Bankless - DeSci: How Blockchains are Powering Science 3.0 | Zuzalu #7

Starting point is 00:00:04 Welcome to Bankless, where we explore the frontier of internet money and internet finance. And today, on this episode of our Zuzalu series, we are exploring some new frontiers. New frontiers and new technologies, all of which are poised to completely revolutionize the world and change everything about the operating system that society is currently running on. Bankless Nation, today we are exploring the frontier of DECI or decentralized science. What is DECI? It's a really good question because I legitimately had no idea going into Zuzalo. but it became clear that D-Sai is a great connector of many of the technologies presented here at Zuzalo.

Starting point is 00:00:39 D-Sai is how synthetic biology and longevity have to do with Ethereum. D-Sai is what is putting Ethereum at the center of these things. The fundamental argument for D-Sai is that the old ways of doing science is bad. And for the same reasons why the old way of doing money and doing finance is bad, D-Sai looks at the incumbent system of producing science and sees friction and corruption, and corruption and antiquation and toxic tradition. D-Sai wants to use blockchain technology to improve the systems and institutions of science. The mechanisms of how science can use a blockchain is a very big conversation, and the answers

Starting point is 00:01:16 are more than a few. But the conversation that you're about to hear with Boris and Mikey will download you on the D-Sai landscape here. But this isn't just about improving the ways that we do science. This isn't just about, hey, we found a new way to do science better and faster. D-Sy presents a zero-year-old. to one step function changed in the form factor of scientific progress itself. You know how Uniswap and AVE and ERC20 tokens are just open APIs to financial tools.

Starting point is 00:01:43 D-Sai wants to do very similar things for scientific data. What would happen if we made our scientific data as open and as free as a contract call? What if scientific data was as modular and open as the internet itself? But blockchain tech doesn't just provide new solutions for scientific data specifically. DISA is also marked by an emergence of DOWs, all following a decently similar form factor of capital allocation, financing clinical trials in hopes of investing in a breakout new treatment, servicing the long tail of unservice patients, which also sounds a lot like banking the unbanked, and a bunch of other similar puzzle pieces that are all coming together in these very variety

Starting point is 00:02:21 dows that are all trying to go after certain specific use cases in the world of science. So this first episode in this two interview series is with Boris Diyakov and Mikey Fisher, both who are pioneers in the D-Sai space and helped me have one of the most enjoyable and easy conversations that I had at Zuzalu. And after listening to this conversation, you'll understand exactly what D-Sai is getting at and whether or not you want to proceed into the second conversation with Al-Octai, whose project ViBio illustrates a specific example of the overall archetype of D-Sy DAOs that are art there, trying to use blockchain tech to coordinate and excel. scientific progress. So, Bankless Station, are you ready to explore the frontier of scientific progress? By the way, at Zuzalu, all of the traditional scientific researchers that were there, all realized that the existence of D-Sai implies the existence of TradSai, which was a meme that stuck pretty damn fast. So, all right, let's go and learn about D-Sai with Boris and Mikey, followed by D-Sai D-Dows, with Aalok. But first, a moment to talk about some of these fantastic sponsors that make the show

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Starting point is 00:06:41 How's it going? And then further down to my right, we got Boris. What's that, Boris? Hello, David. Pleasure to be here. So I've heard the name D. D. Sci a number of times. It had some exposure at East Denver. I've seen it on Twitter, but I haven't really figured it out. But D-Sai seems to be the thing that really is pinning a lot of these various conversations at Zuzaloo together. That's why the synthetic biology people are talking to the crypto people, right? That's why the longevity people are talking to the crypto people. That's kind of my basal level understanding. But beyond that, I don't know what D-Sai really is or how to explain this movement to the Bankless Nation. So I'm hoping you guys can help us guide

Starting point is 00:07:19 all of the listeners down that rabbit hole. You guys want to do that? Very excited too. Yeah, happy to. But first, a little bit more about you guys. Mikey, tell us a little bit about yourself and your background. Yeah, so I just finished my PhD. I was at Stanford. I was studying computer science and natural language processing. And after I finished that, I wrote a book on regulating AI. And then I got very interested in, I saw the PhD. I thought that this could be done in a different way. So I got into crypto. I learned about DCI and I thought one of the key parts around

Starting point is 00:07:51 DCI was like data and how we could fix some of the problems that exist in traditional academia around how data is collected. So I started a company called DBDAO which basically like fractionalizes large data sets and then gives people's and gives people an incentive to contribute data. All right. Boris, tell us about yourself. So I'm a scientist by training. I'm actually a current PhD student, PhD candidate at the University of Toronto and the Ludenfeld-Tanbaum Research Institute. So I'm coming from a different field. My PhD is in molecular genetics, and basically my research is around figuring out which proteins are found within these structures in the cell called nuclear bodies and the nucleus. So I spent most of the past decade pursuing this academic career,

Starting point is 00:08:35 really just trying to build a career as a scientist and eventually have my own lab and continue to unlock new knowledge about how cells work and how they're organized. And during COVID, I kind of took a step back and started exploring other pathways. And after this sort of long journey exploring business and finance, I eventually ended up getting interested in Web3 and thinking about how we could solve some problems in science that essentially drove me away from the career that I'd been pursuing for so long. And we'll talk about this after, I'm sure, because there's a lot of issues in how science has done, both in academia and industry.

Starting point is 00:09:09 But basically I was thinking about how we can maybe fix some of these problems and realized there were other people coming from my background who were excited about these same problems and we're trying to tackle them using some really interesting technologies like Dow's and Crypto. So that was about a year and a half ago and it's been a wild ride ever since. I mean, I think Boris and I are both interested in science. Like we are both scientists and we both love science. And we both went through the traditional science means of doing science, which is a university. we both saw that there's issues or ways that could be done better. And that's what excited me about D.S.I is like, oh, you can still do science, but you can do it in maybe a better way. And that's actually just resonates a lot with me because when I was getting into crypto,

Starting point is 00:09:53 I was thinking about going down a doctorate of physical therapy route with the intention of also applying that to mental health and nutrition. And then I found Ethereum and saw one path, which was slow and friction filled and costly. and the other path, which was new and innovative and fast, where you don't ask for permission. And I kind of think that's why this D-Sy world exists at large is because the old way, the trad-sci, is old and friction-filled and slow. And I think maybe the people that have hopped onto the D-Sai movement

Starting point is 00:10:27 have been able to identify in crypto is that we move really, really fast. And there seems to be an appetite in the scientific community to move faster than the U.S.I. incumbent ways of doing things and that's where this demand for a new form factor of science comes from that's kind of my sentiment is that is that my over the mark here yeah one of the big things is just accelerating science and tradsai um tradsai has that been is that it is now it is you start saying yeah the sin bio people were like oh are we tradside we're like yeah you're

Starting point is 00:10:57 tradsai but it could literally take two to three years to publish a paper for some things by the time you like get the funding to the time you do the play around with the research to publish the paper to get reviews, it could take quite a bit of time. And it doesn't have the quick turnaround cycles like GitHub or like a poll request does. This really does vary field by field. I mean, everything is slow in the life sciences, in biology. Like I work with, I'm a wet lab biologist. And when I say wet lab, I mean, I actually work with pipettes and cells and proteins and liquids and test tubes.

