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Fauna Bio Awakens Medicine to the Mysteries of Hibernation

Why is hibernation something that bears and squirrels do, but humans don’t? Even more interesting, what’s going on inside a hibernating animal, on a physiological and genetic level, that allows them to survive the winter in a near-comatose state without freezing to death and without ingesting any food or water? And what can we learn about that process that might inform human medicine?

Those are the big questions being investigated right now by a four-year-old startup in California called Fauna Bio. And Harry‘s guests today are two of Fauna Bio’s three founding scientists: Ashley Zehnder and Linda Goodman. They explain how they got interested in hibernation as a possible model for how humans could protect themselves from disease, and how progress in comparative genomics over the last few years has made it possible to start to answer that question at the level of gene and protein interactions. The work is shedding light on a previously neglected area of animal behavior that could yield new insights for treating everything from neurodegenerative diseases to cancer.

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Harry Glorikian: Hello. I’m Harry Glorikian, and this is The Harry Glorikian Show, where we explore how technology is changing everything we know about healthcare.

It’s April and spring is well underway, even though it’s been a pretty cold one so far here in New England.

It’s the kind of weather that makes you want to pull the covers over your head in the morning and just sleep in.

Or maybe just hibernate like a bear until summer is really here.

But when you think about it, what is hibernation? Why is it something that bears and squirrels do, but humans don’t?

Even more interesting, what’s going on inside a hibernating animal, physiologically, that allows them to survive all winter without freezing to death and without ingesting any food or water?

And what can we learn about that process that might inform human medicine?

Those are the big questions being investigated right now by a four-year-old startup in California called Fauna Bio

And my guests today are two of Fauna Bio’s three founding scientists: Ashley Zehnder and Linda Goodman.

I asked them to explain how they got interested in hibernation as a possible model for how humans could protect themselves from disease.

…And how progress in comparative genomics over the last few years has made it possible to start to answer that question at the level of gene and protein interactions.

We’ve always looked to the natural world, especially the world of plants, for insights into biochemistry that could inspire new drugs.

But what’s exciting to me about Fauna Bio is that they’re shining a light on a previously neglected area of animal behavior that could yield new insights for treating everything from neurodegenerative diseases to cancer.

So, here’s my conversation with Ashley Zehnder and Linda Goodman.

Harry Glorikian: Ashley. Linda, welcome to the show.

Ashley Zehnder: Thanks, Harry, we’re excited to be here today. It’s going to be fun.

Linda Goodman: Yeah, thanks for having us.

Harry Glorikian: Yeah, I mean, well, you guys are someplace sunny and warm, and I’m actually I shouldn’t say that it’s actually sunny right now on the East Coast. So I’m not I’m not.

Linda Goodman: Don’t jinx yourself.

Harry Glorikian: But the temperature is going to drop. Like to I think they said 18. So everything will freeze tonight for sure. So it’ll, you know, it’s one of those days, but. I want to jump right into this because we’ve got a lot of ground to cover. Like there’s so many questions that I have after sort of looking into the company and sort of digging in and, you know, but even before we jump into what you’re working on. Right, I really want to talk about hibernation. Maybe because I’m jealous and I’d like to be able to hibernate. I have sleep apnea. So sleep is a problem. But humans don’t hibernate. But there’s a ton of other mammalian species that that do. And sometimes I do feel, though, that my teenager hibernates, but that’s a different issue. So, but, what what is interesting to you about hibernation from a physiological point of view. What what goes on with metabolism or gene expression during hibernation, that’s that’s not found in humans, but that could be relevant to human health?

Ashley Zehnder: Yeah, I think this is a great question, Harry, because I think both Linda and I came to fauna from different backgrounds. I came from veterinary science, Linda from comparative genomics. We can go into our details later, but neither of us really appreciated the amazing physiology of these species. There are some of the most extreme mammals on the planet, and there are hibernating bears and literally every group of mammals. Right. This is something Linda specializes in. But there are primates in Madagascar that hibernate very similar to the 39 ground squirrels that we tend to work with. So it’s this really deeply conserved trait in mammals, including primates. And, you know, it kind of highlights for us what our genes can do when they’re adapted for extreme environments. And so that’s kind of the lens that we take when we look at hibernation. It’s how do these species protect their own tissues from being nearly frozen for six, seven months out of the year, having to protect their brains, their hearts, all their vital organs? They’re not eating, they’re not drinking. They’re not moving for these really deep bodied hibernaters. When you think of 100 kilogram animal that’s not eating for seven months, how do they survive that? Right. And it has to do with metabolic rates that change 200- to 300-fold over the course of a couple of hours. It has to do with oxygenation changes and protection from oxidative stress and ischemia reperfusion. And so if you look at a tissue by tissue level, you can start to see how these animals are finally adapted to protecting themselves from from damage. And then we can start to say, well, this is similar damage to what we see in human diseases. And that’s why this is such an interesting system, because it’s so dynamic and because it happens across so many groups of mammals, it really lends itself to this comparative genomics approach that we take to drug discovery.

