've also got imaging which has gone through a revolution, be able to image subcellular without having to use any types of stains that would disrupt cells. That's another part of the deep learning era that came along. One thing I thought was fascinating in the paper in Cell you wrote, “For instance, the Short Read Archive of biological sequence data holds over 14 petabytes of information, which is 1,000 times larger than the dataset used to train ChatGPT.” I mean that's a lot of tokens, that's a lot of stuff, compute resources. It's almost like you're going to need a DeepSeek type of way to get this. I mean not that DeepSeek as its claim to be so much more economical, but there's a data challenge here in terms of working with that massive amount that is different than the human language. That is our language, wouldn't you say?Steve Quake (24:35):So Eric, that brings to mind one of my favorite quotes from Sydney Brenner who is such a wit. And in 2000 at the sort of early first flush of success in genomics, he said, biology is drowning in a sea of data and starving for knowledge. A very deep statement, right? And that's a little bit what the motivation was for putting the Short Read Archive statistic into the paper there. And again, for me, part of the value of this endeavor of creating a virtual cell is it's a tool to help us translate data into knowledge.Eric Topol (25:14):Yeah, well there's two, I think phenomenal figures in your Cell paper. The first one that kicks across the capabilities of the virtual cell and the second that compares the virtual cell to the real or the physical cell. And we'll link that with this in the transcript. And the other thing we'll link is there's a nice Atlantic article, “A Virtual Cell Is a ‘Holy Grail’ of Science. It's Getting Closer.” That might not be quite close as next week or year, but it's getting close and that's good for people who are not well grounded in this because it's much more taken out of the technical realm. This is really exciting. I mean what you're onto here and what's interesting, Steve, since I've known you for so many years earlier in your career you really worked on omics that is being DNA and RNA and in recent times you've made this switch to cells. Is that just because you're trying to anticipate the field or tell us a little bit about your migration.Steve Quake (26:23):Yeah, so a big part of my career has been trying to develop new measurement technologies that'll provide insight into biology. And decades ago that was understanding molecules. Now it's understanding more complex biological things like cells and it was like a natural progression. I mean we built the sequencers, sequenced the genomes, done. And it was clear that people were just going to do that at scale then and create lots of data. Hopefully knowledge would get out of that. But for me as an academic, I never thought I'd be in the position I'm in now was put it that way. I just wanted to keep running a small research group. So I realized I would have to get out of the genome thing and find the next frontier and it became this intersection of microfluidics and genomics, which as you know, I spent a lot of time developing microfluidic tools to analyze cells and try to do single cell biology to understand their heterogeneity. And that through a winding path led me to all these cell atlases and to where we are now.Eric Topol (27:26):Well, we're fortunate for that and also with your work with CZI to help propel that forward and I think it sounds like we're going to need a lot of help to get this thing done. Now Charlotte, as a computer scientist now at EPFL, what are you going to do to keep working on this and what's your career advice for people in computer science who have an interest in digital biology?Charlotte Bunne (27:51):So I work in particular on the prospect of using this to build diagnostic tools and to make diagnostics in the clinic easier because ultimately we have somewhat limited capabilities in the hospital to run deep omics, but the idea of being able to somewhat map with a cheaper and lighter modality or somewhat diagnostic test into something much richer because a model has been seeing all those different data and can basically contextualize it. It's very interesting. We've seen all those pathology foundation models. If I can always run an H&E, but then decide when to run deeper diagnostics to have a better or more accurate prediction, that is very powerful and it's ultimately reducing the costs, but the precision that we have in hospitals. So my faculty position right now is co-located between the School of Life Sciences, School of Computer Science. So I have a dual affiliation and I'm affiliated to the hospitals to actually make this possible and as a career advice, I think don't be shy and stick to your discipline.Charlotte Bunne (28:56):I have a bachelor's in biology, but I never only did biology. I have a PhD in computer science, which you would think a bachelor in biology not necessarily qualifies you through. So I think this interdisciplinarity also requires you to be very fluent, very comfortable in reading many different styles of papers and publications because a publication in a computer science venue will be very, very different from the way we write in biology. So don't stick to your study program, but just be free in selecting whatever course gets you closer to the knowledge you need in order to do the research or whatever task you are building and working on.Eric Topol (29:39):Well, Charlotte, the way you're set up there with this coalescence of life science and computer science is so ideal and so unusual here in the US, so that's fantastic. That's what we need and that's really the underpinning of how you're going to get to the virtual cells, getting these two communities together. And Steve, likewise, you were an engineer and somehow you became one of the pioneers of digital biology way back before it had that term, this interdisciplinary, transdisciplinary. We need so much of that in order for you all to be successful, right?Steve Quake (30:20):Absolutely. I mean there's so much great discovery to be done on the boundary between fields. I trained as a physicist and kind of made my career this boundary between physics and biology and technology development and it's just sort of been a gift that keeps on giving. You've got a new way to measure something, you discover something new scientifically and it just all suggests new things to measure. It's very self-reinforcing.Eric Topol (30:50):Now, a couple of people who you know well have made some pretty big statements about this whole era of digital biology and I think the virtual cell is perhaps the biggest initiative of all the digital biology ongoing efforts, but Jensen Huang wrote, “for the first time in human history, biology has the opportunity to be engineering, not science.” And Demis Hassabis wrote or said, ‘we're seeing engineering science, you have to build the artifact of interest first, and then once you have it, you can use the scientific method to reduce it down and understand its components.’ Well here there's a lot to do to understand its components and if we can do that, for example, right now as both of AI drug discoveries and high gear and there's umpteen numbers of companies working on it, but it doesn't account for the cell. I mean it basically is protein, protein ligand interactions. What if we had drug discovery that was cell based? Could you comment about that? Because that doesn't even exist right now.Steve Quake (32:02):Yeah, I mean I can say something first, Charlotte, if you've got thoughts, I'm curious to hear them. So I do think AI approaches are going to be very useful designing molecules. And so, from the perspective of designing new therapeutics, whether they're small molecules or antibodies, yeah, I mean there's a ton of investment in that area that is a near term fruit, perfect thing for venture people to invest in and there's opportunity there. There's been enough proof of principle. However, I do agree with you that if you want to really understand what happens when you drug a target, you're going to want to have some model of the cell and maybe not just the cell, but all the different cell types of the body to understand where toxicity will come from if you have on-target toxicity and whether you get efficacy on the thing you're trying to do.Steve Quake (32:55):And so, we really hope that people will use the virtual cell models we're going to build as part of the drug discovery development process, I agree with you in a little of a blind spot and we think if we make something useful, people will be using it. The other thing I'll say on that point is I'm very enthusiastic about the future of cellular therapies and one of our big bets at CZI has been starting the New York Biohub, which is aimed at really being very ambitious about establishing the engineering and scientific foundations of how to engineer completely, radically more powerful cellular therapies. And the virtual cell is going to help them do that, right? It's going to be essential for them to achieve that mission.Eric Topol (33:39):I think you're pointing out one of the most important things going on in medicine today is how we didn't anticipate that live cell therapy, engineered cells and ideally off the shelf or in vivo, not just having to take them out and work on them outside the body, is a revolution ongoing, and it's not just in cancer, it's in autoimmune diseases and many others. So it's part of the virtual cell need. We need this. One of the things that's a misnomer, I want you both to comment on, we keep talking about single cell, single cell. And there's a paper spatial multi-omics this week, five different single cell scales all integrated. It's great, but we don't get to single cell. We're basically looking at 50 cells, 100 cells. We're not doing single cell because we're not going deep enough. Is that just a matter of time when we actually are doing, and of course the more we do get down to the single or a few cells, the more insights we're going to get. Would you comment about that? Because we have all this literature on single cell comes out every day, but we're not really there yet.Steve Quake (34:53):Charlotte, do you want to take a first pass at that and then I can say something?Charlotte Bunne (34:56):Yes. So it depends. So I think if we look at certain spatial proteomics, we still have subcellular resolutions. So of course, we always measure many different cells, but we are able to somewhat get down to resolution where we can look at certain colocalization of proteins. This also goes back to the point just made before having this very good environment to study drugs. If I want to build a new drug, if I want to build a new protein, the idea of building this multiscale model allows us to actually simulate different, somehow binding changes and binding because we simulate the effect of a drug. Ultimately, the redouts we have they are subcellular. So of course, we often in the spatial biology, we often have a bit like methods that are rather coarse they have a spot that averages over certain some cells like hundreds of cells or few cells.Charlotte Bunne (35:50):But I think we also have more and more technologies that are zooming in that are subcellular where we can actually tag or have those probe-based methods that allow us to zoom in. There's microscopy of individual cells to really capture them in 3D. They are of course not very high throughput yet, but it gives us also an idea of the morphology and how ultimately morphology determine certain somehow cellular properties or cellular phenotype. So I think there's lots of progress also on the experimental and that ultimately will back feed into the AI virtual cell, those models that will be fed by those data. Similarly, looking at dynamics, right, looking at live imaging of individual cells of their morphological changes. Also, this ultimately is data that we'll need to get a better understanding of disease mechanisms, cellular phenotypes functions, perturbation responses.Eric Topol (36:47):Right. Yes, Steve, you can comment on that and the amazing progress that we have made with space and time, spatial temporal resolution, spatial omics over these years, but that we still could go deeper in terms of getting to individual cells, right?Steve Quake (37:06):So, what can we do with a single cell? I'd say we are very mature in our ability to amplify and sequence the genome of a single cell, amplify and sequence the transcriptome of a single cell. You can ask is one cell enough to make a biological conclusion? And maybe I think what you're referring to is people want to see replicates and so you can ask how many cells do you need to see to have confidence in any given biological conclusion, which is a reasonable thing. It's a statistical question in good science. I think I've been very impressed with how the mass spec people have been doing recently. I think they've finally cracked the ability to look at proteins from single cells and they can look at a couple thousand proteins. That was I think one of these Nature method of the year things at the end of last year and deep visual proteomics.Eric Topol (37:59):Deep visual proteomics, yes.Steve Quake (38:00):Yeah, they are over the hump. Yeah, they are over the hump with single cell measurements. Part of what's missing right now I think is the ability to reliably do all of that on the same cell. So this is what Charlotte was referring to be able to do sort of multi-modal measurements on single cells. That's kind of in its infancy and there's a few examples, but there's a lot more work to be done on that. And I think also the fact that these measurements are all destructive right now, and so you're losing the ability to look how the cells evolve over time. You've got to say this time point, I'm going to dissect this thing and look at a state and I don't get to see what happens further down the road. So that's another future I think measurement challenge to be addressed.Eric Topol (38:42):And I think I'm just trying to identify some of the multitude of challenges in this extraordinarily bold initiative because there are no shortage and that's good about it. It is given people lots of work to do to overcome, override some of these challenges. Now before we wrap up, besides the fact that you point out that all the work has to be done and be validated in real experiments, not just live in a virtual AI world, but you also comment about the safety and ethics of this work and assuming you're going to gradually get there and be successful. So could either or both of you comment about that because it's very thoughtful that you're thinking already about that.Steve Quake (41:10):As scientists and members of the larger community, we want to be careful and ensure that we're interacting with people who said policy in a way that ensures that these tools are being used to advance the cause of science and not do things that are detrimental to human health and are used in a way that respects patient privacy. And so, the ethics around how you use all this with respect to individuals is going to be important to be thoughtful about from the beginning. And I also think there's an ethical question around what it means to be publishing papers and you don't want people to be forging papers using data from the virtual cell without being clear about where that came from and pretending that it was a real experiment. So there's issues around those sorts of ethics as well that need to be considered.Eric Topol (42:07):And of those 40 some authors, do you around the world, do you have the sense that you all work together to achieve this goal? Is there kind of a global bonding here that's going to collaborate?Steve Quake (42:23):I think this effort is going to go way beyond those 40 authors. It's going to include a much larger set of people and I'm really excited to see that evolve with time.Eric Topol (42:31):Yeah, no, it's really quite extraordinary how you kick this thing off and the paper is the blueprint for something that we are all going to anticipate that could change a lot of science and medicine. I mean we saw, as you mentioned, Steve, how that deep visual proteomics (DVP) saved lives. It was what I wrote a spatial medicine, no longer spatial biology. And so, the way that this can change the future of medicine, I think a lot of people just have to have a little bit of imagination that once we get there with this AIVC, that there's a lot in store that's really quite exciting. Well, I think this has been an invigorating review of that paper and some of the issues surrounding it. I couldn't be more enthusiastic for your success and ultimately where this could take us. Did I miss anything during the discussion that we should touch on before we wrap up?Steve Quake (43:31):Not from my perspective. It was a pleasure as always Eric, and a fun discussion.Charlotte Bunne (43:38):Thanks so much.Eric Topol (43:39):Well thank you both and all the co-authors of this paper. We're going to be following this with the great interest, and I think for most people listening, they may not know that this is in store for the future. Someday we will get there. I think one of the things to point out right now is the models we have today that large language models based on transformer architecture, they're going to continue to evolve. We're already seeing so much in inference and ability for reasoning to be exploited and not asking for prompts with immediate answers, but waiting for days to get back. A lot more work from a lot more computing resources. But we're going to get models in the future to fold this together. I think that's one of the things that you've touched on the paper so that whatever we have today in concert with what you've laid out, AI is just going to keep getting better.Eric Topol (44:39):The biology that these foundation models are going to get broader and more compelling as to their use cases. So that's why I believe in this. I don't see this as a static situation right now. I just think that you're anticipating the future, and we will have better models to be able to integrate this massive amount of what some people would consider disparate data sources. So thank you both and all your colleagues for writing this paper. I don't know how you got the 42 authors to agree to it all, which is great, and it's just a beginning of something that's a new frontier. So thanks very much.Steve Quake (45:19):Thank you, Eric.**********************************************Thanks for listening, watching or reading Ground Truths. Your subscription is greatly appreciated.If you found this podcast interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths—newsletters, analyses, and podcasts—is free, open-access, with no ads..Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. And such support is becoming more vital In light of current changes of funding by US biomedical research at NIH and other governmental agencies.Thanks to my producer Jessica Nguyen and to Sinjun Balabanoff for audio and video support at Scripps Research. Get full access to Ground Truths at erictopol.substack.com/subscribe
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  • Public health in the US