Starting point is 00:11:28 And everything's slow. Cells need to grow. You know, all these processes are manual and really drawn out. And that stuff can definitely speed up and be automated. really a D-SI problem. I mean, I think in some ways the slowness of science can be a feature and not a bug, but not in every sense. There's a lot of inefficiencies that can be sped up, and I think a lot of this appetite and excitement for D-SI is one scientist's discovering that there's new technology that enables us to coordinate more effectively, make things more efficient,

Starting point is 00:11:55 do things in a trustless way, of course, and just exploring the possibilities around that. And then I think on the other hand, people who are coming from, like, crypto, are excited to have more use cases for blockchain technology. Yeah. Yeah. One thing you were mentioning is like the permissionlessness of it, of crypto. And I think that's one of the things that's become an issue in traditional science is it is a very permissioned system. You have to get grants from a specific agency.

Starting point is 00:12:27 You have to get accepted into a university by fulfilling some certain things. You have to then appease the advisor, appease a journal. It is very hierarchical and gatekeeping. And approval by the FDA, which is a big one, right? Whereas what's really neat about this D-Sy movement is that it's permissionless. Anybody can contribute to a research project. If you have the right data, if you have the right background, it's not based on a degree or anything. It's based on a meritocracy, and it's based on the data that's provided.

Starting point is 00:13:00 And it's a much different way of thinking about how to do science. If I can add to that, I mean, something we should maybe start with is that the D-Sai movement, I guess we can call it a movement, it really builds on the earlier open science movement, which has been around for decades, which has tried to solve a lot of these same problems we're talking about. I mean, you know, the fact that if you want to read an article, like scientific knowledge that should be freely shared among everyone, you need to get through a paywall. And, you know, hopefully we'll have a chance to talk about public, like the whole publishing process. problem and reproducibility crisis in science, but there's a lot of barriers and it really just doesn't make sense in a lot of ways. So there has been this movement of people pushing for making everything open access, open source. And I think there's a lot of inspiration that science can and must take from like the open source software movement and those communities because it's just a better way

Starting point is 00:13:54 of doing things. It's how things should be. But we as a community are kind of trapped in these longstanding, you know, really like strong institutions of science. which have done a lot of good things, but have also kind of missed the mark in a lot of ways. Yeah, and I mean, building off what Boris says, like, D-Sai is very much has its roots in open science. But one of the things that's really interesting is, like, open science was probably happened like 10 years ago, I don't know, around 20, 30. Yeah, so it's been around for a while, but it's caught in some waves, but it hasn't really taken over as much as people would have liked, I guess. Maybe the crypto corollet is like the Occupy Wall Street movement, which was a good flag, a banner to rally around that actually didn't really end up moving the needle until Bitcoin came around, right? Yeah. Love that analogy. Yeah. It's like, oh yeah. So one of the things that's interesting about the open science is like what is what is what does D.Cai offer that builds on open science? And it's it's like incentivization mechanisms. So now we have the ability to track research from test,

Starting point is 00:15:04 to final product. And so if final product is good, you can incentivize the people that contributed because you have this immutable ledger that anyone can contribute to and you can track who did what part. And so this is very cool because now we have a way of tracking.

Starting point is 00:15:19 If someone does good basic science, if someone does good research, they can now be partial owner of it, the benefit. Whereas in open science, you had your data, you'd throw it over the wall to this journal, to a data set, and you'd lose sort of ownership of that.

Starting point is 00:15:33 And so this is like why blockchain is actually very important for this D-Sy movement. Just for like attribution and creditness and being able to see the source of things and being able to map those things and just having a specific destination of who did what opens up the world of collaboration and other mechanisms? 100%. I mean like the whole idea of like data provenance is a big topic I think in crypto and like data science and all that. But the same thing. It's like your contributions in science essentially are only recognized through this chain of citations, which is like text in a PDF. These things aren't hyperlinked. You know, there are systems now where you can kind of have a record of your academic work.

Starting point is 00:16:14 It's called Orchid. It's very much a web two kind of, you know, system. It's a step in the right direction for sure. But, I mean, we have technology to dramatically improve on these systems and then be able to look back and say, wow, somebody's getting a Nobel Prize for this, but here's all the hundreds of people who can treat. to this. Maybe we should reward them too. Maybe they get an air drop, you know? Like, and the funny thing about it is like an academic paper, it lists all the people on the top of it, but it doesn't say who did what. So you could have a research paper with hundreds of people on it. And the last name is the

Starting point is 00:16:45 advisor and the first name is the lead author. And then everywhere in between is very complicated on who did what. There might be little notes like these people did experiments, but like. But with watching, you know exactly who did every single part and like who contributed good data, who contributed bad data. And with that, Why that's important is not for, like, it's for a reputation, but also you can reward people. Like, oh, I really enjoyed this part of the paper. I'm going to reward this specific person. Right. And I'm assuming there's more ways to make this really, really codified rather than just, like, putting Ethereum addresses next to people's names.

Starting point is 00:17:16 There's a, there's like the idea of like a identity. Yeah, right. There's like mapping at the value graph of all of these things. One thing that, the reason why D-Tis caught my attention lately is that it seems to fit the same mold of other movements that we've seen in crypto, which is there's this spark that just happens because someone figured out a basic pattern, and then that started to get copied a bunch.

Starting point is 00:17:42 And I think, maybe correct me if I'm wrong, but I think the story starts at Vida Dow, and that was like the first D-Sai Dow that created this archetype for other science people to be like, oh, there's something there. And then it spawned more and more and more D-Side-Dows, and now there's like a slow Cambrian, maybe not slow, Cambrian explosion of D-Side-Dow's being formed. And it's like, I think that's the kind of the top of the rabbit

Starting point is 00:18:08 hole of this whole thing. Is that right? I think for a lot of people it is. I mean, longevity is huge in crypto and in tech in general. Vita Dow is doing amazing work, big fan of what they've been doing, also the folks of Molecule who've kind of built that whole ecosystem around Vita-Dal. They're doing a lot for the space for sure and really trying to template that sort of Bio-Dow model with their whole incubator accelerator program. That's I think one type of D-Sai project, right? This is like, not going to call it an

Starting point is 00:18:37 investment DAO, but it's like a it's a DAO that is essentially trying to fund and support specific areas of research that will hopefully have some sort of translational application. Maybe will lead to a drug that will go into clinical trials one day. Or new cures for something, your new products.

Starting point is 00:18:54 And I mean, there's something that I've been thinking about a lot lately, which is that there's like science can mean a lot of different things. There's so many different fields of science, of course, and they all do things a little bit differently. I mean, we're all kind of surrounded by, or unified by the same principle that we're trying to understand

Starting point is 00:19:08 how the world works and gather data and analyze it and use the scientific method to create better models of the world around us. But science can mean basic research, which is just like fundamental basic research, like math, you know, that may not have some specific application like a drug or a cure for a disease. And then there's things down the line, like biomedical research that is trying to find targets for drugs to hit to cure types of cancers. And they have different types of problems, like in terms of how they're funded or how you incentivize

Starting point is 00:19:38 them. But I think that brings me to the topic of incentives, which I think is the other superpower that crypto brings to the problems that science has. So the thing I was talking about where like these Vida-DOWs, there's one I interviewed was a synthetic biology Dow. There's many of these things. is that D.Sai? What is D.S. Like, how do you put a border around this thing? What actually is it? What is DSI?