Harry Glorikian: Yeah. Because I was wondering sort of like what ways of healing from different sort of traumas and conditions do hibernating animals have that that humans don’t, that we sort of maybe wish we did? It’s sort of like, you know, almost Marvel or one of those things where you like go to sleep, you wake up, you’ve totally healed again, which kind of be kind of be cool. Yeah. So, you know. But when did scientists first begin to think about whether having a better understanding of hibernation might help us solve? Some of these riddles that we have in human health. I mean, it surely it can’t be like a new concept. It has to go further back. I mean, what has changed recently to make it more actionable? I mean, is it, you know, omics, costs coming down that are making it easier, computational capabilities that are, you know, making all these come together? I mean, those. What do you guys. What’s. What’s the answer? You guys know the answer better than I do.

Ashley Zehnder: I’ll comment on a little bit on the physiology, and I will let Linda talk about the data revolution, because that’s that’s really what she knows very intimately. So from a physiology standpoint, these are species and not just hibernaters, but a lot of other species that we’ve been studying since the early 1900s, 1950s. I mean, these are some of our earliest biological experiments and our earliest understandings of biology. We’re not necessarily done by studying humans. A lot of that was done by studying natural disease models, right? How did we figure out that genes cause cancer? So it’s a little bit of a tangent, but bear with me, it was not by studying human cancer, it was by studying Rous Sarcoma Virus and how that virus picked up bird genes and then turn them on. Right and other in other individuals. So but then kind of this almost the same year in 1976 that we figured out that genes cause cancer by studying chickens. 1974 we figured out how to genetically modified mice. And we sort of figured out that like, okay, maybe we don’t need to study natural biology anymore. And so I feel like we sort of lost a lot of those skills and figured out we had humans and we had model organisms and we were done. And I think now we’re kind of in this renaissance where people are realizing that actually there’s still a lot of natural biology that we can learn from. But it’s being powered now by this data revolution and the decrease in cost and sequencing and availability of omics data like RNA. Seq and then I will pitch that over to Linda because that’s really what she knows best.

Linda Goodman: Yeah, yes, absolutely. You know, Ashley’s right. And I think just to add on to that, that there was this issue in which there were a lot of field biologists out there working with these really fascinating hibernating animals. They knew a lot about what these animals could do, the extreme environments they were exposed to, that they could overcome, they could protect all of their tissues. And there was so there was a group of field biologists who knew all that information. And then on the other side, you have all of these geneticists who are studying the genomes of probably humans and mouse and rat. And they weren’t really talking to each other for a long time. And I’ve been in the genomics field for at least a decade, and not until very recently did I even hear about all these amazing adaptations that these hibernating mammals have. So I think some of it was just a big communication gap. And now that the genomics field is starting to become a little more aware that all these exciting adaptations are out there that we can learn from, I think that’s going to be huge. And yes, of course, it certainly does not hurt that there’s been a dramatic drop in sequencing costs. We can now sequence a reference genome for around $10,000. That was unheard of years ago. And so a lot of these species that people would previously consider untouchables because they were not model organisms with a pristine reference genome, we can now start to approach these and thoroughly study their biology and genomics in a way that was not possible several years ago.

Harry Glorikian: Yeah. I was thinking I was, you know, I was laughing when you said $10,000, because I remember when we did the genome at Applied Biosystems and it was not $10,000.

Ashley Zehnder: Yeah.

Harry Glorikian: Yeah. And it took I remember Celera, we had an entire floor of sequencers working 24/7 I mean, it was an amazing sight. And now we can do all that, you know, on a.

Ashley Zehnder: Benchtop. Benchtop. Exactly. On a benchtop.

Harry Glorikian: So. But, you know, it’s interesting, like in a way, studying animals to learn more about disease mechanisms seems like a no brainer. I mean, we share a, what, about 99% of our DNA with chimpanzees. And for those listening. Yes, we do. You know, I’m sure there’s people out there that, like, bristle when I say that. But what is it, 97.5% of our DNA with rats and mice. That’s why we use all these things for sort of safety and effectiveness of drugs meant for humans. But. Still, I’m not used to drug hunters starting out by looking at animals, you know? Why do you think it’s taken the drug industry, although I’m I say that very loosely, [so long] to wake up to that idea?

Ashley Zehnder: Yeah. I think it’s I think it’s again, this almost reversal of the paradigm that exists today, which is let’s take a human disease that we want to make a new drug for. Let’s take a mouse and let’s try to genetically manipulate that mouse to mimic as closely as possible what we see in the human disease. And those are always imperfect. I mean, I did a cancer biology PhD at Stanford, and there’s that trope of like, Oh, if I had a dollar for every time you occurred mouse in a human right, it would need to work anymore. That’s replicated across many fields, right? They’re not good models. And so we’re saying like obviously that doesn’t really work for discovery. It’s fine for preclinical and safety and you have to use those models. But for pure discovery, that’s not where you want to be, right? Instead, you want to take the approach of saying, where has nature created a path for you? Where is it already solved this problem? And I think there are companies like Varian Bio who are doing this in human populations. We’re saying, let’s look at humans that have unique physiologies and a unique disease adaptations. And of course then you have to find those niche pockets of human populations.