    Thank you Katelyn Jetelina, Andy Meyers, Tracy Paeschke, MD, FACC, Bruce Lanphear, Tay MacIntyre, and many others for tuning into my live video with Katelyn Jetelina! Join me for my next live video in the app. Get full access to Ground Truths at erictopol.substack.com/subscribe
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  • Anna Greka: Molecular Sleuthing for Rare Diseases
    Funding for the NIH and US biomedical research is imperiled at a momentous time of progress. Exemplifying this is the work of Dr. Anna Greka, a leading physician-scientist at the Broad Institute who is devoted to unlocking the mysteries of rare diseases— that cumulatively affect 30 million Americans— and finding cures, science supported by the NIH.A clip from our conversationThe audio is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.Transcript with audio and external linksEric Topol (00:06):Well, hello. This is Eric Topol from Ground Truths, and I am really delighted to welcome today, Anna Greka. Anna is the president of the American Society for Clinical Investigation (ASCI) this year, a very prestigious organization, but she's also at Mass General Brigham, a nephrologist, a cell biologist, a physician-scientist, a Core Institute Member of the Broad Institute of MIT and Harvard, and serves as a member of the institute’s Executive Leadership Team. So we got a lot to talk about of all these different things you do. You must be pretty darn unique, Anna, because I don't know any cell biologists, nephrologists, physician-scientist like you.Anna Greka (00:48):Oh, thank you. It's a great honor to be here and glad to chat with you, Eric.Eric Topol (00:54):Yeah. Well, I had the real pleasure to hear you speak at a November conference, the AI for Science Forum, which we'll link to your panel. Where I was in a different panel, but you spoke about your extraordinary work and it became clear that we need to get you on Ground Truths, so you can tell your story to everybody. So I thought rather than kind of going back from the past where you were in Greece and somehow migrated to Boston and all that. We're going to get to that, but you gave an amazing TED Talk and it really encapsulated one of the many phenomenal stories of your work as a molecular sleuth. So maybe if you could give us a synopsis, and of course we'll link to that so people could watch the whole talk. But I think that Mucin-1 or MUC1, as you call it, discovery is really important to kind of ground our discussion.A Mysterious Kidney Disease Unraveled Anna Greka (01:59):Oh, absolutely. Yeah, it's an interesting story. In some ways, in my TED Talk, I highlight one of the important families of this story, a family from Utah, but there's also other important families that are also part of the story. And this is also what I spoke about in London when we were together, and this is really sort of a medical mystery that initially started on the Mediterranean island of Cyprus, where it was found that there were many families in which in every generation, several members suffered and ultimately died from what at the time was a mysterious kidney disease. This was more than 30 years ago, and it was clear that there was something genetic going on, but it was impossible to identify the gene. And then even with the advent of Next-Gen sequencing, this is what's so interesting about this story, it was still hard to find the gene, which is a little surprising.Anna Greka (02:51):After we were able to sequence families and identify monogenic mutations pretty readily, this was still very resistant. And then it actually took the firepower of the Broad Institute, and it's actually from a scientific perspective, an interesting story because they had to dust off the old-fashioned Sanger sequencing in order to get this done. But they were ultimately able to identify this mutation in a VNTR region of the MUC1 gene. The Mucin-1 gene, which I call a dark corner of the human genome, it was really, it's highly repetitive, very GC-rich. So it becomes very difficult to sequence through there with Next-Gen sequencing. And so, ultimately the mutation of course was found and it's a single cytosine insertion in a stretch of cytosines that sort of causes this frameshift mutation and an early stop codon that essentially results in a neoprotein like a toxic, what I call a mangled protein that sort of accumulates inside the kidney cells.Anna Greka (03:55):And that's where my sort of adventure began. It was Eric Lander’s group, who is the founding director of the Broad who discovered the mutation. And then through a conversation we had here in Boston, we sort of discovered that there was an opportunity to collaborate and so that’s how I came to the Broad, and that's the beginnings of this story. I think what's fascinating about this story though, that starts in a remote Mediterranean island and then turns out to be a disease that you can find in every continent all over the world. There are probably millions of patients with kidney disease in whom we haven't recognized the existence of this mutation. What's really interesting about it though is that what we discovered is that the mangled protein that's a result of this misspelling of this mutation is ultimately captured by a family of cargo receptors, they’re called the TMED cargo receptors and they end up sort of grabbing these misfolded proteins and holding onto them so tight that it's impossible for the cell to get rid of them.Anna Greka (04:55):And they become this growing heap of molecular trash, if you will, that becomes really hard to manage, and the cells ultimately die. So in the process of doing this molecular sleuthing, as I call it, we actually also identified a small molecule that actually disrupts these cargo receptors. And as I described in my TED Talk, it's a little bit like having these cargo trucks that ultimately need to go into the lysosome, the cells recycling facility. And this is exactly what this small molecule can do. And so, it was just like a remarkable story of discovery. And then I think the most exciting of all is that these cargo receptors turn out to be not only relevant to this one mangled misshapen protein, but they actually handle a completely different misshapen protein caused by a different genetic mutation in the eye, causing retinitis pigmentosa, a form of blindness, familial blindness. We're now studying familial Alzheimer's disease that's also involving these cargo receptors, and there are other mangled misshapen proteins in the liver, in the lung that we're now studying. So this becomes what I call a node, like a nodal mechanism that can be targeted for the benefit of many more patients than we had previously thought possible, which has been I think, the most satisfying part about this story of molecular sleuthing.Eric Topol (06:20):Yeah, and it's pretty extraordinary. We'll put the figure from your classic Cell paper in 2019, where you have a small molecule that targets the cargo receptor called TMED9.Anna Greka (06:34):Correct.Expanding the MissionEric Topol (06:34):And what's amazing about this, of course, is the potential to reverse this toxic protein disease. And as you say, it may have applicability well beyond this MUC1 kidney story, but rather eye disease with retinitis pigmentosa and the familial Alzheimer's and who knows what else. And what's also fascinating about this is how, as you said, there were these limited number of families with the kidney disease and then you found another one, uromodulin. So there's now, as you say, thousands of families, and that gets me to part of your sleuth work is not just hardcore science. You started an entity called the Ladders to Cures (L2C) Scientific Accelerator.Eric Topol (07:27):Maybe you can tell us about that because this is really pulling together all the forces, which includes the patient advocacy groups, and how are we going to move forward like this?Anna Greka (07:39):Absolutely. I think the goal of the Ladders to Cures Accelerator, which is a new initiative that we started at the Broad, but it really encompasses many colleagues across Boston. And now increasingly it's becoming sort of a national, we even have some international collaborations, and it's only two years that it's been in existence, so we're certainly in a growth mode. But the inspiration was really some of this molecular sleuthing work where I basically thought, well, for starters, it cannot be that there's only one molecular node, these TMED cargo receptors that we discovered there's got to be more, right? And so, there's a need to systematically go and find more nodes because obviously as anyone who works in rare genetic diseases will tell you, the problem for all of us is that we do what I call hand to hand combat. We start with the disease with one mutation, and we try to uncover the mechanism and then try to develop therapies, and that's wonderful.Anna Greka (08:33):But of course, it's slow, right? And if we consider the fact that there are 30 million patients in the United States in every state, everywhere in the country who suffer from a rare genetic disease, most of them, more than half of them are children, then we can appreciate the magnitude of the problem. Out of more than 8,000 genes that are involved in rare genetic diseases, we barely have something that looks like a therapy for maybe 500 of them. So there's a huge mismatch in the unmet need and magnitude of the problem. So the Ladders to Cures Accelerator is here to address this and to do this with the most modern tools available. And to your point, Eric, to bring patients along, not just as the recipients of whatever we discover, but also as partners in the research enterprise because it's really important to bring their perspectives and of course their partnerships in things like developing appropriate biomarkers, for example, for what we do down the road.Anna Greka (09:35):But from a fundamental scientific perspective, this is basically a project that aims to identify every opportunity for nodes, underlying all rare genetic diseases as quickly as possible. And this was one of the reasons I was there at the AI for Science Forum, because of course when one undertakes a project in which you're basically, this is what we're trying to do in the Ladders to Cures Accelerator, introduce dozens of thousands of missense and nonsense human mutations that cause genetic diseases, simultaneously introduce them into multiple human cells and then use modern scalable technology tools. Things like CRISPR screens, massively parallel CRISPR screens to try to interrogate all of these diseases in parallel, identify the nodes, and then develop of course therapeutic programs based on the discovery of these nodes. This is a massive data generation project that is much needed and in addition to the fact that it will help hopefully accelerate our approach to all rare diseases, genetic diseases. It is also a highly controlled cell perturbation dataset that will require the most modern tools in AI, not only to extract the data and understand the data of this dataset, but also because this, again, an extremely controlled, well controlled cell perturbation dataset can be used to train models, train AI models, so that in the future, and I hope this doesn't sound too futuristic, but I think that we're all aiming for that cell biologists for sure dream of this moment, I think when we can actually have in silico the opportunity to make predictions about what cell behaviors are going to look like based on a new perturbation that was not in the training set. So an experiment that hasn't yet been done on a cell, a perturbation that has not been made on a human cell, what if like a new drug, for example, or a new kind of perturbation, a new chemical perturbation, how would it affect the behavior of the cell? Can we make a predictive model for that? This doesn't exist today, but I think this is something, the cell prediction model is a big question for biology for the future. And so, I'm very energized by the opportunity to both address this problem of rare monogenic diseases that remains an unmet need and help as many patients as possible while at the same time advancing biology as much as we possibly can. So it's kind of like a win-win lifting all boats type of enterprise, hopefully.Eric Topol (12:11):Yeah. Well, there's many things to get to unpack what you've just been reviewing. So one thing for sure is that of these 8,000 monogenic diseases, they have relevance to the polygenic common diseases, of course. And then also the fact that the patient family advocates, they are great at scouring the world internet, finding more people, bringing together communities for each of these, as you point out aptly, these rare diseases cumulatively are high, very high proportion, 10% of Americans or more. So they're not so rare when you think about the overall.Anna Greka (12:52):Collectively.Help From the Virtual Cell?Eric Topol (12:53):Yeah. Now, and of course is this toxic proteinopathies, there's at least 50 of these and the point that people have been thinking until now that, oh, we found a mangled protein, but what you've zeroed in on is that, hey, you know what, it's not just a mangled protein, it's how it gets stuck in the cell and that it can't get to the lysosome to get rid of it, there's no waste system. And so, this is such fundamental work. Now that gets me to the virtual cell story, kind of what you're getting into. I just had a conversation with Charlotte Bunne and Steve Quake who published a paper in December on the virtual cell, and of course that's many years off, but of course it's a big, bold, ambitious project to be able to say, as you just summarized, if you had cells in silico and you could do perturbations in silico, and of course they were validated by actual experiments or bidirectionally the experiments, the real ones helped to validate the virtual cell, but then you could get a true acceleration of your understanding of cell biology, your field of course.Anna Greka (14:09):Exactly.Eric Topol (14:12):So what you described, is it the same as a virtual cell? Is it kind of a precursor to it? How do you conceive this because this is such a complex, I mean it’s a fundamental unit of life, but it's also so much more complex than a protein or an RNA because not only all the things inside the cell, inside all these organelles and nucleus, but then there's all the outside interactions. So this is a bold challenge, right?Anna Greka (14:41):Oh my god, it's absolutely from a biologist perspective, it's the challenge of a generation for sure. We think taking humans to Mars, I mean that's an aspirational sort of big ambitious goal. I think this is the, if you will, the Mars shot for biology, being able to, whether the terminology, whether you call it a virtual cell. I like the idea of saying that to state it as a problem, the way that people who think about it from a mathematics perspective for example, would think about it. I think stating it as the cell prediction problem appeals to me because it actually forces us biologists to think about setting up the way that we would do these cell perturbation data sets, the way we would generate them to set them up to serve predictions. So for example, the way that I would think about this would be can I in the future have so much information about how cell perturbations work that I can train a model so that it can predict when I show it a picture of another cell under different conditions that it hasn't seen before, that it can still tell me, ah, this is a neuron in which you perturbed the mitochondria, for example, and now this is sort of the outcome that you would expect to see.Anna Greka (16:08):And so, to be able to have this ability to have a model that can have the ability to predict in silico what cells would look like after perturbation, I think that's sort of the way that I think about this problem. It is very far away from anything that exists today. But I think that the beginning starts, and this is one of the unique things about my institute, if I can say, we have a place where cell biologists, geneticists, mathematicians, machine learning experts, we all come together in the same place to really think and grapple with these problems. And of course we're very outward facing, interacting with scientists all across the world as well. But there's this sort of idea of bringing people into one institute where we can just think creatively about these big aspirational problems that we want to solve. I think this is one of the unique things about the ecosystem at the Broad Institute, which I'm proud to be a part of, and it is this kind of out of the box thinking that will hopefully get us to generate the kinds of data sets that will serve the needs of building these kinds of models with predictive capabilities down the road.Anna Greka (17:19):But as you astutely said, AlphaFold of course was based on the protein database existing, right? And that was a wealth of available information in which one could train models that would ultimately be predictive, as we have seen this miracle that Demi Hassabis and John Jumper have given to humanity, if you will.Anna Greka (17:42):But as Demis and John would also say, I believe is as I have discussed with them, in fact, the cell prediction problem is really a bigger problem because we do not have a protein data bank to go to right now, but we need to create it to generate these data. And so, my Ladders to Cures Accelerator is here to basically provide some part of the answer to that problem, create this kind of well-controlled database that we need for cell perturbations, while at the same time maximizing our learnings about these fully penetrant coding mutations and what their downstream sequelae would be in many different human cells. And so, in this way, I think we can both advance our knowledge about these monogenic diseases, build models, hopefully with predictive capabilities. And to your point, a lot of what we will learn about this biology, if we think that it involves 8,000 or more out of the 20,000 genes in our genome, it will of course serve our understanding of polygenic diseases ultimately as well as we go deeper into this biology and we look at the combinatorial aspects of what different mutations do to human cells. And so, it's a huge aspirational problem for a whole generation, but it's a good one to work on, I would say.Learning the Language of Life with A.I. Eric Topol (19:01):Oh, absolutely. Now I think you already mentioned something that's quite, well, two things from what you just touched on. One of course, how vital it is to have this inner or transdisciplinary capability because you do need expertise across these vital areas. But the convergence, I mean, I love your term nodal biology and the fact that there's all these diseases like you were talking about, they do converge and nodal is a good term to highlight that, but it's not. Of course, as you mentioned, we have genome editing which allows to look at lots of different genome perturbations, like the single letter change that you found in MUC1 pathogenic critical mutation. There's also the AI world which is blossoming like I've never seen. In fact, I had in Science this week about learning the language of life with AI and