Starting point is 00:20:06 I guess that's what we should answer, right? It's like a movement. It's like, what is DFI? It's in the same way. It's people that are looking to do, or what is a network state, it's people that are looking to exit the existing system to some extent. And use blockchain as an important part,

Starting point is 00:20:24 or DIDs or collaboration. or putting data on chain. But I think it's very dependent on the actual project. It's an idea. I mean, I think we can look at the current DSI landscape, the projects that people are working on, what's happening in the space, who's giving talks at various great DCI conferences

Starting point is 00:20:42 and meetups that have been happening over the past year or so. And I kind of have like three buckets I like to put it into. One is funding. So funding is a major problem in science. We need more money for science. How do we get more money for science? How do we create better, more liquid markets? for biotech intellectual property, for example.

Starting point is 00:21:01 That brings up topics like IPNFTs, stuff like that. So that's one thing, funding. Second, of course, is something we talked about, which is publishing. You know, the current publishing industry, academic publishing industry, is kind of crazy. And people who aren't in academia aren't aware of how nuts this is. I mean, academic publishing houses have, I think, the highest margins of any industry, like, way higher than anything. It's really absurd because essentially people pay to publish in these journals, and then peer review is done for free by scientists in those fields,

Starting point is 00:21:36 and then they charge universities, individuals, whoever wants to read those papers, huge fees to access those papers. It's like a triple payer model is what some people call it. So that's the second publishing. And the third is, well, not just third, but I think reputation systems, attribution, data provenance, all that, like all the other things that. Yeah, and much more. I would also add reproducibility.

Starting point is 00:21:59 So, like, one of the big problems in science is papers are too complex to be replicable, or the data sets are not open, or basically a lot of stuff can't be reproduced. And D.Sai has an emphasis on reproducibility through many eyes on data, through putting the data on chain so that it's immutable. so that it has provenance and tracking and reputation associated with each of it because I think we're going to go back in 10 years and see that

Starting point is 00:22:33 so much of the data, so much of scientific research is just hard to reproduce so you can't build on it. Whereas like a GitHub project you can just download it, run it and see that you can build on it. And that's an important part of science as being able to reproduce and build it. Yeah, I think another one more bit to add

Starting point is 00:22:50 would be the actual execution of science. I mean, there are projects like Labdow that are trying to build new tools and infrastructure for scientists to actually do scientific work in a more reproducible way. So, yeah, D-Sai is a lot of things. Right, okay, so there is no boundary. There's no border on what is and is not D-SI. It's not just this growth of D-S who are doing various things across the science space. It's just there's a lot more tools in the crypto world that are being leveraged for the pursuit of science.

Starting point is 00:23:23 and there's no really better way to put a boundary on it other than that. Yeah, I like to kind of summarize it as using blockchain technology to improve the systems and institutions of science and create new incentives for science. Something I've been asking myself is how do we create a world where everybody wants to be a scientist and has the opportunity to be a scientist if they want to be a scientist. I don't think everyone should be a scientist or wants to be,

Starting point is 00:23:48 but how do we increase that number? Yeah, I mean, I think in the same way, defy brought about many different types of traders D-Sai has the ability to bring out many different types of scientists and many different people who can contribute to science whether that be through collecting specimens around the world of nature or of like testing out different nutrition or stuff like that

Starting point is 00:24:16 and it has the ability to open up science a lot more So that very much just fits into the mold of crypto, right? Democratizing access, lowering the barriers of entry, making things more permissionless, making things more kind of disrupting the incumbents no matter what. Always kind of tablestakes for the things that crypto touches. Maybe you guys can use your imaginations, put on your imagination cap, and just like fast forward 10 years. What's the bulk case of D.Ci?

Starting point is 00:24:44 What's the bulk case of science? And because crypto enabled it and D. D.S.I have fulfilled all of his promises. What does this new world look like? Yeah. It's like GitHub for science. So it's as easy to do and reproduce science and get credit for science as it is to use a GitHub package today. I love that. I mean, that's a good question. Bull case for D.Sai. I mean, in 10 years, I'd be really happy if most of the new research and most of the new data that is being generated is going on to some sort of decentralized storage system and able to be

Starting point is 00:25:25 accessed permissionlessly with a record of who did the work, who built on the work, what kind of computation was done on it, and we kind of disrupt this whole model of the PDF as the token of knowledge, you know, progression. But it's so much more than that. I think I would really, I'd really expect to see new funding models to appear, new ways of rewarding people for their scientific contributions. Again, science takes time, but at least having a framework in place and seeing early results of that would be what I'd love to see. Yeah. While talking to some of these, the DAWS, it was a ViBio, one of the DAO's one of the interviews I have in this track. It was interesting to see that there's an explicit investment

Starting point is 00:26:11 thesis, an investment case for some of these things where, like, you put in capital, this Dow goes and funds projects. It funds new medicines, new research for new medicines. And then the Dow owns that IP or that Providence, I don't know what to call it, but that whole concept. And then that Dow grows in capital because it produces one medicine that is demanded by the market. So the fact that there's like financial incentives to grow this thing makes me pretty bullish, just on this idea of being able to converge science in financial incentives. in a ways that has been full of friction, right?

Starting point is 00:26:48 We already know that the bankless nation knows the frictions of the traditional financial system. They are probably at least now starting to wake up at the very least to the frictions of the scientific community. And I think the whole idea of defy and desi is that we get to take friction away from both and turn on this propeller of innovation. Maybe that's another way to articulate this whole thing. Yeah. I mean, I think a lot of so. There shouldn't be barriers to contributing to scientific knowledge.

Starting point is 00:27:18 Like anything you do throughout the course of your day could be logged and you should have the ability to contribute that or you have some sort of insight. You should be able to contribute that. Have your data be shared and be rewarded for sharing the data. And there's some things that actually lend itself very well. Like you were talking about earlier around diet and nutrition. I think this is something that has the ability to really take off in D.Ci

Starting point is 00:27:39 because this is something that is very longitudinal. So anything you eat, you should be able to take a picture of that thing, put it to some DAO, say how you felt, share that data set. That data set is purchased. And then everyone who uploaded a picture of their food and their data point of how they felt after it could be rewarded when this data set is purchased. For the minute share of data that they contributed into the data. Pro rata. And this is something that you can actually do with DBDAO is like you get rewarded based. you fractionalize a large data set

Starting point is 00:28:14 so that when it's purchased, everyone who contributed to it gets a portion of the rewards. But this is something that works very, very well for DCI. Other things are a little, they're not to say that they don't work as well, but they're a little trickier.

Starting point is 00:28:26 Like, I want to do like scanning electron microscope research. It's a little harder to democratize than something that is, that more people can participate in. Yeah, yeah. And again, so many different dimensions to DCI, as an idea, as a field, if you want to call it a field or a narrative maybe.