Ashley Zehnder: So that’s not a not a simple problem either. But the approach is very analogous. What we’re saying is we can use that rare disease discovery approach and just expand that scope of discovery. Look at highly conserved genes, look at how other species are using them to reverse how phosphorylation in the brain to repair their hearts after damage, to reverse insulin dependence. To heal, we’ll heal their tissues or regenerate stem cells. Let’s just see how nature did it right and just mimic that instead of trying to fix something that we artificially created. So it’s literally reversing that paradigm of how we think about animals and drug discovery. But you have to know how to do that. You have to know which models are correct. You have to know how to analyze 415 genomes together in an alignment which is really complicated. Linda knows how to do that, so you have to know how to do it correctly, although you could screw it up very badly. So there’s a lot of expertise that goes into these analyses and also again, the data availability, which wasn’t there nearly a decade ago. So.

Harry Glorikian: So I asked this question out of pure naivete, because I’m not sure that I could sort of draw a straight line. But, you know, which drugs were have been discovered through research on genetic mechanisms of disease in animals. Is there, are there?

Ashley Zehnder: You know, I think directly it’s a new field. Right. So I think, Linda, you and I have looked at some examples of looking at drugs for narcolepsy, looking at dog genetics and studies, looking at muscle disorders in certain species of cattle that have naturally beefed up muscles and translating those into therapies. I mean, there are examples of looking at animals for things like genotype, right, came from Gila monster venom, although that’s not strictly a genetic program. Right? So I think this idea of looking at natural animal models is a source of innovation. It’s just that, again, the data wasn’t really available until fairly recently, but we know the strategy works by what’s been done on things like PCSK9 inhibitors in humans, right? It’s a very similar approach to that. It’s just expanding that scope of discovery.

Harry Glorikian: So because you guys raised money and you guys are moving this forward, sort of and I don’t want you to tell me anything that’s confidential, but. So what was the pitch when you when you put that in front of everybody?

Ashley Zehnder: It was really that, look, drug discovery right now is really been hampered by a lack of innovation. And we’re really stuck in looking at these very kind of currently limited data sources, which is humans and again, these handful of really imperfect animal models. But we can take what we’ve learned from working with human genomics and really greatly expand the opportunities for a number of diseases that still don’t have good therapies. Right. We’ve had the human genome for really close to 20 years now. We spent a lot of money sequencing it. And still, if you go back and look at the FDA approvals in the last two years, which I did by hand a while ago, or more than three quarters of those are not new targets. They’re new drugs for a new indication or new drugs, same drugs before a new indication or they’re kind of meta pathway drugs or they’re drugs for which we still don’t know the mechanism. It’s some small molecule. It’s been around since fifties. And so like where is the innovation in the top ten diseases of people still have it changed? So like where I pulled these two headlines right not too long ago, one from 2003, which is like the era of the genomics revolution. Right? And then one from 2019, which was the genomics revolution question mark. Right. Like we’re still sort of waiting for it. And so what is that missing piece of data that’s really going to allow us to really leverage the power that’s in the human genome? And to do that, we have to put our own genes in an evolutionary context to understand what’s important. That’s been that third dimension of genomics that’s been missing. So it’s really not necessarily about any particular species that we work on, all of which are amazing. It’s really about using that data to shine a better light on what’s important in our own genome. And so that’s a lot of the pitches, like how are we going to use our own genome better and find better treatments?

Harry Glorikian: Yep. Understood. So. You have a third founder, Katie Grabek. Right. So. Tell me about yourselves. I mean, did the three of you get interested in comparative genomics and hibernation? How did you come together? How did you decide like, oh, hey, let’s do a startup and get this thing going in this area? So tell tell me the origin story.

Ashley Zehnder: Linda, do you want to kick off?

Linda Goodman: Sure. I think it all really started, Ashley and I initially started batting a few ideas around. We both had this understanding that that drug discovery today did not look outside of human mouse rat very much. And we both understood there was this wealth of animal data that’s just waiting to be used and no one was doing it and we couldn’t really figure out why. And we were having trouble figuring out exactly which animal we wanted to study and which diseases we wanted to study. And it just so happened that we lucked out. There was another woman in our lab at Stanford, Grabek, who had the perfect study system for what we were thinking about. She had these amazing hibernates our animals that have exquisite abilities in terms of disease, resistance and repair. And once she started talking about all the amazing phenotypes these animals have, we thought, wow, that would make a great study system to make the next human therapeutic. Yeah. And I think it’s interesting that both Katie and Linda have human genetics PhDs. Right. So I think both of them and Linda can expound on this. But from Katie perspective. Right, she she went in to do a human genetics Ph.D. trying to understand how genes can be used to improve human health and shouldn’t be rotating the lab of somebody who studied the 39 ground squirrel and said this physiology is way more extreme than anything we see in humans, but they’re doing it using the same genes.

Linda Goodman: What are those genes doing in these animals that we can adapt for human therapeutics? And so she brought that work with her to Stanford and was really one of the preeminent researchers studying the genetics and genomics of these species. My background is I’m of Marion, so my clinical training is in exotic species. So as a clinician, I treated birds, mammals, reptiles and saw that they all presented with different kinds of diseases or in some cases didn’t present with diseases like cancer that were super interesting. And then coming to a place like Stanford to do a PhD, it was working with a bunch of human researchers, human focused researchers. They’re all generally human researchers, but you know what I mean? It’s a little bit tricky with the nomenclature. Generally, I have my doubts about, you know, maybe there’s some chimpanzees doing research somewhere, people studying human diseases, right from a human lens who are completely ignorant of the fact that animals often also had these disease traits or in some cases were resistant to them. So there was this huge disconnect there of of biologists and veterinarians and physiologists who understood all these traits across different species and the people who knew the molecular mechanisms, even though a lot of those are shared.