how there's been like 15 new foundation models, DNA, proteins, RNA, ligands, all their interactions and the beginning of the cell story too with the human cell.Eric Topol (20:14):So this is exploding. As you said, the expertise in computer science and then this whole idea that you could take these powerful tools and do as you said, which is the need to accelerate, we just can't sit around here when there's so much discovery work to be done with the scalability, even though it might take years to get to this artificial intelligence virtual cell, which I have to agree, everyone in biology would say that's the holy grail. And as you remember at our conference in London, Demi Hassabis said that's what we'd like to do now. So it has the attention of leaders in AI around the world, obviously in the science and the biomedical community like you and many others. So it is an extraordinary time where we just can't sit still with these tools that we have, right?Anna Greka (21:15):Absolutely. And I think this is going to be, you mentioned the ASCI presidency in the beginning of our call. This is going to be the president gets to give an address at the annual meeting in Chicago. This is going to be one of the points I make, no matter what field in biomedicine we're in, we live in, I believe, a golden era and we have so many tools available to us that we can really accelerate our ability to help more patients. And of course, this is our mandate, the most important stakeholders for everything that we do as physician-scientists are our patients ultimately. So I feel very hopeful for the future and our ability to use these tools and to really make good on the promise of research is a public good. And I really hope that we can advance our knowledge for the benefit of all. And this is really an exciting time, I think, to be in this field and hopefully for the younger colleagues a time to really get excited about getting in there and getting involved and asking the big questions.Career ReflectionsEric Topol (22:21):Well, you are the prototype for this and an inspiration to everyone really, I'm sure to your lab group, which you highlighted in the TED Talk and many other things that you do. Now I want to spend a little bit of time about your career. I think it's fascinating that you grew up in Greece and your father's a nephrologist and your mother's a pathologist. So you had two physicians to model, but I guess you decided to go after nephrology, which is an area in medicine that I kind of liken it to Rodney Dangerfield, he doesn't get any respect. You don't see many people that go into nephrology. But before we get to your decision to do that somehow or other you came from Greece to Harvard for your undergrad. How did you make that connect to start your college education? And then subsequently you of course you stayed in Boston, you've never left Boston, I think.Anna Greka (23:24):I never left. Yeah, this is coming into 31 years now in Boston.Anna Greka (23:29):Yeah, I started as a Harvard undergraduate and I'm now a full professor. It's kind of a long, but wonderful road. Well, actually I would credit my parents. You mentioned that my father, they're both physician-scientists. My father is now both retired, but my father is a nephrologist, and my mother is a pathologist, actually, they were both academics. And so, when we were very young, we lived in England when my parents were doing postdoctoral work. That was actually a wonderful gift that they gave me because I became bilingual. It was a very young age, and so that allowed me to have this advantage of being fluent in English. And then when we moved back to Greece where I grew up, I went to an American school. And from that time, this is actually an interesting story in itself. I'm very proud of this school.Anna Greka (24:22):It's called Anatolia, and it was founded by American missionaries from Williams College a long time ago, 150 and more years ago. But it is in Thessaloniki, Greece, which is my hometown, and it's a wonderful institution, which gave me a lot of gifts as well, preparing me for coming to college in the United States. And of course, I was a good student in high school, but what really was catalytic was that I was lucky enough to get a scholarship to go to Harvard. And that was really, you could say the catalyst that propelled me from a teenager who was dreaming about a career as a physician-scientist because I certainly was for as far back as I remember in fact. But then to make that a reality, I found myself on the Harvard campus initially for college, and then I was in the combined Harvard-MIT program for my MD PhD. And then I trained in Boston at Mass General in Brigham, and then sort of started my academic career. And that sort of brings us to today, but it is an unlikely story and one that I feel still very lucky and blessed to have had these opportunities. So for sure, it's been wonderful.Eric Topol (25:35):We're the ones lucky that you came here and set up shop and you did your productivity and discovery work and sleuthing has been incredible. But I do think it's interesting too, because when you did your PhD, it was in neuroscience.Anna Greka (25:52):Ah, yes. That's another.Eric Topol (25:54):And then you switch gears. So tell us about that?Anna Greka (25:57):This is interesting, and actually I encourage more colleagues to think about it this way. So I have always been driven by the science, and I think that it seems a little backward to some people, but I did my PhD in neuroscience because I was interested in understanding something about these ion channels that were newly discovered at the time, and they were most highly expressed in the brain. So here I was doing work in the brain in the neuroscience program at Harvard, but then once I completed my PhD and I was in the middle of my residency training actually at Mass General, I distinctly remember that there was a paper that came out that implicated the same family of ion channels that I had spent my time understanding in the brain. It turned out to be a channelopathy that causes kidney disease.Anna Greka (26:43):So that was the light bulb, and it made me realize that maybe what I really wanted to do is just follow this thread. And my scientific curiosity basically led me into studying the kidney and then it seemed practical therefore to get done with my clinical training as efficiently as possible. So I finished residency, I did nephrology training, and then there I was in the lab trying to understand the biology around this channelopathy. And that sort of led us into the early projects in my young lab. And in fact, it's interesting we didn't talk about that work, but that work in itself actually has made it all the way to phase II trials in patients. This was a paper we published in Science in 2017 and follow onto that work, there was an opportunity to build this into a real drug targeting one of these ion channels that has made it into phase II trials. And we'll see what happens next. But it's this idea of following your scientific curiosity, which I also talked about in my TED Talk, because you don't know to what wonderful places it will lead you. And quite interestingly now my lab is back into studying familial Alzheimer's and retinitis pigmentosa in the eye in brain. So I tell people, do not limit yourself to whatever someone says your field is or should be. Just follow your scientific curiosity and usually that takes you to a lot more interesting places. And so, that's certainly been a theme from my career, I would say.Eric Topol (28:14):No, I think that's perfect. Curiosity driven science is not the term. You often hear hypothesis driven or now with AI you hear more AI exploratory science. But no, that's great. Now I want to get a little back to the AI story because it’s so fascinating. You use lots of different types of AI such as cellular imaging would be fusion models and drug discovery. I mean, you've had drug discovery for different pathways. You mentioned of course the ion channel and then also as we touched on with your Cell paper, the whole idea of targeting the cargo receptor with a small molecule and then things in between. You discussed this of course at the London panel, but maybe you just give us the skinny on the different ways that you incorporate AI in the state-of-the-art science that you're doing?Anna Greka (29:17):Sure, yeah, thank you. I think there are many ways in which even for quite a long time before AI became such a well-known kind of household term, if you will, the concept of machine learning in terms of image processing is something that has been around for some time. And so, this is actually a form of AI that we use in order to process millions of images. My lab has by produced probably more than 20 million images over the last few years, maybe five to six years. And so, if you can imagine it's impossible for any human to process this many images and make sense of them. So of course, we've been using machine learning that is becoming increasingly more and more sophisticated and advanced in terms of being able to do analysis of images, which is a lot of what we cell biologists do, of course.Anna Greka (30:06):And so, there's multiple different kinds of perturbations that we do to cells, whether we're using CRISPR or base editing to make, for example, genome wide or genome scale perturbations or small molecules as we have done as well in the past. These are all ways in which we are then using machine learning to read out the effects in images of cells that we're looking at. So that's one way in which machine learning is used in our daily work, of course, because we study misshape and mangled proteins and how they are recognized by these cargo receptors. We also use AlphaFold pretty much every day in my lab. And this has been catalytic for us as a tool because we really are able to accelerate our discoveries in ways that were even just three or four years ago, completely impossible. So it's been incredible to see how the young people in my lab are just so excited to use these tools and they're becoming extremely savvy in using these tools.Anna Greka (31:06):Of course, this is a new generation of scientists, and so we use AlphaFold all the time. And this also has a lot of implications of course for some of the interventions that we might think about. So where in this cargo receptor complex that we study for example, might we be able to fit a drug that would disrupt the complex and lead the cargo tracks into the lysosome for degradation, for example. So there's many ways in which AI can be used for all of these functions. So I would say that if we were to organize our thinking around it, one way to think about the use of machine learning AI is around what I would call understanding biology in cells and what in sort of more kind of drug discovery terms you would call target identification, trying to understand the things that we might want to intervene on in order to have a benefit for disease.Anna Greka (31:59):So target ID is one area in which I think machine learning and AI will have a catalytic effect as they already are. The other of course, is in the actual development of the appropriate drugs in a rational way. So rational drug design is incredibly enabled by AlphaFold and all these advances in terms of understanding protein structures and how to fit drugs into them of all different modalities and kinds. And I think an area that we are not yet harnessing in my group, but I think the Ladders to Cures Accelerator hopes to build on is really patient data. I think that there's a lot of opportunity for AI to be used to make sense of medical records for example and how we extract information that would tell us that this cohort of patients is a better cohort to enroll in your trial versus another. There are many ways in which we can make use of these tools. Not all of them are there yet, but I think it's an exciting time for being involved in this kind of work.Eric Topol (32:58):Oh, no question. Now it must be tough when you know the mechanism of these families disease and you even have a drug candidate, but that it takes so long to go from that to helping these families. And what are your thoughts about that, I mean, are you thinking also about genome editing for some of these diseases or are you thinking to go through the route of here's a small molecule, here's the tox data in animal models and here's phase I and on and on. Where do you think because when you know so much and then these people are suffering, how do you bridge that gap?Anna Greka (33:39):Yeah, I think that's an excellent question. Of course, having patients as our partners in our research is incredible as a way for us to understand the disease, to build biomarkers, but it is also exactly creating this kind of emotional conflict, if you will, because of course, to me, honesty is the best policy, if you will. And so, I'm always very honest with patients and their families. I welcome them to the lab so they can see just how long it takes to get some of these things done. Even today with all the tools that we have, of course there are certain things that are still quite slow to do. And even if you have a perfect drug that looks like it fits into the right pocket, there may still be some toxicity, there may be other setbacks. And so, I try to be very honest with patients about the road that we're on. The small molecule path for the toxic proteinopathies is on its way now.Anna Greka (34:34):It's partnered with a pharmaceutical company, so it's on its way hopefully to patients. Of course, again, this is an unpredictable road. Things can happen as you very well know, but I'm at least glad that it's sort of making its way there. But to your point, and I'm in an institute where CRISPR was discovered, and base editing and prime editing were discovered by my colleagues here. So we are in fact looking at every other modality that could help with these diseases. We have several hurdles to overcome because in contrast to the liver and the brain, the kidney for example, is not an organ in which you can easily deliver nucleic acid therapies, but we're making progress. I have a whole subgroup within the bigger group who's focusing on this. It's actually organized in a way where they're running kind of independently from the cell biology group that I run.Anna Greka (35:31):And it's headed by a person who came from industry so that she has the opportunity to really drive the project the way that it would be run milestone driven, if you will, in a way that it would be run as a therapeutics program. And we're really trying to go after all kinds of different nucleic acid therapies that would target the mutations themselves rather than the cargo receptors. And so, there's ASO and siRNA technologies and then also actual gene editing technologies that we are investigating. But I would say that some of them are closer than others. And again, to your question about patients, I tell them honestly when a project looks to be more promising, and I also tell them when a project looks to have hurdles and that it will take long and that sometimes I just don't know how long it will take before we can get there. The only thing that I can promise patients in any of our projects, whether it's Alzheimer's, blindness, kidney disease, all I can promise is that we're working the hardest we possibly can on the problem.Anna Greka (36:34):And I think that is often reassuring I have found to patients, and it's best to be honest about the fact that these things take a long time, but I do think that they find it reassuring that someone is on it essentially, and that there will be some progress as we move forward. And we've made progress in the very first discovery that came out of my lab. As I mentioned to you, we've made it all the way to phase II trials. So I have seen the trajectory be realized, and I'm eager to make it happen again and again as many times as I can within my career to help as many people as possible.The Paucity of Physician-ScientistsEric Topol (37:13):I have no doubts that you'll be doing this many times in your career. No, there's no question about it. It's extraordinary actually. There's a couple of things there I want to pick up on. Physician-scientists, as you know, are a rarefied species. And you have actually so nicely told the story about when you have a physician-scientist, you're caring for the patients that you're researching, which is, most of the time we have scientists. Nothing wrong with them of course, but you have this hinge point, which is really important because you’re really hearing the stories and experiencing the patients and as you say, communicating about the likelihood of being able to come up with a treatment or the progress. What are we going to do to get more physician-scientists? Because this is a huge problem, it has been for decades, but the numbers just keep going lower and lower.Anna Greka (38:15):I think you're absolutely right. And this is again, something that in my leadership of the ASCI I have made sort of a cornerstone of our efforts. I think that it has been well-documented as a problem. I think that the pressures of modern clinical care are really antithetical to the needs of research, protected time to really be able to think and be creative and even have the funding available to be able to pursue one's program. I think those pressures are becoming so heavy for investigators that many of them kind of choose one or the other route most often the clinical route because that tends to be, of course where they can support their families better. And so, this has been kind of the conundrum in some ways that we take our best and brightest medical students who are interested in investigation, we train them and invest in them in becoming physician-scientists, but then we sort of drop them at the most vulnerable time, which is usually after one completes their clinical and scientific training.Anna Greka (39:24):And they're embarking on early phases of one's careers. It has been found to be a very vulnerable point when a lot of people are now in their mid-thirties or even late thirties perhaps with some family to take care of other burdens of adulthood, if you will. And I think what it becomes very difficult to sustain a career where one salary is very limited due to the research component. And so, I think we have to invest in our youngest people, and it is a real issue that there's no good mechanism to do that at the present time. So I was actually really hoping that there would be an opportunity with leadership at the NIH to really think about this. It's also been discussed at the level of the National Academy of Medicine where I had some role in discussing the recent report that they put out on the biomedical enterprise in the United States. And it's kind of interesting to see that there is a note made there about this issue and the fact that there needs to be, I think, more generous investment in the careers of a few select physician-scientists that we can support. So if you look at the numbers, currently out of the entire physician workforce, a physician-scientist comprised of less than 1%.Anna Greka (40:45):It’s probably closer to 0.8% at this point.Eric Topol (40:46):No, it's incredible.Anna Greka (40:48):So that's