Starting point is 00:28:47 And you were talking about defy and DSI coming together, right? So something that, I don't know if it was Paul or Tyler for Molecule, who kind of birthed this biodow ecosystem, including Vito Dow. I remember a talk that I watched from one of them back in like 2018, and I only saw this a year and a half ago, but it really inspired me because they were talking about the idea of IPNFTs as enabling a much more efficient biopharma IP market, intellectual property, market. Because now you can sort of wrap intellectual property in an NFT wrapper and fractionalize it

Starting point is 00:29:22 and create much more transparent and liquid markets and enable things like prediction markets for drugs that are in clinical trials. Because the whole biopharmia industry, it's very opaque and it's very, very hard to access unless you're an accredited investor. It's actually probably impossible. So they thought, well, how will we bring more liquidity to this? use this to fund more research and sort of hyper-financialize a lot of these things, a lot of these ideas, like has happened in crypto. And I think a lot of scientists are turned off by that term,

Starting point is 00:29:55 but I actually see it as a superpower of crypto that can really feel a lot of innovation and a lot of discovery. And, I mean, yeah, I want to come back to scientists and crypto, but. I mean, the term hyper-financialization generally turns a lot of people off. We definitely need to find a new term for that. The way that I've explained this in the NFT space is like a lot of the resistance to NFTs came because like, oh, you're putting finance in our art. Get your finance away from our art. And I always try and flip it around on them as like, well, you're actually putting your culture into finance. Like these are an opportunity to take your culture and make our finance less banky and more artsy. And so like finding new ways to explain like, yeah, hyper-financialization,

Starting point is 00:30:36 but also, you know, incentives, compensation, rewards, upside, growth. all of these like adjectives that have been missing from so many different other industries. Also accountability. So like science is accountable-ish, but if there's a chain connecting everything together, you can see where the weak points are and you can start to tighten them up a little bit, which I think is probably needed at some point. Definitely. I mean, so one thing I feel like I need to say is that there's this question of onboarding scientists into Web3.

Starting point is 00:31:07 even with D.S.I. really picking up steam over the last year, it's still hard to get typical scientists working in labs, working in universities to kind of pay attention to this, because one, scientists want to do science. Like, most of them don't want to be writing grants and exploring new things. They want to work on what they're interested in. Second, crypto has a pretty bad rap among the, you know, the rest of the world, right?

Starting point is 00:31:31 So if you say the word crypto to a scientist, they kind of recoil with disgust. They lose interest. They don't want to hear about it. They think it's all monkey JPEGs and scams. And, I mean, of course, scams are a problem in crypto. But the other thing is... You're not wrong about that characterization. So when I talk to my colleagues about DISA, I start off with blockchain technology

Starting point is 00:31:52 and start explaining why blockchain technology is unique and why an immutable ledger enables us to do things in a trustless way. And then they start paying attention. They start thinking, oh, okay. So I thought it was just money. I thought it was just like Bitcoin. coins. And I'm like, no, no, no, no. It's just technology. There doesn't need to be money in there at all. That's just like the first use case that was actually, you know, a really good use case.

Starting point is 00:32:15 I think one of the interesting things is going to see the, how D-Sai and TradSai sort of interact. So like look at like Uber. Like it never compete. It competed with taxis, but Uber never tried to change the existing taxi industry. And I think that there's an argument to be made that D-Sai won't necessarily compete. Pete with Tradzai in the sense that it's going to launch its own initiatives around health and wellness, around nutrition, around longevity, around cryogenics, things that are typically not touched as much in traditional science, and then develop its own ecosystem that is sort of bifurcates from the existing infrastructure. So it's not going to try and get money, a D-Sy project is not going to try and get money from the NSF. It's not going to try and do research at Stanford. It's not

Starting point is 00:33:10 going to try and do research, publish in nature. Like, right now we have Ethereum. It could, but like Ethereum doesn't publish their EIPs on a computer science journal. They have their own research thing. They have their own EIP thing. And they've developed this sort of own bifurcation on how they do improvements. And I think that there is definitely a possibility that D-Sai will bifurcate from Tad-Sai and it'll develop its own ecosystem because it's just oftentimes so hard to move an existing culture within something that only the people that want to participate in it will participate in and the people that don't will just continue on the way. To add to that, I mean, I feel like my bullcase for D-SI is that all of traditional science

Starting point is 00:33:57 just becomes synonymous with decentralized science things that we talk about now. Science is supposed to be decentralized in the ultimate use case. Science is supposed to be a marketplace of ideas and competition. Something is true until it has proven false and stuff like that. Totally, but exactly. So it's supposed to be that, but in a lot of ways it isn't. And there are a lot of mislined incentives which lead to things like most of the data being published not being reproducible in like biomedical research,

Starting point is 00:34:25 some ridiculous set, like 60% or something. And I think, again, with this technology, we have opportunities to build new systems which address those problems, which create the right incentives to address those problems. I'm being a little bit vague because we're still figuring this out. And a lot of people are excited to discuss these ideas. If you want to jam on Dysai, come find us on Twitter and come to the next DSI conference and meet-of. D-Sy-N-YC. We have them monthly, actually. Oh, yeah, you're wearing the shirt. I should have worn a Gitcoin shirt.

Starting point is 00:34:54 We'll talk about Gitcoin and funding after. The Bankless Nation is very familiar with Git-Coin. Yeah, yeah. But yeah, I mean, it's... You need a bankless nation for D-Sy. Something like some term, like something less. Yeah, yeah. But so that's the thing.

Starting point is 00:35:08 I think really like D-Sai is just going to be the new infrastructure for how science is done. I don't think that D-Sai is going to replace our current scientific institutions. It's not going to replace PhD training programs. Like there's a lot of values you get from the science apprenticeship of being in the lab and doing the work and being around scientists and just like, becoming a scientist. But I think we can improve that process by bringing new funding sources, by, you know, creating new incentives, like I keep saying, but just making things more efficient, better tools, making it easy to collaborate and to publish your work. It's like sort of really simple stuff in a lot of ways, but scientists need a good reason to start doing

Starting point is 00:35:49 things in a new way. And that's where we need to work. You know, what problems can we solve for scientists now that will sort of create an entry point for all this technology to flourish. Yeah, I totally agree with what Boris is saying around PhDs are still important and needed in some areas for sure.

Starting point is 00:36:08 That's not the part of science. We want to disrupt. Well, you actually do learn something in a PhD of four years of X number of years. Four years? Of dedicated research. It is useful in doing these hard subjects. One of the interesting things

Starting point is 00:36:24 around D-Sai, that's a bit of an unknown still is like how chat GPT plays into this and how AI comes into play. Can an AI, can you learn from an AI? Can an AI take the role of what previously had a PhD advisor? So could an AI mentor you and be like, get you up to speed to doing deep foundational science research?

Starting point is 00:36:45 And can you use, can chat GPT then say like, oh, do this experiment and I do the experiment? And then I upload it to D-Sai and then I get rewarded for it. So I think one of the things I'm very excited about in D.Sai is also more of the integration of AI into how it thinks. One of the thing that would be really cool is like when you're writing a research paper, one of the important parts is like related work. AI could generate that thing in an instant. And that thing would previously take a human, you know, a long, long time to write. So there's a lot of cool things that were things that are fundamentally changing here, which will even further propel D.Sai.

Starting point is 00:37:21 I was wondering when AI would come up during this conversation because something that I've noticed a lot around the conversations regarding crypto and AI together, it comes down to like, you know, decentralization of models and reproducibility of these models and being able to trust that this was the model that was run to give you your output. And all of these same problems are directly transferable

Starting point is 00:37:45 to other areas of scientific computing, like computational biology. So I think there's a lot of space to explore there. The design space is huge. Also things like knowledge graphs and discourse graphs and how you can use that to train AIs and also reward people who have contributed to this work. I think crypto is a big role to play in all of these emerging technologies.