Linda Goodman: And so one of the things that I found really interesting just from a cancer perspective was that a lot of our major oncogenes are highly conserved because these are core biological genes that if you screw them up, will give you cancer. But there’s an evolutionary pressure to maintain these genes. And so there’s a reason why they’re conservative, because they’re really important biologically, and that’s true across many other diseases as well. So from that perspective, I was really interested in this intersection of human and animal health. I always wanted to do more genomics myself and just never had had the training. Linda had always been interested in veterinary science, and so we kind of immediately started collaborating and saying, Look, look, there’s a huge opportunity in this, again, third space, third dimension of genomics that people are not looking at. What do we do trying to start a comparative genomics company? I’m using air quotes here for the podcast listeners is a little bit broad. Where do you start? And I think Katie really gave us that start in saying, here’s a model. We have a biobank of samples that are proprietary to fauna. We have an expert in this field. We have a model that’s good for so many different diseases. Let’s prove that the process works here and then we can expand into multiple disease areas.

Harry Glorikian: You know, you got to love, people I think, underestimate that magic that happens when the right people get together and the spark happens, right? I mean, I’ll take that. Any day. I mean, I love coming up with a plan and then, you know, working to the plan. But when it happens, when the right people in the room and they’re all get excited, those are those are the most incredible start ups, in my opinion. Yeah. So you’re starting off with targets in heart disease, stroke, Alzheimer’s, diabetes, very different areas, right? Cardiovascular, neurodegenerative and metabolic. So. Why start with those areas in particular?

Linda Goodman: So I think for us it was really again showing showing what we can translate from this model. So some of the phenotypes that we see, the traits that we see in the ground squirrel, which is predominantly one of the species we use for our work, is that they’re exquisitely resistant to ischemia, reperfusion injury. So the kind of injury that gets, if you have a heart attack and you go and get the heart attack on block, you get this rush of warm, oxygenated blood back into your heart that can actually be damaging. And that’s a lot of what causes damage after a heart attack, what these animals happen, they do this 25 times over the course of a 6 to 7 month hibernation cycle. And if you look at their hearts in the peak of one of these periods, there is an upregulation of collagen, which is cause of fibrosis. There’s an upregulation, there’s histologically, there’s a little bit of damage. It’s less than you would I would have, but there’s a little bit there. But if you get to the end of that whole cycle and look at their hearts, they look normal and they do it again next year. Right. So you and I could not survive 25 of these attacks over six or seven month period, right? Obviously not. So let’s pick the strongest phenotypes we have in these animals and let’s show that we can use information from that and come up with genes and compounds that are protective in our more standard models of these diseases.

Linda Goodman: And that’s what we did really with the first round of data that we had is we generated four genetic targets and two compounds that came out of the heart data that we had from hibernating and that we tested them in human cardiomyocytes in a dish and said if we take oxygen and glucose away from these cells, they get really unhappy and die and we could double survival of human heart cells in a dish. And then we said, okay, great, let’s actually move this into animals. And so we used AAV or some of these viral vectors to then knock down genes in vivo in hearts of rats. So we literally tied off a coronary artery and then let the blood come back in and saw that we could almost fully protect these hearts from damage by knocking down genes that we found in the hibernating data. So it was really closing that loop and saying, where are the strongest traits? Can we show that this works? And then it was really figuring out where are the really large areas of unmet need. And so in terms of metabolism, we end up connecting with Novo Nordisk, which is a publicly disclosed partnership. They are very focused on obesity. We have a model that increases this metabolism, 235 fold over an hour. Name another model that can do that, right?

Harry Glorikian: I need that. I need that. I need like, because…

Ashley Zehnder: We all need that!

Harry Glorikian: I could get rid of a few pounds right around here.

Linda Goodman: Exactly. So then it’s really just figuring out where are the unmet needs, who is really interested in these areas we’re looking at and do we have unique data that speaks to those models? And that’s really we just try to be guided by the biology and saying, where do we have unique data sets that can answer high unmet needs?

Harry Glorikian: Okay. Well, all I mean, all sounds super exciting if we can make the translation, you know, in the right way and find those targets. But. You guys have built up a significant biobank, right? I understand you have a huge database of genomic readout from various hibernating animals. Can you tell us a little more about the extent of that biobank? How did you collect the data and how unique is that database in the industry?

Ashley Zehnder: Yeah. Linda, do you want to talk a little bit about the data sources that we’re currently using at Fauna?

Linda Goodman: Yeah. So maybe, you might be the best person to talk about the Biobank and then I can talk about all the other data sources layering on top of that.

Ashley Zehnder: Yeah, I’ll talk a little about the BiobanK. So we have yeah, we have a number of different data sources. The Biobank is one of them and probably one of the main ones that we use. So Katie, during her PhD, built a really unique biobank of very precisely time tissue samples from 39 ground squirrels across the whole hibernation cycle. And the reason why that timing is so important is because the cycle is so dynamic. If you don’t have really precise sample timing, you end up with a big kind of smush of data that you can’t tease apart by having really precisely timed data points, you can separate these genes into clusters and know exactly kind of where you are in time. And that timing relates to the physiological injuries that we study. So we know what time points their hearts are protected because those physiological studies have been done. We’ve looked at those time points very specifically. So we have that biobank of samples that we in licensed as founding IP at Fauna CANI literally drove it across the country in a U-Haul because we didn’t trust anybody to move it. So that’s that’s now in our freezers and Emeryville with a cadre of backup batteries to protect it.