really not enough, I think, to maintain the enterprise and if you will, this incredible innovation economy that the United States has had this miracle engine, if you will, in biomedicine that has been fueled in large part by physician investigators. Of course, our colleagues who are non-physician investigators are equally important partners in this journey. But we do need a few of the physician-scientists investigators I think as well, if you really think about the fact that I think 70% of people who run R&D programs in all the big pharmaceutical companies are physician-scientists. And so, we need people like us to be able to work on these big problems. And so, more investment, I think that the government, the NIH has a role to play there of course. And this is important from both an economic perspective, a competition perspective with other nations around the world who are actually heavily investing in the physician-scientist workforce.Anna Greka (41:51):And I think it's also important to do so through our smaller scale efforts at the ASCI. So one of the things that I have been involved in as a council member and now as president is the creation of an awards program for those early career investigators. So we call them the Emerging-Generation Awards, and we also have the Young Physician-Scientist Awards. And these are really to recognize people who are making that transition from being kind of a trainee and a postdoc and have finished their clinical training into becoming an independent assistant professor. And so, those are small awards, but they're kind of a symbolic tap on the shoulder, if you will, that the ASCI sees you, you're talented, stay the course. We want you to become a future member. Don't give up and please keep on fighting. I think that can take us only so far.Anna Greka (42:45):I mean, unless there's a real investment, of course still it will be hard to maintain people in the pipeline. But this is just one way in which we have tried to, these programs that the ASCI offers have been very successful over the last few years. We create a cohort of investigators who are clearly recognized by members of the ASCI is being promising young colleagues. And we give them longitudinal training as part of a cohort where they learn about how to write a grant, how to write a paper, leadership skills, how to run a lab. And they're sort of like a buddy system as well. So they know that they're in it together rather than feeling isolated and struggling to get their careers going. And so, we've seen a lot of success. One way that we measure that is conversion into an ASCI membership. And so, we're encouraged by that, and we hope that the program can continue. And of course, as president, I'm going to be fundraising for that as well, it's part of the role. But it is a really worthy cause because to your point, we have to somehow make sure that our younger colleagues stay the course that we can at least maintain, if not bolster our numbers within the scientific workforce.Eric Topol (43:57):Well, you outlined some really nice strategies and plans. It's a formidable challenge, of course. And we'd like to see billions of dollars to support this. And maybe someday we will because as you say, if we could relieve the financial concerns of people who have curiosity driven ideas.Anna Greka (44:18):Exactly.Eric Topol (44:19):We could do a lot to replenish and build a big physician-scientist workforce. Now, the last thing I want to get to, is you have great communication skills. Obviously, anybody who is listening or watching this.Eric Topol (44:36):Which is another really important part of being a scientist, no less a physician or the hybrid of the two. But I wanted to just go to the backstory because your TED Talk, which has been watched by hundreds of thousands of people, and I'm sure there's hundreds of thousands more that will watch it, but the TED organization is famous for making people come to the place a week ahead. This is Vancouver used to be in LA or Los Angeles area and making them rehearse the talk, rehearse, rehearse, rehearse, which seems crazy. You could train the people there, how to give a talk. Did you have to go through that?Anna Greka (45:21):Not really. I did rehearse once on stage before I actually delivered the talk live. And I was very encouraged by the fact that the TED folks who are of course very well calibrated, said just like that. It's great, just like that.Eric Topol (45:37):That says a lot because a lot of people that do these talks, they have to do it 10 times. So that kind of was another metric. But what I don't like about that is it just because these people almost have to memorize their talks from giving it so much and all this coaching, it comes across kind of stilted and unnatural, and you're just a natural great communicator added to all your other things.Anna Greka (46:03):I think it’s interesting. Actually, I would say, if I may, that I credit, of course, I actually think that it's important, for us physician-scientists, again, science and research is a public good, and being able to communicate to the public what it is that we do, I think is kind of an obligation for the fact that we are funded by the public to do this kind of work. And so, I think that's important. And I always wanted to cultivate those communication skills for the benefit of communicating simply and clearly what it is that we do in our labs. But also, I would say as part of my story, I mentioned that I had the opportunity to attend a special school growing up in Greece, Anatolia, which was an American school. One of the interesting things about that is that there was an oratory competition.Anna Greka (46:50):I got very early exposure entering that competition. And if you won the first prize, it was in the kind of ancient Rome way, first among equals, right? And so, that was the prize. And I was lucky to have this early exposure. This is when I was 14, 15, 16 years old, that I was training to give these oratory speeches in front of an audience and sort of compete with other kids who were doing the same. I think these are just wonderful gifts that a school can give a student that have stayed with me for life. And I think that that's a wonderful, yeah, I credit that experience for a lot of my subsequent capabilities in this area.Eric Topol (47:40):Oh, that's fantastic. Well, this has been such an enjoyable conversation, Anna. Did I miss anything that we need to bring up, or do you think we have it covered?Anna Greka (47:50):Not at all. No, this was wonderful, and I thoroughly enjoyed it as well. I'm very honored seeing how many other incredible colleagues you've had on the show. It's just a great honor to be a part of this. So thank you for having me.Eric Topol (48:05):Well, you really are such a great inspiration to all of us in the biomedical community, and we'll be cheering for your continued success and thanks so much for joining today, and I look forward to the next time we get a chance to visit.Anna Greka (48:20):Absolutely. Thank you, Eric.**************************************Thanks for listening, watching or reading Ground Truths. Your subscription is greatly appreciated.If you found this podcast interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths—newsletters, analyses, and podcasts—is free, open-access.Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. And such support is becoming more vital In light of current changes of funding and support for biomedical research at NIH and other US governmental agencies.Thanks to my producer Jessica Nguyen and to Sinjun Balabanoff for audio and video support at Scripps Research. Get full access to Ground Truths at erictopol.substack.com/subscribe
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  • Carl Zimmer: Air-Borne and the Big Miss With Covid
    Before getting into this new podcast, have you checked out the recent newsletter editions and podcasts of Ground Truths?—the first diagnostic immunome—a Covid nasal vaccine update—medical storytelling and uncertainty—why did doctors with A.I. get outperformed by A.I. alone?The audio is available on iTunes and Spotify. The full video is embedded here, at the top, and also can be found on YouTube.Transcript with links to Audio and External Links Eric Topol (00:07):Well, hello. It's Eric Topol with Ground Truths, and I am just thrilled today to welcome Carl Zimmer, who is one of the great science journalists of our times. He's written 14 books. He writes for the New York Times and many other venues of great science, journalism, and he has a new book, which I absolutely love called Air-Borne. And you can see I have all these rabbit pages tagged and there's lots to talk about here because this book is the book of air. I mean, we're talking about everything that you ever wanted to know about air and where we need to go, how we missed the boat, and Covid and everything else. So welcome, Carl.Carl Zimmer (00:51):Thanks so much. Great to be here.A Book Inspired by the PandemicEric Topol (00:54):Well, the book starts off with the Skagit Valley Chorale that you and your wife Grace attended a few years later, I guess, in Washington, which is really interesting. And I guess my first question is, it had the look that this whole book was inspired by the pandemic, is that right?Carl Zimmer (01:18):Certainly, the seed was planted in the pandemic. I was working as a journalist at the New York Times with a bunch of other reporters at the Times. There were lots of other science writers also just trying to make sense of this totally new disease. And we were talking with scientists who were also trying to make sense of the disease. And so, there was a lot of uncertainty, ambiguity, and things started to come into focus. And I was really puzzled by how hard it was for consensus to emerge about how Covid spread. And I did some reporting along with other people on this conflict about was this something that was spreading on surfaces or was it the word people were using was airborne? And the World Health Organization said, no, it's not airborne, it's not airborne until they said it was airborne. And that just seemed like not quantum physics, you know what I'm saying? In the sense that it seemed like that would be the kind of thing that would get sorted out pretty quickly. And I think that actually more spoke to my own unfamiliarity with the depth of this field. And so, I would talk to experts like say, Donald Milton at the University of Maryland. I'd be like, so help me understand this. How did this happen? And he would say, well, you need to get to know some people like William Wells. And I said, who?Eric Topol (02:50):Yeah, yeah, that's what I thought.Carl Zimmer (02:53):Yeah, there were just a whole bunch of people from a century ago or more that have been forgotten. They've been lost in history, and yet they were real visionaries, but they were also incredibly embattled. And the question of how we messed up understanding why Covid was airborne turned out to have an answer that took me back thousands of years and really plunged me into this whole science that's known as aerobiology.Eric Topol (03:26):Yeah, no, it's striking. And we're going to get, of course, into the Covid story and how it got completely botched as to how it was being transmitted. But of course, as you go through history, you see a lot of the same themes of confusion and naysayers and just extraordinary denialism. But as you said, this goes back thousands of years and perhaps the miasma, the moral stain in the air that was start, this is of course long before there was thing called germ theory. Is that really where the air thing got going?A Long History of Looking Into Bad AirCarl Zimmer (04:12):Well, certainly some of the earliest evidence we have that people were looking at the air and thinking about the air and thinking there's something about the air that matters to us. Aristotle thought, well, there's clearly something important about the air. Life just seems to be revolve around breathing and he didn't know why. And Hippocrates felt that there could be this stain on the air, this corruption of the air, and this could explain why a lot of people in a particular area, young and old, might suddenly all get sick at the same time. And so, he put forward this miasma theory, and there were also people who were looking at farm fields and asking, well, why are all my crops dead suddenly? What happened? And there were explanations that God sends something down to punish us because we've been bad, or even that the air itself had a kind of miasma that affected plants as well as animals. So these ideas were certainly there, well over 2,000 years ago.Eric Topol (05:22):Now, as we go fast forward, we're going to get to, of course into the critical work of William and Mildred Wells, who I'd never heard of before until I read your book, I have to say, talk about seven, eight decades filed into oblivion. But before we get to them, because their work was seminal, you really get into the contributions of Louis Pasteur. Maybe you could give us a skinny on what his contributions were because I was unaware of his work and the glaciers, Mer de Glace and figuring out what was going on in the air. So what did he really do to help this field?Carl Zimmer (06:05):Yeah, and this is another example of how we can kind of twist and deform history. Louis Pasteur is a household name. People know who Louis Pasteur is. People know about pasteurization of milk. Pasteur is associated with vaccines. Pasteur did other things as well. And he was also perhaps the first aerobiologist because he got interested in the fact that say, in a factory where beet juice was being fermented to make alcohol, sometimes it would spoil. And he was able to determine that there were some, what we know now are bacteria that were getting into the beet juice. And so, it was interrupting the usual fermentation from the yeast. That in itself was a huge discovery. But he was saying, well, wait, so why are there these, what we call bacteria in the spoiled juice? And he thought, well, maybe they just float in the air.Carl Zimmer (07:08):And this was really a controversial idea in say, 1860, because even then, there were many people who were persuaded that when you found microorganisms in something, they were the result of spontaneous generation. In other words, the beet juice spontaneously produced this life. This was standard view of how life worked and Pasteur was like, I'm not sure I buy this. And this basically led to him into an incredible series of studies around Paris. He would have a flask, and he'd have a long neck on it, and the flask was full of sterile broth, and he would just take it places and he would just hold it there for a while, and eventually bacteria would fall down that long neck and they would settle in the broth, and they would multiply in there. It would turn cloudy so he could prove that there was life in the air.Carl Zimmer (08:13):And they went to different places. He went to farm fields, he went to mountains. And the most amazing trip he took, it was actually to the top of a glacier, which was very difficult, especially for someone like Pasteur, who you get the impression he just hated leaving the lab. This was not a rugged outdoorsman at all. But there he is, climbing around on the ice with this flask raising it over his head, and he caught bacteria there as well. And that actually was pivotal to destroying spontaneous generation as a theory. So aerobiology among many, many other things, destroyed this idea that life could spontaneously burst into existence.Eric Topol (08:53):Yeah, no. He says ‘these gentlemen, are the germs of microscopic beings’ shown in the existence of microorganisms in the air. So yeah, amazing contribution. And of course, I wasn't familiar with his work in the air like this, and it was extensive. Another notable figure in the world of germ theory that you bring up in the book with another surprise for me was the great Robert Koch of the Koch postulates. So is it true he never did the third postulate about he never fulfilled his own three postulates?Carl Zimmer (09:26):Not quite. Yeah, so he had these ideas about what it would take to actually show that some particular pathogen, a germ, actually caused a disease, and that involved isolating it from patients, culturing it outside of them. And then actually experimentally infecting an animal and showing the symptoms again. And he did that with things like anthrax and tuberculosis. He nailed that. But then when it came to cholera, there was this huge outbreak in Egypt, and people were still battling over what caused cholera. Was it miasma? Was it corruption in the air, or was it as Koch and others believe some type of bacteria? And he found a particular kind of bacteria in the stool of people who were dying or dead of cholera, and he could culture it, and he consistently found it. And when he injected animals with it, it just didn't quite work.Eric Topol (10:31):Okay. Yeah, so at least for cholera, the Koch’s third postulate of injecting in animals, reproducing the disease, maybe not was fulfilled. Okay, that's good.Eric Topol (10:42):Now, there's a lot of other players here. I mean, with Fred Meier and Charles Lindbergh getting samples in the air from the planes and Carl Flügge. And before we get to the Wells, I just want to mention these naysayers like Charles Chapin, Alex Langmuir, the fact that they said, well, people that were sensitive to pollen, it was just neurosis. It wasn't the pollen. I mean, just amazing stuff. But anyway, the principles of what I got from the book was the Wells, the husband and wife, very interesting characters who eventually even split up, I guess. But can you tell us about their contributions? Because they're really notable when we look back.William and Mildred Wells Carl Zimmer (11:26):Yeah, they really are. And although by the time they had died around 1960, they were pretty much forgotten already. And yet in the 1930s, the two of them, first at Harvard and then at University of Pennsylvania did some incredible work to actually challenge this idea that airborne infection was not anything real, or at least nothing really to worry about. Because once the miasmas have been cleared away, people who embrace the germ theory of disease said, look, we've got cholera in water. We've got yellow fever in mosquitoes. We've got syphilis in sex. We have all these ways that germs can get from one person to the next. We don't need to worry about the air anymore. Relax. And William Wells thought, I don't know if that's true. And we actually invented a new device for actually sampling the air, a very clever kind of centrifuge. And he started to discover, actually, there's a lot of stuff floating around in the air.Carl Zimmer (12:37):And then with a medical student of his, Richard Riley started to develop a physical model. How does this happen? Well, you and I are talking, as we are talking we are expelling tiny droplets, and those droplets can potentially contain pathogens. We can sneeze out big droplets or cough them too. Really big droplets might fall to the floor, but lots of other droplets will float. They might be pushed along by our breath like in a cloud, or they just may be so light, they just resist gravity. And so, this was the basic idea that he put forward. And then he made real headlines by saying, well, maybe there's something that we can do to these germs while they're still in the air to protect our own health. In the same way you'd protect water so that you don't get cholera. And he stumbled on ultraviolet light. So basically, you could totally knock out influenza and a bunch of other pathogens just by hitting these droplets in the air with light. And so, the Wells, they were very difficult to work with. They got thrown out of Harvard. Fortunately, they got hired at Penn, and they lasted there just long enough that they could run an experiment in some schools around Philadelphia. And they put up ultraviolet lamps in the classrooms. And those kids did not get hit by huge measles outbreak that swept through Philadelphia not long afterwards.Eric Topol (14:05):Yeah, it's pretty amazing. I had never heard of them. And here they were prescient. They did the experiments. They had this infection machine where they could put the animal in and blow in the air, and it was basically like the Koch's third postulate here of inducing the illness. He wrote a book, William and he’s a pretty confident fellow quoted, ‘the book is not for here and now. It is from now on.’ So he wasn't a really kind of a soft character. He was pretty strong, I guess. Do you think his kind of personality and all the difficulties that he and his wife had contributed to why their legacy was forgotten by most?Carl Zimmer (14:52):Yes. They were incredibly difficult to work with, and there's no biography of the Wellses. So I had to go into archives and find letters and unpublished documents and memos, and people will just say like, oh my goodness, these people are so unbearable. They just were fighting all the time. They were fighting with each other. They were peculiar, particularly William was terrible with language and just people couldn't deal with them. So because they were in these constant fights, they had very few friends. And when you have a big consensus against you and you don't have very many friends to not even to help you keep a job, it's not going to turn out well, unfortunately. They did themselves no favors, but it is still really remarkable and sad just how much they figured out, which was then dismissed and forgotten.Eric Topol (15:53):Yeah, I mean, I'm just amazed by it because it's telling about your legacy in science. You want to have friends, you want to be, I think, received well by your colleagues in your community. And when you're not, you could get buried, your work could get buried. And it kind of was until, for me, at least, your book Air-Borne. Now we go from that time, which is 60, 70 years ago, to fast forward H1N1 with Linsey Marr from Virginia Tech, who in 2009 was already looking back at the Wells work and saying, wait a minute there's something here that this doesn't compute, kind of thing. Can you give us the summary about Linsey? Of course, we're going to go to 2018 again all before the pandemic with Lydia, but let's first talk about Linsey.Linsey MarrSee my previous Ground Truths podcast with Prof Marr hereCarl Zimmer (16:52):Sure. So Linsey Marr belongs to this new generation of scientists in the 21st century who start to individually rediscover the Welles. And then in Lind\sey Marr's case, she was studying air pollution. She's an atmospheric scientist and she's at Virginia Tech. And she and her husband are trying to juggle their jobs and raising a little kid, and their son is constantly coming home from daycare because he's constantly getting sick, or there's a bunch of kids who are sick there and so on. And that got Linsey Marr actually really curious like what's going on because they were being careful about washing objects and so on, and doing their best to keep the kids healthy. And she started looking into ideas about transmission of diseases. And she got very interested in the flu because in 2009, there was a new pandemic, in other words that you had this new strain of influenza surging throughout the world. And so, she said, well, let me look at what people are saying. And as soon as she started looking at it, she just said, well, people are saying things that as a physicist I know make no sense. They're saying that droplets bigger than five microns just plummet to the ground.Carl Zimmer (18:21):And in a way that was part of a sort of a general rejection of airborne transmission. And she said, look, I teach this every year. I just go to the blackboard and derive a formula to show that particles much bigger than this can stay airborne. So there's something really wrong here. And she started spending more and more time studying airborne disease, and she kept seeing the Welles as being cited. And she was like, who are these? Didn't know who they were. And she had to dig back because finding his book is not easy, I will tell you that. You can't buy it on Amazon. It's like it was a total flop.Eric Topol (18:59):Wow.Carl Zimmer (19:00):And eventually she started reading his papers and getting deeper in it, and she was like, huh. He was pretty smart. And he didn't say any of the things that people today are claiming he said. There's a big disconnect here. And that led her into join a very small group of people who really were taking the idea of airborne infection seriously, in the early 2000s.Lydia BourouibaEric Topol (19:24):Yeah, I mean, it's pretty incredible because had we listened to her early on in the pandemic and many others that we're going to get into, this wouldn't have gone years of neglect of airborne transmission of Covid. Now, in 2018, there was, I guess, a really important TEDMED talk by Lydia. I don't know how you pronounce her last name, Bourouiba or something. Oh, yeah. And she basically presented graphically. Of course, all this stuff is more strained for people to believe because of the invisibility story, but she, I guess, gave demos that were highly convincing to her audience if only more people were in her audience. Right?Carl Zimmer (20:09):That's right. That's right. Yeah. So Lydia was, again, not an infectious disease expert at first. She was actually trained as a physicist. She studied turbulence like what you get in spinning galaxies or spinning water in a bathtub as it goes down the drain. But she was very taken aback by the SARS outbreak in 2003, which did hit Canada where she was a student.Carl Zimmer (20:40):And it really got her getting interested in infectious diseases, emerging diseases, and asking herself, what tools can I bring from physics to this? And she's looked into a lot of different things, and she came to MIT and MIT is where Harold Edgerton built those magnificent stroboscope cameras. And we've all seen these stroboscope images of the droplets of milk frozen in space, or a bullet going through a card or things like that that he made in the 1930s and 1940s and so on. Well, one of the really famous images that was used by those cameras was a sneeze actually, around 1940. That was the first time many Americans would see these droplets frozen in space. Of course, they forgot them.Carl Zimmer (21:34):So she comes there and there's a whole center set up for this kind of high-speed visualization, and she starts playing with these cameras, and she starts doing experiments with things like breathing and sneezes and so on. But now she's using digital video, and she discovers that she goes and looks at William Wells and stuff. She's like, that's pretty good, but it's pretty simple. It's pretty crude. I mean, of course it is. It was in the 1930s. So she brings a whole new sophistication of physics to studying these things, which she finds that, especially with a sneeze, it sort of creates a new kind of physics. So you actually have a cloud that just shoots forward, and it even carries the bigger droplets with it. And it doesn't just go three feet and drop. In her studies looking at her video, it could go 10 feet, 20 feet, it could just keep going.Eric Topol (22:24):27 feet, I think I saw. Yeah, right.Carl Zimmer (22:26):Yeah. It just keeps on going. And so, in 2018, she gets up and at one of these TEDMED talks and gives this very impressive talk with lots of pictures. And I would say the world didn't really listen.Eric Topol (22:48):Geez and amazing. Now, the case that you, I think centered on to show how stupid we were, not everyone, not this group of 36, we're going to talk about not everyone, but the rest of the world, like the WHO and the CDC and others was this choir, the Skagit Valley Chorale in Washington state. Now, this was in March 2020 early on in the pandemic, there were 61 people exposed to one symptomatic person, and 52 were hit with Covid. 52 out of 61, only 8 didn't get Covid. 87% attack rate eventually was written up by an MMWR report that we'll link to. This is extraordinary because it defied the idea of that it could only be liquid droplets. So why couldn't this early event, which was so extraordinary, opened up people's mind that there's not this six-foot rule and it’s all these liquid droplets and the rest of the whole story that was wrong.Carl Zimmer (24:10):I think there's a whole world of psychological research to be done on why people accept or don't accept scientific research and I'm not just talking about the public. This is a question about how science itself works, because there were lots of scientists who looked at the claims that Linsey Marr and others made about the Skagit Valley Chorale outbreak and said, I don't know, I'm not convinced. You didn't culture viable virus from the air. How do you really know? Really, people have said that in print. So it does raise the question of a deep question, I think about how does science judge what the right standard of proof is to interpret things like how diseases spread and also how to set public health policy. But you're certainly right that and March 10th, there was this outbreak, and by the end of March, it had started to make news and because the public health workers were figuring out all the people who were sick and so on, and people like Linsey Marr were like, this kind of looks like airborne to me, but they wanted to do a closer study of it. But still at that same time, places like the World Health Organization (WHO) were really insisting Covid is not airborne.“This is so mind-boggling to me. It just made it obvious that they [WHO] were full of s**t.”—Jose-Luis JimenezGetting It Wrong, Terribly WrongEric Topol (25:56):It's amazing. I mean, one of the quotes that there was, another one grabbed me in the book, in that group of the people that did air research understanding this whole field, the leaders, there's a fellow Jose-Luis Jimenez from University of Colorado Boulder, he said, ‘this is so mind-boggling to me. It just made it obvious that they were full of s**t.’ Now, that's basically what he's saying about these people that are holding onto this liquid droplet crap and that there's no airborne. But we know, for example, when you can't see cigarette smoke, you can't see the perfume odor, but you can smell it that there's stuff in the air, it's airborne, and it's not necessarily three or six feet away. There's something here that doesn't compute in people's minds. And by the way, even by March and April, there were videos like the one that Lydia showed in 2018 that we're circling around to show, hey, this stuff is all over the place. It's not just the mouth going to the other person. So then this group of 36 got together, which included the people we were talking about, other people who I know, like Joe Allen and many really great contributors, and they lobbied the CDC and the WHO to get with it, but it seemed like it took two years.Carl Zimmer (27:32):It was a slow process, yes. Yes. Because well, I mean, the reason that they got together and sort of formed this band is because early on, even at the end of January, beginning of February 2020, people like Joe Allen, people like Linsey Marr, people like Lidia Morawska in Australia, they were trying to raise the alarm. And so, they would say like, oh, I will write up my concerns and I will get it published somewhere. And journals would reject them and reject them and reject them. They'd say, well, we know this isn't true. Or they'd say like, oh, they're already looking into it. Don't worry about it. This is not a reason for concern. All of them independently kept getting rejected. And then at the same time, the World Health Organization was going out of their way to insist that Covid is not airborne. And so, Lidia Morawska just said like, we have to do something. And she, from her home in Australia, marshaled first this group of 36 people, and they tried to get the World Health Organization to listen to them, and they really felt very rebuffed it didn't really work out. So then they went public with a very strong open letter. And the New York Times and other publications covered that and that really started to get things moving. But still, these guidelines and so on were incredibly slow to be updated, let alone what people might actually do to sort of safeguard us from an airborne disease.Eric Topol (29:15):Well, yeah, I mean, we went from March 2020 when it was Captain Obvious with the choir to the end of 2021 with Omicron before this got recognized, which is amazing to me when you look back, right? That here you've got millions of people dying and getting infected, getting Long Covid, all this stuff, and we have this denial of what is the real way of transmission. Now, this was not just a science conflict, this is that we had people saying, you don't need to wear a mask. People like Jerome Adams, the Surgeon General, people like Tony Fauci before there was an adjustment later, oh, you don't need masks. You just stay more than six feet away. And meanwhile, the other parts of the world, as you pointed out in Japan with the three Cs, they're already into, hey, this is airborne and don't go into rooms indoors with a lot of people and clusters and whatnot. How could we be this far off where the leading public health, and this includes the CDC, are giving such bad guidance that basically was promoting Covid spread.Carl Zimmer (30:30):I think there are a number of different reasons, and I've tried to figure that out, and I've talked to people like Anthony Fauci to try to better understand what was going on. And there was a lot of ambiguity at the time and a lot of mixed signals. I think that also in the United States in particular, we were dealing with a really bad history of preparing for pandemics in the sense that the United States actually had said, we might need a lot of masks for a pandemic, which implicitly means that we acknowledge that the next pandemic might to some extent be airborne. At least our healthcare folks are going to need masks, good masks, and they stockpiled them, and then they started using them, and then they didn't really replace them very well, and supplies ran out, or they got old. So you had someone like Rick Bright who was a public health official in the administration in January 2020, trying to tell everybody, hey, we need masks.The Mess with MasksCarl Zimmer (31:56):And people are like, don't worry about it, don't worry about it. Look, if we have a problem with masks, he said this, and he recounted this later. Look, if the health workers run out of masks, we just tell the public just to not use masks and then we'll have enough for the health workers. And Bright was like, that makes no sense. That makes no sense. And lo and behold, there was a shortage among American health workers, and China was having its own health surge, so they were going to be helping us out, and it was chaos. And so, a lot of those messages about telling the public don't wear a mask was don't wear a mask, the healthcare workers need them, and we need to make sure they have enough. And if you think about that, there's a problem there.Carl Zimmer (32:51):Yeah, fine. Why don't the healthcare workers have their own independent supply of masks? And then we can sort of address the question, do masks work in the general community? Which is a legitimate scientific question. I know there are people who are say, oh, masks don't work. There's plenty of studies that show that they can reduce risk. But unfortunately, you actually had people like Fauci himself who were saying like, oh, you might see people wearing masks in other countries. I wouldn't do it. And then just a few weeks later when it was really clear just how bad things were getting, he turns around and says, people should wear masks. But Jerome Adams, who you mentioned, Surgeon General, he gets on TV and he's trying to wrap a cloth around his face and saying, look, you can make your own mask. And it was not ideal, shall we say?Eric Topol (33:55):Oh, no. It just led to mass confusion and the anti-science people were having just a field day for them to say that these are nincompoops. And it just really, when you look back, it's sad. Now, I didn't realize the history of the N95 speaking of healthcare workers and fitted masks, and that was back with the fashion from the bra. I mean, can you tell us about that? That's pretty interesting.Carl Zimmer (34:24):Yeah. Yeah, it's a fascinating story. So there was a woman who was working for 3M. She was consulting with them on just making new products, and she really liked the technology they used for making these sort of gift ribbons and sort of blown-fiber. And she's like, wow, you should think about other stuff. How about a bra? And so, they actually went forward with this sort of sprayed polyester fiber bra, which was getting much nicer than the kind of medieval stuff that women had to put up with before then. And then she's at the same time spending a lot of time in hospitals because a lot of her family was sick with various ailments, and she was looking at these doctors and nurses who were wearing masks, which just weren't fitting them very well. And she thought, wait a minute, you could take a bra cup and just basically fit it on people's faces.Carl Zimmer (35:29):She goes to 3M and is like, hey, what about this? And they're like, hmm, interesting. And at first it didn't seem actually like it worked well against viruses and other pathogens, but it was good on dust. So it started showing up in hardware stores in the 70s, and then there were further experiments that basically figured showed you could essentially kind of amazingly give the material a little static charge. And that was good enough that then if you put it on, it traps droplets that contain viruses and doesn't let them through. So N95s are a really good way to keep viruses from coming into your mouth or going out.Eric Topol (36:14):Yeah. Well, I mean it's striking too, because in the beginning, as you said, when there finally was some consensus that masks could help, there wasn't differentiation between cotton masks, surgical masks, KN95s. And so, all this added to the mix of ambiguity and confusion. So we get to the point finally that we understand the transmission. It took way too long. And that kind of tells the Covid story. And towards the end of the book, you're back at the Skagit Valley Chorale. It's a full circle, just amazing story. Now, it also brings up all lessons that we've learned and where we're headed with this