Starting point is 00:38:08 And all these emerging technologies have a big role to play in science. So at some point we're going to stop talking about DISA. We're just going to talk about the different products that people are building on. I think maybe, this whole like new frontier for listeners is like oh man I didn't really expect this this is like an unexpected turn of events for crypto to like be

Starting point is 00:38:27 integrating into the science space but I think it's worth kind of zooming back out and putting on our Kathy Wood hat because Kathy Wood was always about hey gene editing synthetic biology crypto AI these are all intersecting

Starting point is 00:38:43 and so these are all coming together and because our products are finally becoming like useful for each other these are all new technologies that are outside of the system and they're all using each other to help bootstrap each other. And like from the crypto, I'm coming from the crypto side of things, the providing new scientific tools to a new scientific community is probably like one of the most legitimizing use cases of crypto that we've ever created. Yeah, agreed. And one of the things that's slightly different around D-Sy than D-Fi is there's exogenic information being added to the system. So when I conduct-

Starting point is 00:39:17 Great word, by the way. Thank you. When I conduct an experiment, I'm taking data from the natural world and putting it on chain. That is creating value. When people are swapping tokens, it's a different type of value. It's a speculative value. It's a different type of value. But when someone does something and creates value that way, and that's what's going to drive these projects to create value.

Starting point is 00:39:44 is like there's useful information here. In the same way, when someone builds a house, they're taking lumber and nailing it together, and that creates something that's really valuable. And here, when you take data and you conduct experiments, and you put it on chain and you do analysis on it and you show it's reproducible, that creates tangible value.

Starting point is 00:40:00 Beautiful, guys. This has been a great first exploration into the world of D. D.C. I'm excited to go down this rabble hole even further. If people are peaked, is there a starting place that you suggest to them? Like, how would one get started exploring the deeper, the world of D. DbDau.XYZ has a one-pager on D-Sai, and you should also check out all the meetups that are around the world. D-Sy, NYC, D-Sai Tokyo, D-Sy, London.

Starting point is 00:40:25 There's many more out there, and you can Google them and find them. We will put the link into the show notes. I'd also add the Ethereum Foundation has a pretty good and comprehensive page for D-Sy with tons of links. And if you want to see what some of the current, like, new projects in D-Sy are right now, check out the D-Sai Gitcoin grant round. That is, I don't know if it's going to be before or after this, but you can get a sense of like, what are people trying to get money to build right now in D-Sai?

Starting point is 00:40:51 This is part of the whole new grant stack and Allo Protocol launch at Gitcoin, which I had to talk about at some point, because I'm organizing the D-Sai round along with some community stewards. Beautiful, guys, thank you so much. I've learned quite a lot, and I think I'm very optimistic about this world of science on the blockchain. It's nice to be able to say on the blockchain again. said that in a while. It's all just going to merge together. On the blockchain. Cheers, guys. Appreciate it. Thank you.

Starting point is 00:41:16 We are here with Alok Taii of Vibe Bio. Alok, welcome. Thanks so much for having me. Really appreciate it. So we are here in the synthetic bio track at Zuzalo, which is way more broad than I ever thought that it would be. And we got introduced at just one of the talks today. So maybe you could introduce yourself and explain what a little bit about what Vibe Bio is. Yeah. So I myself, I'm actually a scientist. I spent about 15 years at the bench doing research, then caught the software bug and started a bunch of software companies, focused on the biotech industry. Those companies went on to raise about 100 million plus in venture, a few hundred employees doing pretty well. So an entrepreneur builder at heart. Exactly right. And someone who not only was a practitioner of science, but also I've had the fortune of seeing how different functions in the life sciences industry operate.

Starting point is 00:42:07 having built tools for clinical trials, for R&D labs, et cetera. So I feel like I was fortunate to have a really unique viewpoint into how pharma operates and how the overall drug discovery process unfolds. And so can you go into a little bit about the problem that you're tackling here with Fyb? Yeah. So as an organization, you know, we were founded in 2022. The impetus for founding Vibe was that while I was building software companies in the life sciences space, In mid-2020, my wife and I were fortunate up to have our first kid.

Starting point is 00:42:41 Though the pregnancy went okay, unfortunately our daughter was born very sick and spent a long time in the hospital. One of the reasons was because the diseases that she had were somewhat common, the biology well understood. But unfortunately, there were no dedicated therapeutic options available to her. And as a consequence, she spent a long time suffering. That's an interesting dichotomy, a common disease without a ready-to-go treatment. Correct. And that was sort of my focal point. when she became sick.

Starting point is 00:43:09 Right. Where in a circumstance where a lot of people suffer from this disease, when we truly understand its root causes, why is it that we don't have a treatment, much less anybody working on it?

Starting point is 00:43:18 And that became an obsession for me, and that translated it into bio-bio today. Okay, so talk to me a little bit more about that. What were you, I'm sure, as a very concerned adult, a parent of your first child, you're watching them, I'm assuming, live in the hospital.

Starting point is 00:43:35 the archetype, the typical response, that leads to Hollywood response, is that they go on a learning, they go down a rabbit hole. Is that what you did? I'd say very much so. I think in my case, we were fortunate enough to live in Boston, which has phenomenal medical establishments as well as a deep biotechnology corridor. And so given my experience having built software companies in the space as well as having been a scientist, it allowed me to very rapidly spend time with everyone from biotech family. to pharma companies, to venture capitalists, to truly peel back the onion and understand why in this circumstance we don't have treatments for these sorts of rare diseases and for diseases at large. Okay, so just redefine the problem for me one more time just zooming back out, and then we'll start to talk about what your next steps were. But the problem was that there wasn't a solution for this common disease? Yeah, so basically for my daughter's diseases,

Starting point is 00:44:33 there were no dedicated to therapeutic options. And when we started to understand why this exists, we start to realize that the challenge is not finding a cure, but rather funding them. Further, when you actually look at the incentive structure within the pharmaceutical industry, they often try to go after the largest potential diseases and deprioritize the balance.

Starting point is 00:44:54 But when there's 13,000-plus diseases out there, it's really hard to get the industry to focus on more than just a few hundred. So we saw this dual-fold challenge of both capital, capital access, but also incentive structure and alignment to go have the metal to go find treatments for these sorts of diseases. Is the right mental model for understanding this is like especially when you say we know what the disease is, we just don't have the cure. That sounds like one half the problem solved at the very least, but it's about, you know,

Starting point is 00:45:22 continuing on this arc down to go to the other problem. It sounds like the, maybe a way to articulate this is that there is a long tail of diseases is out there and with the current incentive structures of venture capital and research and perhaps maybe insurance is involved that they don't really care or they care less about the system cares less about the long tail of diseases. Is that a way to articulate this? I think you've started to hit the nail on the head because when you look at the incentive structure today, a lot of these companies are valued based on a net present value of the drugs they pursue. Naturally, that guides those medicines to the largest potential diseases as opposed to the remaining 13,000, where

Starting point is 00:46:00 There's actually good economic opportunity, a measurable amount of unmet need, but just get deprioritized in comparison. And one of the areas that we've often seen this challenge emerge is as these medicines are being studied and developed, as they approach what's known as an inflection point, it becomes an opportunity for the company to prioritize and double down on usually the largest diseases and deprioritize the balance. So to your earlier point, the venture capital funding environment, as well as the decision-making and incentives, just unfortunately deprivation. these sets of diseases, and we see new opportunities to be able to crush correct for there. Yeah, and I think bankless listeners who have been listening with us for a long time will probably understand there's some basic patterns that are probably about to emerge here. First, we're talking about capital coordination and failures in capital coordination. What is crypto other than tools for coordination?