Ashley Zehnder: So that’s the founding data that we have. And that’s been really crucial because I look at other companies trying to use data for drug discovery, particularly in the early stage. A lot of it is kind of publicly available data or cell lines or kind of shared data sources. And part of what is unique about font, as we literally have truly novel data sources that we’re starting with that are wholly owned that we control and we know the quality of those. So that’s really the Biobank that we have is and it’s 22 different tissues. I mean, it’s brain, it’s kidney, it’s lung, it’s hard. It’s liver or skeletal muscle. Right? Pretty much every kind of tissue you would want in that founding biobank. But then on top of that, I think what we’ve done with the other data is super important. Yeah. And so we layer on top of that all sorts of publicly available data and also data we’ve been able to source, such as human data from the UK Biobank. But I really want to hit on the point of, of why the model species hibernate or data is so different. All of the other data that most people work with is trying to compare animals that are healthy to animals that are diseased, or people that are healthy to people who are have disease. What’s really unique about the model species that we’re working with is we’re trying to figure out why they have these superpowers in terms of disease, resistance and repair.

Ashley Zehnder: So it’s kind of the other end of the spectrum that we’re making this comparison between a normal, normal hibernate or during, say, the summer months and then a hibernate or that has gene expression patterns that mean that it’s resistant to many diseases and it can repair tissues when it gets damaged. So it’s actually quite different from the normal types of comparisons that others would make. But yes, and then we integrate publicly available data from sources like Open Targets Reactance. And one of the other data sets that we work with that’s that’s valuable is that we go back through literature that is relevant to the disease, indications that we’re going after. And we have a team of curators that mines these papers that where the biology is relevant and we integrate those transcriptomic studies generally into our database. And that that really helps with our comparisons. And I can kind of give you an example of the way that we would do this type of cross-species analysis compared to what other what others in the industry might do if they were just looking at humans or say, just looking at mouse and rat is that, you know, if you’re if you’re just looking at at a human study and you’re trying to say, look, for what genes do we think are involved in heart failure? You would look at, say, transcriptomic, differences between healthy human hearts and failing human hearts.

Ashley Zehnder: And then you would have some type of gene list where you’d see the genes that have differential regulation between those two groups. And it fa not we we look at that type of data and then we also look at hibernate or data and then we can compare that. And that’s really where the magic happens because we can look at hibernate hours when their hearts are protected during the winter months. So we have an example of these are genes that are involved in protection and then compare that to the summer months where they’re not protected. And then we can integrate both of those to analyses so we can say what’s really different about a human heart when it is failing to a hibernating heart when it is protected. And we do very fancy types of network analyses and then we layer on all of these data from external sources and the really exciting moments where we see these networks light up with the exact regulation patterns we are expecting that is relevant to our biology. Those are really fun. And I would say the other data source, Linda, that would be good to touch on is the genomic data, right? I think the comparative genomics data. So maybe give a little context on that. I think that really broadens the the views point of what we work with.

Linda Goodman: Yeah, absolutely. So that’s another data source that we work with. We have a collaboration with the Broad Institute that is one of the leaders of the Zoonomia Project that has in the neighborhood of 250 mammals in a in a big alignment. So we can do comparative genomics across all of these animals. And what we like to look for are comparing the genomes of animals that have a specific phenotype to others that don’t. So for example, what is different in the genomes of hibernaters compared to the mammals that cannot hibernate? And we typically do this with how fast or slow evolving genes are, right? So if a gene doesn’t accumulate very many mutations in hibernate hours, then it’s probably pretty important for hibernation because there’s a lot of purifying selection on that versus say, in other mammals that are not hibernaters, like like a human or a rat. It got a lot of mutations in it because it didn’t matter as much for those animals. So that’s another way of pinpointing the genes that are really important to hibernation. And we know, of course, that some of those might relate to the overall hibernation trait, but many of them are going to be disease relevant because they’ve had to evolve these genes in a way to protect their hearts and their other organs from these extreme environments they’re in during hibernation.

Harry Glorikian: So that, if I’m not mistaken, so did the Zoonomia Consortium, there was a big white paper about comparative genomics published in Nature.

Ashley Zehnder: Nature last year? Yep. Two years ago. Yeah. A little bit.

Harry Glorikian: Yes. Time seems to blur under COVID.

Ashley Zehnder: Yeah.

Harry Glorikian: How long have I been in this room? Wait. No.

Harry Glorikian: But. Can you guys I mean, because doing comparative genomics is not, you know. It’s not new necessarily, but can you guys summarize sort of the. Arguments or the principles of that paper, you know, quickly. And then, you know, my next question is going to be like, do you feel that Fauna Bio is part of a larger movement in science and drug discovery that sort of gaining momentum? So I’ll, I’ll I’ll let you guys riff on that launch.

Ashley Zehnder: Linda, you’re you’re the best one to do a perspective on that paper for sure.