whole knowledge of the aerobiome, which is fascinating. I didn't know that we breathe 2000 to 3000 gallons a day of air, each of us.Every Breath We TakeEric Topol (37:11):Wow, I didn't know. Well, of course, air is a vector for disease. And of course, going back to the Wells, the famous Wells that have been, you've brought them back to light about how we're aerial oysters. So these things in the air, which we're going to get to the California fires, for example, they travel a long ways. Right? We're not talking about six feet here. We're talking about, can you tell us a bit about that?Carl Zimmer (37:42):Well, yeah. So we are releasing living things into the air with every breath, but we're not the only ones. So I'm looking at you and I see beyond you the ocean and the Pacific Ocean. Every time those waves crash down on the surf, it's spewing up vast numbers of tiny droplets, kind of like the ocean's own lungs, spraying up droplets, some of which have bacteria and viruses and other living things. And those go up in the air. The wind catches them, and they blow around. Some of them go very, very high, many, many miles. Some of them go into the clouds and they do blow all over the place. And so, science is really starting to come into its own of studying the planetary wide pattern of the flow of life, not just for oceans, but from the ground, things come out of the ground all of the time. The soil is rich with microbes, and those are rising up. Of course, there’s plants, we are familiar with plants having pollen, but plants themselves are also slathered in fungi and other organisms. They shed those into the air as well. And so, you just have this tremendous swirl of life that how high it can go, nobody's quite sure. They can certainly go up maybe 12 miles, some expeditions, rocket emissions have claimed to find them 40 miles in the air.Carl Zimmer (39:31):It's not clear, but we're talking 10, 20, 30 miles up is where all this life gets. So people call this the aerobiome, and we're living in it. It's like we're in an ocean and we're breathing in that ocean. And so, you are breathing in some of those organisms literally with every breath.Eric Topol (39:50):Yeah, no, it's extraordinary. I mean, it really widens, the book takes us so much more broad than the narrow world of Covid and how that got all off track and gives us the big picture. One of the things that happened more recently post Covid was finally in the US there was the commitment to make buildings safer. That is adopting the principles of ventilation filtration. And I wonder if you could comment at that. And also, do you use your CO2 monitor that you mentioned early in the book? Because a lot of people haven't gotten onto the CO2 monitor.Carl Zimmer (40:33):So yes, I do have a CO2 monitor. It's in the other room. And I take it with me partly to protect my own health, but also partly out of curiosity because carbon dioxide (CO2) in the room is actually a pretty good way of figuring out how much ventilation there is in the room and what your potential risk is of getting sick if someone is breathing out Covid or some other airborne disease. They're not that expensive and they're not that big. And taking them on planes is particularly illuminating. It's just incredible just how high the carbon dioxide rate goes up when you're sitting on the plane, they've closed the doors, you haven't taken off yet, shoots way up. Once again, the air and the filter system starts up, it starts going down, which is good, but then you land and back up again. But in terms of when we're not flying, we're spending a lot of our time indoors. Yeah, so you used the word commitment to describe quality standards.Eric Topol (41:38):What's missing is the money and the action, right?Carl Zimmer (41:42):I think, yeah. I think commitment is putting it a little strongly.Eric Topol (41:45):Yeah. Sorry.Carl Zimmer (41:45):Biden administration is setting targets. They're encouraging that that people meet certain targets. And those people you mentioned like Joe Allen at Harvard have actually been putting together standards like saying, okay, let's say that when you build a new school or a new building, let's say that you make sure that you don't get carbon dioxide readings above this rate. Let's try to get 14 liters per second per person of ventilated fresh air. And they're actually going further. They've actually said, now we think this should be law. We think these should be government mandates. We have government mandates for clean water. We have government mandates for clean food. We don't just say, it'd be nice if your bottled water didn't have cholera on it in it. We'll make a little prize. Who's got the least cholera in their water? We don't do that. We don't expect that. We expect more. We expect when you get the water or if you get anything, you expect it to be clean and you expect people to be following the law. So what Joseph Allen, Lidia Morawska, Linsey Marr and others are saying is like, okay, let's have a law.Eric Topol (43:13):Yeah. No, and I think that distinction, I've interviewed Joe Allen and Linsey Marr on Ground Truths, and they've made these points. And we need the commitment, I should say, we need the law because otherwise it's a good idea that doesn't get actualized. And we know how much keeping ventilation would make schools safer.Carl Zimmer (43:35):Just to jump in for a second, just to circle back to William and Mildred Wells, none of what I just said is new. William and Mildred Wells were saying over and over again in speeches they gave, in letters they wrote to friends they were like, we've had this incredible revolution in the early 1900s of getting clean water and clean food. Why don't we have clean air yet? We deserve clean air. Everyone deserves clean air. And so, really all that people like Linsey Marr and Joseph Allen and others are doing is trying to finally deliver on that call almost a century later.Eric Topol (44:17):Yeah, totally. That's amazing how it's taken all this time and how much disease and morbidity even death could have been prevented. Before I ask about planning for the future, I do want to get your comments about the dirty air with the particulate matter less than 2.5 particles and what we're seeing now with wildfires, of course in Los Angeles, but obviously they're just part of what we're seeing in many parts of the world and what that does, what carries so the dirty air, but also what we're now seeing with the crisis of climate change.Carl Zimmer (45:01):So if you inhale smoke from a wildfire, it's not going to start growing inside of you, but those particles are going to cause a lot of damage. They're going to cause a lot of inflammation. They can cause not just lung damage, but they can potentially cause a bunch of other medical issues. And unfortunately, climate change plus the increasing urbanization of these kinds of environments, like in Southern California where fires, it's a fire ecology already. That is going to be a recipe for more smoke in the air. We will be, unfortunately, seeing more fire. Here in the Northeast, we were dealing with really awful smoke coming all the way from Canada. So this is not a problem that respects borders. And even if there were no wildfires, we still have a huge global, terrible problem with particulate matter coming from cars and coal fire power plants and so on. Several million people, their lives are cut short every year, just day in, day out. And you can see pictures in places like Delhi and India and so on. But there are lots of avoidable deaths in the United States as well, because we're starting to realize that even what we thought were nice low levels of air pollution probably are still killing more people than we realized.Eric Topol (46:53):Yeah, I mean, just this week in Nature is a feature on how this dirty air pollution, the urbanization that’s leading to brain damage, Alzheimer’s, but also as you pointed out, it increases everything, all-cause mortality, cardiovascular, various cancers. I mean, it's just bad news.Carl Zimmer (47:15):And one way in which the aerobiome intersects with what we're talking about is that those little particles floating around, things can live on them and certain species can ride along on these little particles of pollution and then we inhale them. And there's some studies that seem to suggest that maybe pathogens are really benefiting from riding around on these. And also, the wildfire smoke is not just lofting, just bits of dead plant matter into the air. It's lofting vast numbers of bacteria and fungal spores into the air as well. And then those blow very, very far away. It's possible that long distance winds can deliver fungal spores and other microorganisms that can actually cause certain diseases, this Kawasaki disease or Valley fever and so on. Yeah, so everything we're doing is influencing the aerobiome. We're changing the world in so many ways. We're also changing the aerobiome.Eric Topol (48:30):Yeah. And to your point, there were several reports during the pandemic that air pollution potentiated SARS-CoV-2 infections because of that point that you're making that is as a carrier.Carl Zimmer (48:46):Well, I've seen some of those studies and it wasn't clear to me. I'm not sure that SARS-CoV-2 can really survive like long distances outdoors. But it may be that, it kind of weakens people and also sets up their lungs for a serious disease. I'm not as familiar with that research as I'd like to be.Eric Topol (49:11):Yeah, no, it could just be that because they have more inflammation of their lungs that they're just more sensitive to when they get the infection. But there seems like you said, to be some interactions between pathogens and polluted air. I don't know that we want to get into germ warfare because that's whole another topic, but you cover that well, it's very scary stuff.Carl Zimmer (49:37):It’s the dark side of aerobiology.Eric Topol (49:39):Oh my gosh, yes. And then the last thing I wanted just to get into is, if we took this all seriously and learned, which we don't seem to do that well in some respects, wouldn’t we change the way, for example, the way our cities, the way we increase our world of plants and vegetation, rather than just basically take it all down. What can we do in the future to make our ecosystem with air a healthier one?Carl Zimmer (50:17):I think that's a really important question. And it sounds odd, but that's only because it's unfamiliar. And even after all this time and after the rediscovery of a lot of scientists who had been long forgotten, there's still a lot we don't know. So there is suggestive research that when we breathe in air that's blowing over vegetation, forest and so on. That's actually in some ways good for our health. We do have a relationship with the air, and we've had it ever since our ancestors came out the water and started breathing with their lungs. And so, our immune systems may be tuned to not breathing in sterile air, but we don't understand the relationship. And so, I can't say like, oh, well, here's the prescription. We need to be doing this. We don't know.Eric Topol (51:21):Yeah. No, it's fascinating.Carl Zimmer (51:23):We should find out. And there are a few studies going on, but not many I would have to say. And the thing goes for how do we protect indoor spaces and so on? Well, we kind of have an idea of how airborne Covid is. Influenza, we're not that sure and there are lots of other diseases that we just don't know. And you certainly, if a disease is not traveling through the air at all, you don't want to take these measures. But we need to understand they're spread more and it's still very difficult to study these things.Eric Topol (52:00):Yeah, such a great point. Now before we wrap up, is there anything that you want to highlight that I haven't touched on in this amazing book?Carl Zimmer (52:14):I hope that when people read it, they sort of see that science is a messy process and there aren't that many clear villains and good guys in the sense that there can be people who are totally, almost insanely wrong in hindsight about some things and are brilliant visionaries in other ways. And one figure that I learned about was Max von Pettenkofer, who really did the research behind those carbon dioxide meters. He figured out in the mid-1800s that you could figure out the ventilation in a room by looking at the carbon dioxide. We call it the Pettenkofer number, how much CO2 is in the room. Visionary guy also totally refused to believe in the germ theory of disease. He shot it tooth in the nail even. He tried to convince people that cholera was airborne, and he did it. He took a vial. He was an old man. He took a vial full of cholera. The bacteria that caused cholera drank it down to prove his point. He didn't feel well afterwards, but he survived. And he said, that's proof. So this history of science is not the simple story that we imagine it to be.Eric Topol (53:32):Yeah. Well, congratulations. This was a tour de force. You had to put in a lot of work to pull this all together, and you're enlightening us about air like never before. So thanks so much for joining, Carl.Carl Zimmer (53:46):It was a real pleasure. Thanks for having me.**********************************************Thanks for listening, watching or reading Ground Truths. Your subscription is greatly appreciated.If you found this podcast interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths—newsletters, analyses, and podcasts—is free, open-access.Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. And such support is becoming more vital In light of current changes of funding by US biomedical research at NIH and other governmental agencies. Get full access to Ground Truths at erictopol.substack.com/subscribe
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  • Emily Silverman: Storytelling, Uncertainty, and Humanity in Medicine
    Before getting into this new podcast, have you checked out the recent newsletter editions of Ground Truths?—how are gut microbiome drives sugar cravings—the influence of sleep on brain waste clearance and aging—the new findings of microplastics in the brain—the surprise finding about doctors and A.I.In this podcast with Dr. Emily Silverman, an internist and founder of The Nocturnists, an award winning podcast and live show, we discuss what inspired her in medicine, what led to her disillusionment, the essentiality of storytelling, of recognizing uncertainty, the limits of A.I., and promoting humanity in medicine. The audio is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.“Storytelling is medicine's currency. Storytelling is not just an act of self-healing; it may actually create better physicians.”—Emily SilvermanTranscript with links to audio and relevant publications, websitesEric Topol (00:07):Well, hello. This is Eric Topol with Ground Truths, and with me, I am delighted to welcome Dr. Emily Silverman, who is Assistant Volunteer Professor of Medicine at UCSF, an old training grounds for me. And we're going to talk about some of the experience she's had there and she is the Founder of the remarkably recognized podcast, The Nocturnists. It's more than a podcast folks. We'll talk about that too. So Emily, welcome.Emily Silverman (00:40):Thank you for having me.Inspiration by Kate McKinnonEric Topol (00:42):Yeah. Well, I thought I would go back to perhaps when we first synapsed, and it goes back to a piece you wrote in JAMA about going to the Saturday Night Live (SNL) with Kate McKinnon. And it was one of my favorite columns, of course, it brought us together kind of simpatico because you were telling a story that was very personal, and a surprise factor added to it. We'll link to it. But it said, ‘Sometime in 2016, I fell in love with SNL comedian Kate McKinnon.’ You wrote, ‘It was something about her slow-mo swagger; her unilateral dimple, flickering in and out of existence; the way she drinks up her characters and sweats them from her pores.’ I mean, you're an incredible writer, no less podcast interviewer, organizer, doctor. And you talked about my sterile clinical life, which was kind of maybe a warning of things to come and about the fact that there's two very different career paths, comedy and medicine. One could argue they are in essence the same. So maybe you could tell us about that experience and about Kate McKinnon who, I mean, she's amazing.Emily Silverman (02:09):You're making me blush. Thank you for the kind words about the piece and about the writing, and I'm happy to give you a bit of background on that piece and where it came from. So I was in my internal medicine residency at UCSF and about halfway through residency really found myself hitting a wall. And that is actually what gave birth to The Nocturnists, which is the medical storytelling program that I run. But I think another symptom of my hitting that wall, so to speak, and we can talk more about what exactly that is and what that means, was me really looking outside of medicine and also outside of my typical day-to-day routine to try to find things that were a part of me that I had lost or I had lost touch with those aspects of myself. And one aspect of myself that I felt like I had lost touch to was my humorous side, my sense of humor, my silly side even you could say.Emily Silverman (03:17):And throughout my life I have this pattern where when I'm trying to get back in touch with a side of myself, I usually find somebody who represents that and sort of study it, I guess you could say. So in this case, for whatever reason that landed on Kate McKinnon, I just loved the surrealism of her comedy. I loved how absurd she is and loved her personality and so many things. Everything that you just read and really found her and her comedy as an escape, as a way to escape the seriousness of what I was doing on a day-to-day basis in the hospital and reconnect with those humorous sides of myself. So that's the understory. And then the story of the article is, I happened to be traveling to New York for a different reason and found myself standing in line outside of 30 Rock, hoping to get into Saturday Night Live. And there was basically a zero chance that we were going to get in. And part of the reason why is the musical guest that week was a K-pop band called BTS, which is one of the most famous bands in the world. And there were BTS fans like camped out in three circles around 30 Rock. So that week in particular, it was especially difficult to get in. There was just too many people in line. And we were at the very end of the line.Eric Topol (04:43):And it was in the pouring rain, too.Emily Silverman (04:45):And it was pouring rain. And my husband, God bless him, was there with me and he was like, what are we doing? And I was like, I don't know. I just have a feeling that we should stay in line, just go with it. So we did stay in line and then in the morning we got a number, and the way it works is you get your number and then that evening you show up with your number and our number was some crazy number that we weren't going to get in. But then that evening when we went back with our number to wait in line again to get in, what ended up happening is a young woman in the NBC gift shop, she passed out in the middle of the gift shop and I was right