Starting point is 00:46:52 And when we talk about the long tail of things, usually that is where these weird new frontier technologies actually get their way to get their start. So I'm assuming the audience and myself, actually, starting to see the seeds of how blockchain starts to work. But before we started talking about how, because again, we're at the bio week of Zuzalu, where bio meets blockchain is the name of this particular week. So I think listeners can see where this goes. But first, I still want to do a full kind of autopsy of the system of incentives that has created this failure mode in addressing the long tail of diseases. Can you really just walk us through the full problem set so we can really understand this problem? For sure. Well, so drug development is a very complex, long-term, highly risky endeavor.

Starting point is 00:47:37 Oftentimes it starts with the first process of discovery, which is really trying to understand the root biology of a disease at the mechanistic, you know, whether it's the genetic or the cellular level. In those circumstances, whether it's an academic institution or an early-stage biotech company, you have scientists in a canonical lab trying to better understand the mechanics behind a disease and then hopefully elucidate. a gap that you could potentially use to treat that disease. From there, there's a myriad of tools that have been developed over the past two to three decades, from small molecules to antibodies, gene therapies, to CRISPR that allow you to be able to then go and remediate that disease, and those are then identified in that discovery stage. From there, those medicines are then moved into what's known as preclinical development, where you figure out how to manufacture it, test it for safety, and if it passes that bar, you can then move into a clinical trial step.

Starting point is 00:48:35 Most folks, especially given the pandemic, are probably familiar at a high level with clinical trials, but you're essentially running an A-B test, if you will, to use software parlance of the drug versus no drug to see if the drug actually works to treat that disease. And then ultimately, if it does, then governments, the FDA regulatory authorities, will allow you to then sell that medicine out. And so when you start to break down that overall approach, what ends up happening is that that cascade ends up focusing the industry on those diseases where there exists a well-trodden path. But those diseases, sorry, those medicines that pursue a well-trodden path are usually going after diseases that already have some treatments that are already out there. In the totality of time, however, what we're also starting to see is that diseases themselves, whether it be a cancer or an autism or IBD,

Starting point is 00:49:26 are actually not one large disease, but actually are composed of hundreds of little diseases. So we're seeing this other, broader, industrial shift away from sort of one drug to try and treat everything, and often poorly, but rather very targeted, very specific medicines that treat very explicit diseases out of the gate. So this is sort of the overall landscape. Overall, I'd say there's probably $1.2 trillion a year that are invested in pharmaceuticals every year, and maybe almost $80 to $100 billion a year and just in the R&D phase as a whole. So a lot of opportunity, I think, to drive efficiency, but also I think a lot of opportunity for communities to also play an important role. Sure. Yeah. And intuitively, every time there's a step that a,

Starting point is 00:50:13 in this process of creating a cure for a disease, that probably makes the longest part of that long tail less and less viable. So every new step is just more cost. And we reduce the to go and we have to, you know, not risk too much, we can only risk a little bit every time new steps get created. What would you say is the most critical step in this that has removed the most of the long tail? I might guess that it's the FDA in regulation, but I won't speak for you. What are the big steps here that we should focus on? Yeah, you know, I think the items that I would highlight is this broader concept of inflection points. Okay. Unlike the software world or even Web 3, where you can get incremental users easily,

Starting point is 00:50:55 In the biotech world, value is created by these highly binary events known as inflection points. An inflection point is essentially a piece of data or an experiment that helps produce an understanding around a given medicine and supports its continued advancement and investment. Some example inflection points that are in the drug development process are when you prove in a petri dish that this candidate medicine actually could treat a disease. or you do so in an animal model, or you do so in a human, like in a clinical trial. Those are example inflection points. And I'd say some of the key gaps that often emerge

Starting point is 00:51:34 are in this process, not only the fact that there's multiple of them, as you pointed out, but getting medicine into patients is usually a very expensive and time-intensive endeavor. And as you start to go down this long tail, there are fewer and fewer people that you can actually go and collaborate with to actually run those trials,

Starting point is 00:51:51 which makes it even longer and more expensive. And so as a consequence, I think you see people wanting to mitigate that kind of risk and focus on those better tried paths. Okay. So it's, it's, you wouldn't say there's any one particular obstacle. It's more of just, again, the holistic system just doesn't produce the resources and the connections that need to happen. Yeah, it's death by a thousand cuts, unfortunately. Right. Okay. Well, that's the worst kind of problem. Yep. Yep. Okay, so let's go into the solutions. So we can talk about Vibe Bio a little bit here, but then also just high level. again, using the principles that we've talked about at bankless, maybe we can keep that in that theme of just like capital coordination and going and expediting the process and attacking the

Starting point is 00:52:34 long tail of diseases. So where does this conversation start when we talk about the solution here? Yeah, well, you know, I think we're really fortunate that I think Vib's approach has drawn a lot of inspiration from how patient communities have actually remediated these issues in the past. So if you actually reflect on the past half century of drug development, There's been many circumstances where medicines were actually not developed by VCs or by the FDA, but actually patient communities themselves. I'm assuming out of their own raw need for the solution. Exactly right. When no solution exists and the existing institutions don't see it to be viable, patients themselves have rallied together in the form of a community, often instantiated initially as a charity, raise money philanthropically, and then invested in drugs.

Starting point is 00:53:22 and drug development themselves. So some of the most canonical medicines we think about, the vaccine for polio, treatments for cystic fibrosis, forms of hypertension, et cetera, were actually backed not by the FDA or by traditional institutions, but actually by these patient communities. And just intuitively, I'm guessing that events like this that happen are probably for addressing diseases and solutions to diseases that are probably just further along on the frontier than the long tail, Right? Still not super far out, but still like close enough because that's probably what our is the next most viable kind of disease. Is my intuition right here?

Starting point is 00:54:00 I think, you know, you're hitting an important point because oftentimes the legacy institutions look at numbers today around a given disease in that long tail. But time and time again, what we've seen is that the medical establishment underdiagnoses a disease when no treatment exists because you never want to give false hope to a given patient. But the moment a medicine actually comes to the forefront around a given disease, you see this magical expansion in the overall number of patients. Cystic fibrosis is one of the most canonical examples because in this specific circumstance, dating back several decades ago, there were only about a few thousand patients known in the United States. The cystic fibrosis foundation, which was founded to find a treatment for Cystic FF, ended up funding to the tune of tens of millions of dollars, a company called a Rerobrosis. Biosciences, which eventually became vertex pharmaceuticals today through an acquisition, and brought the first set of medicines to the table for CF. After those set of medicines were brought to market and awareness was grown, we saw the patient

Starting point is 00:55:05 population roughly 10x over that period of time because diagnostics improved. So even those diseases that we think are long tail, actually, once properly vetted and diagnosed, actually become pretty substantial. Right, so it's almost like just a search problem, right? Exactly right. Yeah. And so what we've also started to see is that this same model that the CFF has pursued has led us to, again, things like the vaccine for polio, treatments for forms of hypertension. And I think this broader concept of communities come together coordinating capital have led to not only transformative medical outcomes, but huge financial wins.

Starting point is 00:55:42 Vertex Pharmaceuticals is an $80 billion market cap company that does almost $7 billion a year in Topline, all from about roughly 10,000 patients globally in CF. United Therapeutics, which is started by Martin Rothblatt, does over a billion dollars top line initially started focusing on pulmonary arterial hypertension, et cetera, et cetera. There's many such examples where these are transformative medical and financial outcomes when operated this way. Okay, so I cut you off to go down that little rabbit hole as we're talking about the solutions here. So maybe let's pick up that thread. Yeah.