Linda Goodman: Sure. Yeah. You know, I think this is really born out of the concept that in order to identify the most important genes in the human genome, we need to be looking at other animals and more precisely, other mammals to see their pattern of evolution. Because if you see a gene that looks nearly identical across all other mammals, that means that it’s really important. It means that it has been evolving for somewhere in the neighborhood of 100 million years, not accumulating mutations, which really translates to if you got damaging mutations in that gene, you were a dead mammal. Those have been selected out. And that’s really how you can tell these are the key genes that are important to to your physiology, the difference between life and death. And you can’t understand those things as well by just looking within humans and human populations. We’re all too similar to each other. But it’s really when you get to these long time scales that the statistics work out where you can see, okay, this has been this mutation has not happened in 100 million years. We don’t see it in anybody’s genome. So that is obviously very important. And that’s just this other way of looking at our own human genome that helps highlight the genes that are going to be important to diseases. And I think, you know, another side to this paper related to conservation and the fact that a lot of these animals with really exciting genomes, the ones that are exciting to people like us, are those that have these really long branch lengths where they’re they’re kind of an ancient lineage. And that’s really where the gold is, because that helps us even more understand how quickly or slowly some of these genes are evolving, and it related to trying to conserve some of these species as well.

[musical interlude]

Harry Glorikian: Let’s pause the conversation for a minute to talk about one small but important thing you can do, to help keep the podcast going. And that’s leave a rating and a review for the show on Apple Podcasts.

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And one more thing. If you like the interviews we do here on the show I know you’ll like my new book, The Future YouHow Artificial Intelligence Can Help You Get Healthier, Stress Less, and Live Longer.

It’s a friendly and accessible tour of all the ways today’s information technologies are helping us diagnose diseases faster, treat them more precisely, and create personalized diet and exercise programs to prevent them in the first place.

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And now, back to the show.

[musical interlude]

Harry Glorikian: I should say congratulations because you guys did raise a $9 million seed round last fall from a group of venture funds, some in life sciences, some more general. Right. What does that funding do? What is it? What does that unlock next?

Ashley Zehnder: You. I will answer that question. I do want to jump back to your other question that was kind of is this part of a larger movement and comparative genomics? Right. I think that’s an important question. I think you sort of hit the nail on the head there. We were invited to a symposium in August of 2019 called Perspective and Comparative Genomics that was held at NHGRI in Bethesda. And I think there’s a recognition and actually some of our grant funding is also through NHGRI. And I think there’s a recognition from the folks who sequenced the human genome, that they don’t have all those answers. And so it’s an interesting time where we realize that there is this kind of other data out there that can help us really understand that better. And it does feel a little bit like a rising tide. And so that’s that’s something that I think is important to recognize. But in terms of the seed round, really, that was meant to expand the platform and the pipeline that we built with our initial funding back from Laura Deming and Age One and True Ventures, who led around for us in early 2019. It’s really saying like that initial $3 million or so is really to say like, does this work or is this crazy, right? Can we it’s just a crazy idea.

Ashley Zehnder: And that’s what we really started to generate those first few animal studies that said, yes, actually we can find genes and compounds from this data that meaningfully affect not only human cells, but animal models of human disease. And now we’re really expanding into new disease areas. We’re looking at areas like fibrosis. We’re looking at areas like pulmonary disease. We’ve got some really interesting data coming out of animal models of pulmonary hypertension with a compound that we found on our platform. We’ve got the collaboration with Novo Nordisk, which of the five genes that they tested in animals? We have one that has a significant obesity phenotype. So I mean, 20% hit rate on a novel target discovery in vivo is not bad, right? So we’ve gotten to the point now where repeatedly over multiple disease areas, we’ve seen that between 20 and 30% of our either compounds or genes are hits, which shows us that this is not only kind of a we got lucky in cardiac disease, but actually this is a process for enriching for important drug targets. And now it’s a matter of really expanding the pipeline. We brought on a really experienced head of Therapeutics Discovery, Brian Burke, who spent 20 years at NIBR running very early discovery programs and then seeing programs go into the clinic.

Ashley Zehnder: He worked on drugs like Entresto and then worked on a couple of startups after that. So he’s kind of gotten both big pharma and startup experience, and his job at Fauna is to really look at the menu of things that we’re presenting him from an early research and discovery phase and picking the winners and really figuring out how to take them forward and also killing the programs that are less exciting to him for a number of technical or practical reasons. So that’s been really, really helpful to have someone come in truly from the outside and take a look at the science at Fauna and say this is as good or better as anything that I’ve worked on before. I’m really excited to work on this, and that’s been kind of a nice external perspective on on the science and the pipeline at Fauna. So that’s really what the $9 million is for. It’s really expanding a lot of the computational expertise and and progress and Linda can talk a little bit about that, but also just expanding into new disease areas as well.

Harry Glorikian: Understood. So, you know, on this show, like, I talk a lot about, you know, technology, data, and how it’s all affecting health care, which this all fits into. But one of the things we talk about a lot is how crappy, terrible, I should use, you know, terrible, right, electronic health records are in the lack of interoperability between them. And Ashley, you actually wrote a paper.

Ashley Zehnder: I did, yeah, veterinary medical records are just as bad, actually, veterinary medical records are probably a little bit worse, if it’s possible.

Harry Glorikian: And to be quite honest, I’m sorry, I just hadn’t thought about Fifi or Rover and their…

Ashley Zehnder: Their medical records.