there. And so, I went over to her and was asking her questions and trying to help her out.Emily Silverman (05:27):And fortunately, she was fine. I think she just was dehydrated or something, and the security guards were so appreciative. And the next thing I knew, they were sweeping me backstage and up a staircase and in an elevator and they said, thank you so much for your service, welcome to Saturday Night Live. So it became this interesting moment where the very thing that I had been escaping from like medicine and serving and helping people ended up being the thing that gave me access, back to that side of myself, the humorous side. So it was just felt kind of cosmic, one of those moments, like those butterfly wing flapping moments that I decided to write about it and JAMA was kindly willing to publish it.Eric Topol (06:15):Well, it drew me to you and recognize you as quite an extraordinary talent. I don't know if you get recognized enough for the writing because it's quite extraordinary, as we'll talk about in some of your other pieces in the New York Times and in other JAMA journals and on and on. But one thing I just would note is that I resort to comedy a lot to deal with hard times, like the dark times we're in right now, so instead of watching the news, I watch Jimmy Kimmel's monologue or Colbert's monologue or the Comedy Show, anything to relieve some of the darkness that we're dealing with right at the moment. And we're going to get back to comedy because now I want to go back, that was in 2019 when you wrote that, but it was in 2016 when you formed The Nocturnists. Now, before you get to that critical path in your career of this new podcast and how it blossomed, how it grew is just beyond belief. But maybe you could tell us about your residency, what was going on while you were a medical resident at UCSF, because I can identify with that. Well, like any medical residency, it's pretty grueling experience and what that was like for you.Medical ResidencyEmily Silverman (07:45):There were so many wonderful positive aspects of residency and there were so many challenges and difficult aspects of residency. It's all mixed up into this sticky, complicated web of what residency was. On the positive side, some of the most amazing clinicians I've ever met are at UCSF and whether that was seasoned attendings or chief residents who they just seemed to have so many skills, the clinical, the research, the teaching, just amazing, amazing high caliber people to learn from. And of course, the patient population. And at UCSF, we rotate at three different hospitals, the UCSF hospital, the SF General Hospital, which is the public county hospital and the VA hospital. So having the opportunity to see these different patient populations was just such a rich clinical and storytelling opportunity. So there was a lot there that was good, but I really struggled with a few things.Emily Silverman (08:48):So one was the fact that I spent so much of my sitting in front of a computer, and that was not something that I expected when I went into medicine when I was young. And I started to learn more about that and how that happened and when that changed. And then it wasn't just the computer, it was the computer and other types of paperwork or bureaucratic hurdles or administrative creep and just all the different ways that the day-to-day work of physicians was being overtaken by nonclinical work. And that doesn't just mean thinking about our patients, but that also means going to the bedside, sitting with our patients, getting to know them, getting to know their families. And so, I started to think a lot about clinical medicine and what it really means to practice and how that's different from how it was 10, 20, 40 years ago.Emily Silverman (09:43):And then the other part of it that I was really struggling with was aspects of medical culture. The fact that we were working 80 hour weeks, I was working 28 hour shifts every fourth night, every other month. And the toll that took on my body, and I developed some health issues as a result of that and just felt in a way, here I am a doctor in the business of protecting and preserving health and my own health is kind of being run into the ground. And that didn't make sense to me. And so, I started asking questions about that. So there was a lot there. And at first I thought, maybe this is a me thing or maybe this is a California thing. And eventually I realized this was a national thing and I started to notice headlines, op-eds, articles, even pre-Covid about the epidemic of clinician burnout in this country.Emily Silverman (10:40):And there are so many different facets to that. There's the moral injury aspect of it, there's the working conditions and understaffing aspect of it. I learned about how physicians were starting to think about unionizing, which was something that had not really been in the physician, I think consciousness 20, 40 years ago. So just started learning a lot about how medicine had evolved and was continuing to evolve and felt myself wanting to create a space where people could come together and tell stories about what that was like and what their experience was. And that was the birth of The Nocturnists. But I guess that wasn't really your question. Your question was about residency.Birth of The NocturnistsEric Topol (11:20):That's a good answer actually. It kind of gives the background, lays the foundation of how you took a fork in the road here, which we're going to get into now. We're going to link to The Nocturnists website of course, but you have an intro there about, ‘shatter the myth of the “physician God” reveal the truth: that healthcare workers are human, just like everyone else, and that our humanity is our strength, not our weakness.’ And that's a very deep and important point that you make to get people interested in The Nocturnists. But now you finished your residency, you're now on the faculty, assistant professor at UCSF, and then you have this gathering that you hadn't already named it the Nocturnists yet had you?Emily Silverman (12:15):I named it in residency.Eric Topol (12:17):Oh, okay in residency. So this was even before you had finished, you started the podcast before you finished?Emily Silverman (12:25):Correct. Before we were a podcast, we were a live show. So the very first live show was in 2016, so I consider that the birth year of the program. And then I graduated residency in 2017, so I started it about halfway through residency.Eric Topol (12:39):Got it. So tell us about that first live show. I mean, that's pretty amazing. Yeah.Emily Silverman (12:46):Yeah. I went to a live taping of The Moth in San Francisco, which some of your listeners may know. The Moth is a live storytelling show in the US, it's often on the radio on NPR. You may have heard it. It's a very ancient way of telling stories. It's more like monologues, people standing up on stage and just spontaneously telling a story the way you would around a campfire or something like that. It's not hyper scripted or anything like that. So I came out of that event feeling really inspired, and I had always loved live performance and live theater. I grew up going to the theater and ended up deciding that I would try that with my community, with the clinicians in my community. So the very first show that we did was in 2016, it was about 40 people in this living room of this Victorian mansion in San Francisco.Emily Silverman (13:42):It was a co-op where different people lived. In the living space, they occasionally rented out for meetings and presentations and gatherings, and it was like $90. So I rented that out and people came and residents, physician residents told stories, but a couple of faculty came and told stories as well. And I think that was a really nice way to set the stage that this wasn't just a med student thing or a resident thing, this was for everybody. And there was definitely an electricity in the air at the show. I think a lot of people were experiencing the same thing I was experiencing, which was having questions about the medical system, having questions about medical culture, trying to figure out how they fit into all of that, and in my case, missing my creative side, missing my humorous side. And so, I think that's the reason people came and showed up was that it wasn't just a night out of entertainment and coming was really more out of a hunger to reconnect with some aspect of ourselves that maybe gets lost as we go through our training. So that was the first show, and people kept asking, when are you going to do another one? When are you going to do another one? The rest is history. We have done many shows since then. So that was the beginning.Eric Topol (14:58):Well, you've been to many cities for live shows, you sold out hundreds and hundreds of seats, and it's a big thing now. I mean, it's been widely recognized by all sorts of awards, and the podcast and the shows. It's quite incredible. So a derivative of The Moth to medicine, is it always medical people telling stories? Does it also include patients and non-medical people?Emily Silverman (15:28):So we're nine years in, and for the first several years, this question came up a lot. What about the patient voice? What about the patient perspective? And the way that I would respond to that question was two ways. First, I would say the line between doctor and patient isn't as bright as you would think. Doctors are also patients. We also have bodies. We also have our own medical and psychiatric conditions and our own doctors and providers who take care of us. So we're all human, we're all patients. That said, I recognize that the doctor, the clinician has its own unique place in society and its own unique perspective. And that's really what I was trying to focus on. I think when you're making art or when you're making a community, people ask a lot about audience. And for me, for those first several years, I was thinking of The Nocturnists as a love letter by healthcare to healthcare. It was something that I was making for and with my community. And in recent months and years, I have been wondering about, okay, what would a new project look like that pulls in the patient voice a bit more? Because we did the clinician thing for several years, and I think there's been a lot of wonderful stories and material that's come out of that. But I'm always itching for the next thing. And it was actually an interview on the podcast I just did with this wonderful person, Susannah Fox.Eric Topol (17:04):Oh yeah, I know Susannah. Sure.Emily Silverman (17:04):Yeah. She was the chief technology officer at the Department of Health and Human Services from 2015 to 2017, I want to say. And she wrote a book called Rebel Health, which is all about patients who weren't getting what they needed from doctors and researchers and scientists. And so, they ended up building things on their own, whether it was building medical devices on their own, on the fringes or building disease registries and communities, online disease communities on their own. And it was a fabulous book and it was a fabulous interview. And ever since then I've been thinking about what might a project look like through The Nocturnists storytelling ethos that centers and focuses on the patient voice, but that's a new thought. For the first several years, it was much more focused on frontline clinicians as our audience.Why is Storytelling in Medicine so Important?Eric Topol (17:55):And then I mean the storytelling people that come to the shows or listen to the podcast, many of them are not physicians, they're patients, all sorts of people that are not part of the initial focus of who's telling stories. Now, I want to get into storytelling. This is, as you point out in another JAMA piece that kind of was introducing The Nocturnists to the medical community. We’ll link to that, but a few classic lines, ‘Storytelling is medicine's currency. Storytelling is not just an act of self-healing; it may actually create better physicians.’ And then also toward the end of the piece, “Some people also believe that it is unprofessional for physicians to be emotionally vulnerable in front of colleagues. The greater risk, however, is for the healthcare professional to appear superhuman by pretending to not feel grief, suffer from moral distress, laugh at work, or need rest.” And finally, ‘storytelling may actually help to humanize the physician.’ So tell us about storytelling because obviously it's one of the most important, if not the most important form of communication between humans. You nailed it, how important it is in medicine, so how do you conceive it? What makes it storytelling for you?Emily Silverman (19:25):It's so surreal to hear you read those words because I haven't read them myself in several years, and I was like, oh, what piece is he talking about? But I remember now. Look, you on your program have had a lot of guests on to talk about the massive changes in medicine that have occurred, including the consolidation of it, the corporatization of it, the ways in which the individual community practice is becoming more and more endangered. And instead what's happening is practices are getting gobbled up and consolidated into these mega corporations and so on and so forth. And I just had on the podcast, the writer Dhruv Khullar, who wrote a piece in the New Yorker recently called the Gilded Age of Medicine is here. And he talks a lot about this and about how there are some benefits to this. For example, if you group practices together, you can have economies of scale and efficiencies that you can't when you have all these scattered individual self-owned practices.Emily Silverman (20:26):But I do think there are risks associated with the corporatization of healthcare. The more that healthcare starts to feel like a conveyor belt or a factory or fast food like the McDonald's of healthcare, MinuteClinic, 15 minutes in and out, the more that we risk losing the heart and soul of medicine and what it is; which is it's not as simple as bringing in your car and getting an oil change. I mean, sometimes it is. Sometimes you just need a strep swab and some antibiotics and call it a day. But I think medicine at its best is more grounded in relationships. And so, what is the modern era of medicine doing to those relationships? Those longitudinal relationships, those deeper relationships where you're not just intimately familiar with a patient's creatinine trend or their kidney biopsy results, but you know your patient and their family, and you know their life story a little bit.Emily Silverman (21:26):And you can understand how the context of their renal disease, for example, fits into the larger story of their life. I think that context is so important. And so, medicine in a way is, it is a science, but it's also an art. And in some ways it's actually kind of an applied science where you're taking science and applying it to the messy, chaotic truth of human beings and their families and their communities. So I think storytelling is a really important way to think of medicine. And then a step beyond that, not just with the doctor patient interaction, but just with the medical community and medical culture at large. I think helping to make the culture healthier and get people out of this clamped down place where they feel like they have to be a superhuman robot. Let's crack that open a little bit and remind ourselves that just like our patients are human beings, so are we. And so, if we can leverage that, and this is also part of the AI conversation that we're having is like, is AI ever going to fully substitute for a physician? Like, well, what does a physician have that AI doesn't? What does a human being have that a machine doesn’t? And I think these are really deep questions. And so, I think storytelling is definitely related to that. And so, there's just a lot of rich conversation there in those spaces, and I think storytelling is a great way into those conversations.Eric Topol (22:57):Yeah. We'll talk about AI too, because that's a fascinating future challenge to this. But while you're talking about it, it reminds me that I'm in clinic every week. My fellow and I have really worked on him to talk to the patients about their social history. They seem to omit that and often times to crack the case of what's really going on and what gets the patient excited or what their concerns are really indexed to is learning about what do they do and what makes them tick and all that sort of thing. So it goes every which way in medicine. And the one that you've really brought out is the one where clinicians are telling their stories to others. Now you've had hundreds and hundreds of these physician related stories. What are some of the ones that you think are most memorable? Either for vulnerability or comedy or something that grabbed you because you’ve seen so many, and heard so many now.A Memorable StoryEmily Silverman (24:02):It's true. There have been hundreds of physician stories that have come through the podcast and some non-physician. I mean, we are, because I'm a doctor, I find that the work tends to be more focused around doctors. But we have brought in nurses and other types of clinicians to tell their stories as well, particularly around Covid. We had a lot of diversity of healthcare professionals who contributed their stories. One that stands out is dialogue that we featured in our live show. So most of our live shows up until that point had featured monologues. So people would stand on stage, tell their story one by one, but for this story, we had two people standing on stage and they alternated telling their story. There was a little bit more scripting and massaging involved. There was still some level of improvisation and spontaneity, but it added a really interesting texture to the story.Emily Silverman (24:58):And basically, it was a story of these two physicians who during Covid, one of them came out of retirement and the other one I think switched fields and was going to be doing different work during Covid as so many of us did. And they were called to New York as volunteers and ended up meeting in the JFK airport in 2020 and it was like an empty airport. And they meet there and they start talking and they realize that they have all these strange things in common, and they sit next to each other on the plane and they're kind of bonding and connecting about what they're about to do, which is go volunteer at the peak of Covid in New York City, and they end up staying in hotels in New York and doing the work. A lot of it really, really just harrowing work. And they stay connected and they bond and they call each other up in the evenings, how was your day? How was your day? And they stay friends. And so, instead of framing it in my mind as a Covid story, I frame it more as a friendship story. And that one just was really special, I think because of the seriousness of the themes, because of the heartwarming aspect of the friendship and then also because of the format, it was just really unusual to have a dialogue over a monologue. So that was one that stood out. And I believe the title of it is Serendipity in Shutdown. So you can check that out.Eric Topol (26:23):That's great. Love it. And I should point out that