Starting point is 00:56:16 We can continue going down what Vibe Bio is and how the puzzle pieces all come together. Absolutely. So what we saw is that model of community-driven drug development as being a true inspiration for what we do at Vibe. And so Vibe Bio essentially wants to take those, that model, and put it on steroids. So Vibe is essentially a community of patients and scientists that help identify and fund treatments and specifically treatments to move them through an inflection point. So we have a broad-based group of communities that we partner with, as well as patient charities and drug developers, that help us identify and vet these high potential medicines that exist inside biotech companies, academic institutions, etc.

Starting point is 00:56:59 We then provide capital to be able to help advance those medicines at the point where it's hardest to get capital, to then ensure that those medicines are able to show their potential and then be able to recoup our investment once they're able to obtain. proper sources of funding. So it's an investment vehicle. It's a way to allocate capital to invest in the opportunities that Vibe has identified are good financial opportunities that are also targeting diseases and cures for diseases that are not being targeted by the current institution. Exactly. You know, near and dear to my heart are sort of rare and overlooked diseases, which about half of the projects we're evaluating right now are sort of in that space. But we see a broader opportunity where this challenge of medicines sitting on a shelf as it approaches an inflection point is a common problem across many different diseases. And so we see an opportunity

Starting point is 00:57:52 by which we can help unlock capital and help ensure a medicine gets a shot on goal. Okay. So where does the blockchain element fit into this? Where does the crypto element happen? So, you know, when we started, we saw a huge opportunity to empower patient communities because of the work we've seen from other organizations as a form of charity. But what we saw is that in the current instantiation of whether it's a C-Corp or an academic lab or charity, you have inherent limitations. Some of those limitations include how many people can participate and have ownership, limitations in terms of the types and quantity of capital that you can access,

Starting point is 00:58:27 as well as the risk tolerance of that capital. So what we see is actually a DAO is a really unique construct because it allows you to have essentially infinite scalability of ownership and participation, especially amongst the patients themselves. Second, it allows you to leverage something like tokens to be able to raise meaningful sums of capital from a source which is both looking to take on big projects and take big swings like in crypto, but also provides liquidity. But then third and finally is that we see it as an opportunity by which any proceeds from those medicines can flow back to the community to be reinvested in the next generation of projects. So we see Dow's and these sorts of communities and that approach as being a very high potential. way to kind of scale the development of medicines in this way. And that's why our mission at Vibe Bio is to find every cure for every community.

Starting point is 00:59:20 Would it be fair to classify Vibe as just an investment, an investment doubt? I think we initially would sort of see it as a capital deployment approach that enables this approach to financing that we call inflection point financing. And I think our hope is to be able to then enable investment DAOs to come in and take advantage of that model. Unlike a traditional investment DAO, one of the other pieces that we're also starting to build is technology to allow us to evaluate rapidly these high potential projects. Because one of the issues that emerges as capital allocators is often adverse selection. And I'm sure that's something that a lot of your listeners has probably seen across a myriad of other DAO's and projects.

Starting point is 01:00:05 So we see our remit as being not only advancing this approach to find around inflection points, but also building the tools to make sure that DAOs and communities can make good financing decisions. Can we just do the, just the anatomy of Vibe Bio? Sure. And we'll go through, maybe there's like a big step one, step two, step three that we could talk about. Like how do we understand the story arc here? Yeah. So let's, so maybe taking a step back, Vibe as an entity is about nine or so folks, about one-third, one-third, one-third, one-third on the community and marketing side, one-third on the drug development side and one-third on the software and engineering side.

Starting point is 01:00:39 And so as a team, we are actively engaged and partnered with biotech venture capital firms, biotech founders, patient communities, who oftentimes are in the flow of high potential medicines that just aren't quite ready for a larger round of financing or proper partnership, say, bigger pharmaceutical companies. So we are receiving proposals from them basically every day of high potential medicines that with a modest amount of dollars, hundreds of thousands, maybe a million or two million dollars, could actually get some real pivotal data to advance that medicine. So that's sort of step one, is sort of the partnerships and the ecosystem that we're looking to build to be able to identify those high potential medicines. Second step is diligence. In this case, we sort of run two processes in parallel, one to look at the financial plan

Starting point is 01:01:31 of those candidate medicines and to evaluate its potential. But then second is to go and do a deep dive enabled by our science. scientific community to ensure that the scientific rationale is solid and that the scientific plan around obtaining that data is viable. This is, I think, the hardest part because today, a lot of that work inside pharmaceutical companies and venture capital firms is highly laborious, takes months on end, and is laden with friction. This is, I think, another area where communities, especially Dow's, of domain experts, can actually expedite and rapidly evaluate projects at scale. Third is finally financing.

Starting point is 01:02:11 So for those projects that sort of exceed a certain bar that we decide to fund as a community, we then release funds to that organization and do so in a partnership with an external service provider who's going to run that experiments and obtain that data for the biotech. So that's sort of the three-step process, proposals, diligence, and then eventually funding. So to put this into different terms, is the first step like deal flow sourcing, except for diseases. And so, like, what is the best disease that we can identify that we think that we have a viable path to create a cure for?

Starting point is 01:02:46 And that's step one. It's like deal flow, but with diseases and opportunity identification for the best diseases that aren't being yet addressed by the fat tail that are on the long tail. So step one is, like, disease deal flow. Yes. Step two is, like, okay, let's push that through the due diligence process. Let's stress test this. Let's make sure, like, we can have the assurances that this is a good investment.

Starting point is 01:03:10 And then if it passes that, then it's actual investment. Exactly right. And then that's when, like, you finance what is a disease startup, which is, like, what it takes to make a cure. And then that cure, if that cure successful, is owned by the ViBio org. And that is the way that the ViBio has, like, profit or capital generation. Yeah, great question. So we initially had started out when we launched about nine months ago, spinning up new biotech companies around these candidate medicines, investing and building out teams to pursue them. Oh, cool.

Starting point is 01:03:47 Yeah. I still believe that to be a long-term path in terms of how we can enable communities to pursue medicines and enable the focus on those diseases. What we're doing at the moment and what we found greater scalability is that many of these high potential medicines already reside within biotechs. that have a team, capital, labs, etc. But oftentimes, as these biotechs approach an inflection point, their boards are trying to focus them in on, say, the highest potential medicine because they lack capital to pursue the others in parallel. So instead of us, say, taking on the medicine,

Starting point is 01:04:22 that team already has the expertise, the infrastructure, and the know-how. So we're actually doing is providing them with access to capital to run drugs two, three, and four in parallel with the first one. And then when that institution is able to get to the next round of financing, we're then paid back for the amount that we had shared risk on. And then would be the ideas, like, for these new companies that are generated, you have some sort of stake in them. Correct.

Starting point is 01:04:48 And they only exist because they have economic viability, probably, because they've identified a cure for a disease that is in need because that's what the original process was for. Exactly right. And so this is like kind of an org of org sorts of things where every single new org comes out, has decent assurances that it's going to be a viable capital growth org. Yeah, I'd say so. I think the interesting thing is that when you look at sort of the incentive structure, because a given biotech is financed to the point where I can pursue, say, one high potential medicine, they often tend to aggregate to a few hundred sort of diseases out of the 13,000. In our case now, through our financing mechanism, we can actually enable them to have. multiple shots on goal to becoming a successful biotech because if you only have one medicine you're working on, that's a lot of risk that you're putting on the organization. So what we're

Starting point is 01:05:40 seeing is that our inflection point financing model allows these biotechs to not only get to the inflection point, but second, increase the chances that they get there. And if they do, and they have multiple drugs that work, have outsized value once they do. So it becomes a really exciting model, I think, longer term, and one that we've been getting a lot of really positive feedback at this conference and elsewhere about. Right. It's one more time. Where does the actual Dow element? So I don't think there's much of a blockchain here. It really just sounds like there's some governance decisions, and that's really the main application of the crypto world to this.