Harry Glorikian: EHR. Is like is the problem bigger, even, when it comes to functional genomics? I’m trying to think of like obtaining and storing and analyzing ‘omics of different species. I mean, who’s working on this? Is that part of the Zoonomia consortium? Right. I’m just trying to think it through, like, how do you get all this information and then look at it across all these different species. And at some point, you know, look looking at it against humans also.

Ashley Zehnder: Yeah. I’ll let Linda talk about the genomics side. I’ll comment on sort of some of the validation, some of the externally curated data that Linda talked about. I think this is actually becoming a really important data set. It was a little bit of a slow burn to figure out how to get it and to curate it. But there are a lot of studies now coming out and not just your traditional model organisms, but naked mole rats and long lived rock fishes and primate studies and bats and all kinds of people looking at genomics and RNA seek metabolomics and proteomics across these species that have interesting phenotypes. The problem is, every one of those researchers really heads down on their own species of interest, right? Nobody’s saying, oh, well, actually, we’re seeing the same genetic signature in these bats that we’re seeing in the naked mole rats that we’re seeing in some of these long lived fish. Right. But that data is not in a very friendly format. So we were like originally we were like, okay, we’re going to write some scripts, we’re going to try to pull some of the stuff out of supplemental tables. It’s going to be awesome. No, no, no. We have very highly trained curators who work on this data and bring it in. And we have a very standard pipeline and a process and a way to normalize the data across different studies and standard ontologies and ways to clean up this data in a way that it can be integrated with the genomics coming out of the platform. And that is a tedious and painful and ongoing effort to bring in all this data.

Ashley Zehnder: Now, we have data from well over 330 individual studies, over 30 species. I think Linda, you told me it was like more than 800,000 gene entries at this point that’s curated and that’s kind of growing month over month. So now that’s becoming part of our defensible moat, is that we’ve taken the last two or three years, again, slow burn, pulling all this data together in a way that it can be reused. And now we can turn a paper around and put it on a platform in a week or two. So we’re kind of always scanning for these studies. But yeah, it’s, it’s, it’s out there, but it’s not always in a usable format without a lot of pain and effort. And so we’ve kind of put that pain and effort into getting that data in a place that we can use it. And then, of course, the comparative genomics is like a whole ‘nother level of complexity.

Linda Goodman: Yeah, so I can talk a little bit about how we do that within the comparative genomics community and how we’ve done that for Zoonomia. Because I referenced before that we like to do these sorts of studies to examine the genomes of hibernate ers and non hibernate and figure out what’s different. And you’d think it would be a trivial question who is a hybrid nature amongst mammals? But it’s actually not. And so along with our collaborators Alison Hindle and Cornelia Santer, as part of the Genome Project, Fauna tried to go through and categorize every every genome that was in Zoonomia. So we’re talking about around 250 mammals for is it a hibernater, or is it not? And you’d be surprised how often it was digging through literature from the 1970s and someone would say, this animal is not often seen during the winter. So we think it hibernates and it’s not always the most satisfying. And so it is an extremely tedious effort, but well worthwhile to go through and say this animal, I’m very sure, hibernates. This one, I’m very sure does not. And then there’s this third category of animals that were unsure about we’re going to remove those. And it’s tedious, but you have to do that part, right? Because if you do the analysis with bad data, you’re never going to find the genes that you want. And Linda, I remember you telling me when you were going through this very painful process, I think your threshold for being a perpetrator, quote unquote, was that you could drop your metabolism like 50%. Correct me if I’m wrong, and humans could go down to like 40 like in certain instances, like humans are almost there. You know, it’s it’s hard to know when there is only one paper about it, but certainly there are some really deep meditative states and humans and low oxygen environments where, you know, we’re getting kind of close to the area where we might say that that’s a hibernated, but certainly not the duration that you get out of hibernation. But it’s it’s it surprised me to see how close how much how much metabolic flexibility there really is when you start to look at it. Yeah.

Harry Glorikian: Yeah. We’ve got to go talk to the monks.

Linda Goodman: Absolutely. Absolutely. You know, we have that in mind. It sounds like an interesting travel experience. Yeah.

Harry Glorikian: So I want to jump back for a second because. You guys don’t necessarily have from what I have pieced together, the normal sort of like startup story. Right. First of all, you’re an all female founding team, right? Highly unusual, right? Not something I see every day. You guys started at an accelerator program in San Francisco called Age One.

Ashley Zehnder: Age One.

Harry Glorikian: And then you moved to QB3 and the East Bay Innovation Center.

Ashley Zehnder: Yep.

Harry Glorikian: And then I think they helped you with some paid interns.

Ashley Zehnder: Well, we got some from Berkeley. Yep, we did.

Harry Glorikian: Yeah. And then you went through a SBIR grant.

Ashley Zehnder: A couple of them.

Harry Glorikian: From the Small Business Administration. And then a small business technology transfer grant from the Human Genome Research Initiative at NIH. Right.

Ashley Zehnder: Yep.

Harry Glorikian: I’m hopeful, hopefully my notes are all correct. Talk a little bit about the on ramp or infrastructure today for sort of seed stage startups like you. I mean, what were the most important resources?