a lot of these clinical audio diaries are in the US Library of Congress, so it isn't like these are just out there, they're actually archived and it's pretty impressive. While I have you on some of these themes, I mean you're now getting into some bigger topics. You mentioned the pandemic. Another one is Black Voices in Healthcare, and you also got deep into Shame in Medicine. And now I see that you've got a new one coming on Uncertainty in Medicine. Can you give us the skinny on what the Uncertainty in Medicine's going to be all about?Uncertainty in MedicineEmily Silverman (27:14):Yes. So the American Board of Internal Medicine put out a call for grant proposals related to the topic of uncertainty in medicine. And the reason they did that is they identified uncertainty as an area of growth, an area where maybe we don't talk about it enough or we're not really sure how to tolerate it or handle it or teach about it or work with it, work through it in our practice. And they saw that as an area of need. So they put out this call for grants and we put together a grant proposal to do a podcast series on uncertainty in medicine. And we're fortunate enough to be one of the three awardees of that grant. And we've been working on that for the last year. And it's been really interesting, really interesting because the place my mind went first with uncertainty is diagnostic uncertainty.Emily Silverman (28:07):And so, we cover that. We cover diagnostic odyssey and how we cope with the fact that we don't know and things like that. But then there's also so many other domains where uncertainty comes up. There's uncertainties around treatment. What do we do when we don't know if the treatment's working or how to assess whether it's working or it's not working and we don't know why. Or managing complex scenarios where it's not clear the best way to proceed, and how do we hold that uncertainty? Prognostic uncertainty is another area. And then all of the uncertainty that pops up related to the systems issues in healthcare. So for example, we spoke to somebody who was diagnosed with colon cancer, metastatic to the liver, ended up having a bunch of radiation of the mets in the liver and then got all this liver scarring and then got liver failure and then needed a liver transplant and saw this decorated transplant surgeon who recommended the transplant was already to have that done.Emily Silverman (29:06):And then the insurance denied the liver transplant. And so, dealing with the uncertainty of, I know that I need this organ transplant, but the coverage isn't going to happen, and the spoiler alert is that he ended up appealing several times and moving forward and getting his transplant. So that one has a happy ending, but some people don't. And so, thinking about uncertainty coming up in those ways as well for patients. So for the last year we've been trying to gather these stories and organize them by theme and figure out what are the most salient points. The other exciting thing we've done with the uncertainty series is we've looked to people outside of medicine who navigate high uncertainty environments to see if they have any wisdom or advice to share with the medical community. So for example, we recently interviewed an admiral in the Navy. And this person who was an admiral in the Navy for many years and had to navigate wartime scenarios and also had to navigate humanitarian relief scenarios and how does he think about being in command and dealing with people and resources and it is life or death and holding uncertainty and managing it.Emily Silverman (30:18):And he had a lot of interesting things to say about that. Similarly, we spoke to an improvisational dancer who his whole job is to get on stage and he doesn't know what's going to happen. And to me, that sounds terrifying. So it's like how do you deal with that and who would choose that? And so, that's been really fun too, to again, go outside the walls of medicine and see what we can glean and learn from people operating in these different contexts and how we might be able to apply some of those.Eric Topol (30:51):Yeah, I mean this is such a big topic because had the medical community been better in communicating uncertainties in medicine, the public trust during the pandemic could have been much higher. And this has led to some of the real challenges that we're seeing there. So I'm looking forward to that series of new additions in The Nocturnists. Now, when you get this group together to have the live show, I take it that they're not rehearsed. You don't really know much about what they're going to do. I mean, it's kind of like the opposite, the un-TED show. TED Talk, whereby those people, they have to practice in Vancouver wherever for a whole week. It's ridiculous. But here, do you just kind of let them go and tell their story or what?Emily Silverman (31:44):In the beginning it was more open mic, it was more let them go. And then as the years went on, we moved more toward a TED model where we would pair storytellers with a story coach, and they would work together pretty intensively in the six to eight weeks leading up to the event to craft the story. That said, it was very important to us that people not recite an essay that they memorized word for word, which surprise, surprise physicians really love that idea. We're like, we're so good at memorization and we love certainty. We love knowing word for word what's going to come. And so, it's really more of this hybrid approach where we would help people get in touch with, all right, what are the five main beats of your story? Where are we opening? Where are we closing? How do we get there?Emily Silverman (32:34):And so, we'd have a loose outline so that people knew roughly what was going to, but then it wasn't until the night of that we'd fill in the blanks and just kind of see what happens. And that was really exciting because a lot of unexpected things happened. Certain stories that we thought would be really comedic ended up landing with a much more serious and thoughtful tone and vice versa. Some of the stories that we thought were really heavy would unexpectedly get laughs in places that we didn't expect. So I think the magic of live audience is, I guess you could say uncertainty of not quite knowing what's going to happen, and sort of a one time night.Eric Topol (33:17):I’d like to have a storytelling coach. That'd be cool. I mean, we could always be better. I mean, it takes me back to the first story you told with the Saturday Night Live and Kate McKinnon, you told the story, it was so great. But to make telling your story, so it's even more interesting, captivating and expressing more emotion and vulnerability and what makes the human side. I mean, that's what I think we all could do, you never could do it perfectly. I mean, that's kind of interesting how you organize that. Alright, well now I want to go back to your career for a moment because you got into The Nocturnists and these shows and you were gradually, I guess here we are in the middle and still a global burnout, depression, suicide among clinicians, especially physicians, but across the board. And you're weaning your time as a faculty member at UCSF. So what was going through your mind in your life at that time? I guess that takes us to now, too.A Career MoveEmily Silverman (34:36):Yeah, when I was a little kid, I always wanted to doctor and fully intended when I went to med school and residency to find my way as a physician and didn't really think I would be doing much else. I mean, I'd always love reading and writing and the arts, but I never quite thought that that would become as big of a piece of my career as it has become. But what ended up happening is I finished residency. I took a job in the division of hospital medicine at SF General and worked as a hospitalist for about four years and was doing that and balancing with my medical storytelling nonprofit and eventually realized that it wasn't quite working, it wasn't the right fit. And ended up taking a step back and taking a little break from medicine for a while to try to figure out how am I going to balance this?Emily Silverman (35:26):Am I going to shift and go full medicine and retire The Nocturnists? Am I going to go full art, creative journalism, writing and leave clinical medicine behind? Or am I going to continue to proceed in this more hybrid way where I do a little bit of practicing, and I do a little bit of creative on the side? And thus far, I have continued to pursue that middle road. So I ended up starting a new outpatient job, a part-time job that's actually outside of UCSF. I'm still on faculty at UCSF, but my practice now is in private practice. And so, I do that two days a week and it feeds me in a lot of ways and I'm really glad that I've continued to keep that part of myself alive. And then the rest of the days of the week I work from home and some of that is charting and doing clinical work and some of that time is podcasting and working on these other creative projects. So that's where I've landed right now. And I don't know what it will look like in 5, 10, 20 years, but for now it seems to be working.Taking On EpicEric Topol (36:31):Yeah. Well, I think it's great that you've found the right kind of balance and also the channel for getting your exceptional talent, your niche if you will, in medicine to get it out there because people I think are really deriving a lot of benefit from that. Now, another piece you wrote in the New York Times, I just want to touch on because it is tied to the burnout story. This was a great op-ed, Our Hospital's New Software Frets About My ‘Deficiencies’ and I want to just warn the listeners or readers or watchers that Epic, this company that you wrote about has non-disparaging agreements with hospitals, censors hospitals and doctors to say anything bad about Epic. So when anybody ever writes something, particularly if it's published in a widely read place, the Epic company doesn't like that and they squash it and whatnot. So what was in your mind when you were writing this op-ed about Epic?Emily Silverman (37:39):So this came out of personal experience that I had where, and maybe this is some of the reason why the hospital medicine work wore me down so much is the frequent messages and alerts and popups just having a lot of fatigue with that. But also what the popups were saying, the language that they used. So you'd open up your electronic chart and a message would pop up and it would say, you are deficient, or it would say you are a delinquent. And it was this scary red box with an upside down exclamation point or something. And it really started to get to me, and this was definitely in that phase of my life and career where I was peak burnout and just kind of raging into the machine a little bit, you could say, I think right now I'm somewhat past that. I think part of the reason why is, I've been able to get myself out into a more sustainable situation, but ended up, it actually came out of me, this piece poured out of me one night.Emily Silverman (38:37):It was like two, three in the morning and my laptop was open and I was laying in bed and my husband was like, go to sleep, go to sleep. And I said, no, this wants to come out, these moments where things just, you just want to give birth, I guess, to something that wants to come out. So I wrote this long piece about Epic and how tone deaf these messages are and how clinicians are, they're working really hard in a really difficult system and just the lack of sensitivity of that language and ended up pitching that to the New York Times. And I think there was something in there that they appreciated about that. There was some humor in there actually. Maybe my Kate McKinnon side came out a little bit. So yes, that piece came out and I think I did get a message or two from a couple folks who worked at Epic who weren't thrilled.Eric Topol (39:33):They didn't threaten to sue you or anything though, right?Emily Silverman (39:35):They didn't. NoEric Topol (39:37):Good.Emily Silverman (39:37):Fortunately, yeah.Medicine and A.I.Eric Topol (39:38):Yeah. Wow. Yeah, it was great. And we'll link to that, too. Now, as they say in comedy, we're going to have a callback. We're going to go to AI, which we talked about and touched on. And of course, one of the things AI is thought that it could help reduce the burden of data clerk work that you've talked about and certainly affected you and affects every person in working in medicine. But I wanted to get to this. For me, it was like a ChatGPT moment of November 2022. Recently, I don’t know if you've ever delved into NotebookLM.Emily Silverman (40:18):I have.Eric Topol (40:19):Okay, so you'll recognize this. You put in a PDF and then you hit audio and it generates a podcast of two agents, a man and a woman who are lively, who accurately take, it could be the most complex science, it could be a book, and you can put 50 of these things in and they have a really engaging conversation that even gets away from some of the direct subject matter and it's humanoid. What do you think about that?Emily Silverman (40:57):Well, a lot of what I know about AI, I learned from your book, Eric. And from the subsequent conversation that we had when you came on my podcast to talk about your book. So I'm not sure what I could teach you about this topic that you don't already know, but I think it's a deeply existential question about what it means to be human and how machine intelligence augments that, replaces that, threatens that. I don't really know how to put it. I had Jamie Metzl on the podcast. He's this great historian and science policy expert, and he was saying, I don't like the phrase artificial intelligence because I don't think that's what we're making. I think we're making machine intelligence and that's different from human intelligence. And one of the differences is human beings have physical bodies. So being a human is an embodied experience.Emily Silverman (41:57):A machine can’t enjoy, I was going to say a cheeseburger and I was like, wait, I'm talking to a cardiologist. So a machine intelligence being can't enjoy a cucumber salad, a machine intelligence can't feel the endorphins of exercise or have sex or just have all of these other experiences that human beings have because they have bodies. Now, does empathy and emotion and human connection and relationships also fall into that category? I don't know. What is the substrate of empathy? What is the substrate of human connection and relationships and experience? Can it be reduced to zeros and ones or whatever, quantum computing, half zeros and half ones existing simultaneously on a vibrating plane, or is there something uniquely human about that? And I actually don't know the answer or where the edges are. And I think in 5, 10, 20 years, we'll know a lot more about what that is and what that means.Emily Silverman (42:55):What does that mean for medicine? I don't know about the human piece of it, but I think just practically speaking, I believe it will transform the way that we do medicine on so many levels. And this is what your book is about. Some of it is image analysis and EKG analysis, X-ray analysis and MRI analysis. And some of it is cognition, like diagnostic reasoning, clinical reasoning, things like that. I already use OpenEvidence all the time. I don't know if you use it. It's this basically a search engine kind of GPT like search engine that's trained on high quality medical evidence. I'm always going to OpenEvidence with questions. And I actually saw a headline recently, oh gosh, I'll have to fish it out and email it to you and you can link it in the show notes. But it's a little bit about how medical education and also medical certification and testing is going to have to quickly bring itself up to speed on this.Emily Silverman (43:56):The USMLE Step 1 exam, which all physicians in the US have to pass in order to practice medicine. When I took it anyway, which was back in I think 2012, 2013, was very recall based. It was very much based on memorization and regurgitation. Not all, some of it was inference and analysis and problem solving, but a lot of it was memorization. And as you said, I think Eric on our interview on my podcast, that the era of the brainiac memorizing Doogie Howser physician is over. It's not about that anymore. We can outsource that to machines. That's actually one of the things that we can outsource. So I'm excited to see how it evolves. I hope that medical schools and hospitals and institutions find ways safely, of course, to embrace and use this technology because I think it can do a lot of good, which is also what your book is about, the optimistic lens of your book.Eric Topol (44:55):Well, what I like though is that what you're trying to do in your work that you're passionate about is bringing back and amplifying humanity. Enriching the humanity in medicine. Whether that's physicians understanding themselves better and realizing that they are not just to be expected to be superhuman or non-human or whatever, to how we communicate, how we feel, experience the care of patients, the privilege of care of patients. So that's what I love about your efforts to do that. And I also think that people keep talking about artificial general intelligence (AGI), but that's not what we are talking about here today. We're talking about human emotions. Machines don't cry, they don't laugh. They don't really bond with humans, although they try to. I don't know that you could ever, so this fixation on AGI is different than what we're talking about in medicine. And I know you’re destined to be a leader in that you already are. But I hope you'll write a book about medical storytelling and the humanity and medicine, because a natural for this and you're writing it is just great. Have you thought about doing that?Emily Silverman (46:24):It's very kind of you to say. I have thought about if I were to embark on a book project, what would that look like? And I have a few different ideas and I'm not sure. I'm not sure. Maybe I'll consult with you offline about that.Eric Topol (46:42):Alright, well I'd like to encourage you because having read your pieces that some of them cited here you have it. You really are a communicator extraordinaire. So anyway, Emily, thank you for joining today. I really enjoyed our conversation and your mission not just to be a physician, which is obviously important, but also to try to enhance the humanity in medicine, in the medical community particularly. So thank you.Emily Silverman (47:14):Thank you. Thank you for having me.***************************************Thanks for listening, watching or reading Ground Truths. Your subscription is greatly appreciated.If you found this podcast interesting please share it!That makes the work involved in putting these together especially worthwhile.All content on Ground Truths—newsletters, analyses, and podcasts—is free, open-access.Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. And such support is becoming more vital In light of current changes of funding by US biomedical research at NIH and other governmental agencies. Get full access to Ground Truths at erictopol.substack.com/subscribe
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