Ashley Zehnder: This is such an important conversation. I’m really glad you’re asking this question. We had a call with a reporter from Business Insider yesterday who was talking to all three of us about this early founder ecosystems in biotech and sort of East Coast versus West Coast ways of starting biotechnology companies. Right. And that is a whole do a whole podcast on that, let me tell you. But I will say that there are a lot of resources for, let’s call them founder led bio. Right. In the West Coast, which is kind of the buzzword these days, but people really supporting the scientists who originate the concepts and training them to be founders as opposed to assuming that you need to bring in an experienced CEO to run a company at this stage. Right. So I think we were very fortunate to meet Laura Deming at Stanford, who is one of the founding VCs. And longevity before that was a buzz word, right? She was one of the first longevity funds, literally Longevity Fund, and is really been a champion of founders, starting companies and really training founders to start companies who are deep science founders. So we started in age one. It was the first batch of age one. We’re still very close to that cohort of companies doing interesting things from machine learning and image analysis through pure therapeutics development. And then Laura really helped us, her, her. We asked her later, like, why did you end up investing in us? She said, Well, the science was amazing.

Ashley Zehnder: This is totally a field with so much promise. I just needed to teach you guys how to pitch. The science was there, right? So she helped me just how to pitch and how to use less science words in our pitches, which we’re still working on to some extent. But then it was this balanced approach of taking in some venture money to really support the growth of the company, but balance with some of this non-dilutive funding for specific projects where it made sense and some of that was some of that in the early stage is validation, right? Having having funding through groups like NHGRI, having an early partnership with a company like Novo Nordisk, which provided also some non-dilutive funding for the company, really validated all of the science that we were doing because we were first time founders, because we’re a little bit outside of the normal profile. For me, I don’t feel weird being a female founder only because 80% of veterinarians are female. Like, I’m used to being in a room with all women. You go to a bio conference, it’s not the same thing, right? So for us, we’re just we are who we are. Right. But it’s helpful, I think, to get some of that external validation and then really be able to use that to to start to build on programs and show progress.

Ashley Zehnder: And then it becomes more about the data and the progress and what you can do with it. So that’s a lot of how we started the company. There’s I said there’s a lot of support in the West Coast for this kind of thing. There’s great programs like Berkeley Foreman Fund Talks, which I worked, which I was in as well, just about logistics around starting companies. There’s a lot of good startup accelerators. I’ve got a really amazing all of us, how amazing a network of founders who we can reach out to on different. I got four or five different Slack channels of founders that I could reach out to for all kinds of advice. And usually it’s always good to have a company that’s one or two stages ahead of you, like talking to folks who IPO’d or something last year is is not as helpful as folks who recently raised a series B, right. And figuring out what those milestones look like and then particularly those that have taken mostly money from tech investors like we have all the lifeforce capital who led our last round is also has funded some very good therapeutics companies, Sonoma Therapeutics and Second Genome and other therapeutics companies as well. So I think it’s it’s helpful to see how people balance the needs of the companies at different stages in what you need.

Harry Glorikian: But so do you guys think that you could have started Fauna ten years ago? I mean, did the support systems exist for starting a company like this?

Ashley Zehnder: Well, no, for two reasons. We couldn’t have started Fauna ten years ago. One is the data just simply wasn’t in a place that the company was a tractable strategy. Everything was still too expensive and we had really shitty genomes for a few species at that point. And B, I think there really wasn’t the kind of groundswell of support for deeply scientific technical founders to start their own companies and train them to be the kind of leaders they need to be to run those companies for a longer term. So I think it’s a confluence of those things and being in an environment like Stanford that really encourages people to to try startups, it’s not a crazy idea. Like people don’t look at you like you’re your heads backwards. If you start to start a company at Stanford, it’s like, okay, cool. Like, when are you launching? You know.

Harry Glorikian: I think it’s the opposite.

Ashley Zehnder: Yeah, exactly. Exactly. Like, why aren’t you have a company yet? Whereas you know, a lot, many, many, many, many other places like that is seen as a very strange thing to do. So I think the environment plays a huge role. Yeah, for sure.

Harry Glorikian: Yeah. I think between East Coast and West Coast too, there’s.

Ashley Zehnder: That’s a whole, we should have a whole ‘nother podcast on that.

Harry Glorikian: Yeah. Yeah, exactly. Well, I live here and I was I was born and raised on the West and I remember there and I came here and I was like, Oh, this is where you are not in Kansas anymore. Like, this place is different. So, I mean, I’m hoping that the East Coast is actually embracing risk a little bit more and sort of stepping out on the edge. But it’s really slow. They don’t call it New England for nothing. So. But, you know, it was great having you both on the show. I this was great. I we covered a lot of ground. I’m sure people’s heads are spinning, thinking about, you know, you know, different animal species and how that’s going to play into this. And I mean. It really does sound like I know we have to do the hard work, but there’s a lot of computational effort that has to go on here to sort of. Make sense of this and bring it all together and align it so that you can be looking at it properly and make the right decisions going forward.

Ashley Zehnder: Yep. Millions of data points coming together to find drug targets for sure.

Harry Glorikian: So thanks for being on the show. And you know, I wish you guys incredible luck.

Ashley Zehnder: Thanks, Harry, so much. This was fun.

Linda Goodman: Thanks for having us.

Harry Glorikian: Thanks.

Harry Glorikian: That’s it for this week’s episode.

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