Starting point is 01:06:16 Yeah, so I'd say right now we're just trying to get the basics of the business model working. So we have yet to launch the token and formally instantiate the Dow. Unfortunately, being based in the U.S., there's a big regulatory shift. I love to hear your thoughts on that at some point. today, but yeah, so we're right now currently trying to get the mechanics, the diligence process, and the tooling right, in order to be able to scale up the model using tokens. So one of our investors is Ryan Selkis from Missouri. I'm sure someone you know as well. Oh, yeah.

Starting point is 01:06:49 You know, one of the things he's mentioned to me in a recent call was that he've used tokens like fuel. He's like, if you have a dumpster and you add tokens to it, you're going to have a dumpster fire. But if you have a rocket ship, then you'll get rocket fuel and then reach the stratosphere. And the analogy he was trying to make is that you have to ensure that both your community and your core economics and business model are sound before you add tokens to the mix to ensure that you can actually start to scale things up and make good decisions long term. So that's why we've been really methodical over the past nine months to focus in both on our technology products as well as our community build

Starting point is 01:07:26 to help find really exciting drug programs. Is it too early to ask what the mechanism of the token does? A little too early at the moment, but I think thinking of it as a governance token, if we choose to launch one in the future or when we choose to launch one in the future, is probably the right mental model.

Starting point is 01:07:42 But right now we're sort of instantiated as a C-Corp with cash off our balance sheet and a few high net worths. And so that's what has allowed us to get some pretty good momentum and hopefully initially pre-brupt this model to then be able to extend out using a token potentially in the future. Okay, so the original process they were talking about,

Starting point is 01:07:59 the three steps, the deal flow, the due diligence, and then the financing, that is what would be governed over, I'm assuming. Correct. In the future thing. Yes, you got it. Beautiful. So we're proving it out in a centralized way initially with the first couple, in a scrappy lean way,

Starting point is 01:08:15 and then intend to translate that over to a more formal DAO or other sort of vehicles over time. Why does it need to be transferred over? Why can't that just be contained to the? the experts. I think the diligence process for sure should be, but the part that we've seen as we spent time with over a thousand patient families, patient charities, is that patient communities, I believe, having been the father of one, that they should be involved in two facets of the drug development process, most importantly. Prioritization and capital allocation. And I think diligence for sure should be pursued by experts, but ultimately the final sort of check to be written,

Starting point is 01:08:54 I think patients should have a seat at the table for. Okay. And that would mean that they have a saying governance. Correct. Right. And so, do you know, maybe it's again too early, but how would they get their hands on tokens in order to have that governance power? So some of the things that we have been talking about in the industry for the past couple

Starting point is 01:09:09 months has been looking at the overall tokenomics and the allocation of tokens, enabling patient communities themselves to have a pretty measurable, if not the largest stake in a DAO itself. And the way we would do that is instead of giving it directly to individual patients, because that's hard to vet, is in the U.S. especially, many of these diseases that don't have treatments are instantiated as 501C3 charities. So we can actually provide tokens and allocation to the patient charities themselves, the foundations, and enable them to be part participants and owners in the process, such that Not only can they govern, but they can also capture some of the upside if the overall project is successful.

Starting point is 01:09:51 So without knowing really the specifics of the full role of the token in this org, when did you have the aha moment about using crypto tools to help facilitate this? And what really brought the idea of using a Dow to the table for you? Yeah. You know, I think that really happened in mid-2020, after my daughter was born, because I had started getting into crypto a few years prior. what really excited me personally was the vibe, for lack of better phrase, within the crypto industry and Web 3 more broadly, and its potential, I think it has to sort of rewrite Wall Street and how money flows. But then when my daughter got sick, what I knew after having peel back the onion on this industry and some of the challenges is that we truly need ownership to extend to people other than those who are purely financially motivated. and second, we also need participants who want to inherently take big swings.

Starting point is 01:10:48 And when you start to think about those two requirements, when my wife and I looked at other sorts of vehicles, a C-Corp, a foundation, an academic lab, they all had gaps, and only a Dow and Web 3 really enabled those two in the long term. So, you know, we saw that as the telltale that that was the technology stack we should be building on, and that's some of the principles

Starting point is 01:11:10 that we should be bringing in from the get-go. And these other sort of canonical examples like the Cystic Fibrosis Foundation and the March of Dimes, I think, just further cemented that from a community standpoint. Sure. So it was more, maybe it was less about

Starting point is 01:11:21 these specific technologies are exactly what I need, but is the community ethos and the community culture that is what you want to align with and what you want to attract. And so perhaps that was why you were more open to adopting

Starting point is 01:11:34 crypto tools in a time where other people found it kind of unsavory. Yeah. Well, yeah, I think that's a fair statement. I think I'll be candid that, you know, I think of myself first and foremost as the father of a sick kid. And in that circumstance, I'm not dogmatic about what technology I use.

Starting point is 01:11:49 I want to go solve the problem. And it just so happened that I think Web3, Dow's, community-oriented coordination tools, I think are the ones that are going to have the best long-term potential and are the direction we want ahead in. And I think the broader industry does too. So what other piece, have we touched on every single piece of this story here, or what, stone have we left unturned? No, I think we hit on a lot of the key pieces. I've actually loved to ask you a question, which is, you know, you sort of mentioned the volatility in the Web3 space and the regulatory environment. You know, that's one of the challenges I think we face today and why we're in part taking our time and being really diligent on any sort of white paper and

Starting point is 01:12:29 tokenomics is because of the regulatory uncertainty, at least in the United States. Curious to hear what you've been seeing, given your perch across the industry. Sure, yeah. So, again, without too much details, there seems to be some of the common patterns found here. So we have a governance token. We have this organization that invests in opportunities and then hopefully harvest those opportunities to be reinvested back to the org to invest further, which means capital appreciation. If that means that we're putting this thing and that is being governed by the token, like the equity, the word equity and governance token are pretty similar. And so, like, my regulatory ears are definitely perked. Yep. And so, but also at the same time, uh, that relationship between like coordination between capital, financing the long tail of not just diseases, but planet, everything, planet earth, right? There's so many long tail things that humans haven't discovered yet.

Starting point is 01:13:28 Like, this is why we use, we're on the frontier at bank list. Like, we're on every frontier. Right now we're talking about the frontier of diseases that haven't been addressed yet. Uh, and so like using. crypto as capital coordination tools along with tokens for incentive alignment and giving upside to communities which is one of the core primitives of this space

Starting point is 01:13:47 that is what we are here to do. And then sadly, Gary Gensler comes into this conversation and says hi, hello, no you can't do that, which is really sad, right? And one of the big themes that I've noticed while listening to the talks over at the synthetic bio and the longevity tracks and talks is that

Starting point is 01:14:07 man, the FDA really messes everything up And I don't find it any, like, it's not a coincidence that, like, the crypto industry is frustrated with Gary Gensler, the longevity community is frustrated with the FDA. It's like, man, top-down regulation really comes in and hampers a lot of progress and Rob's a lot of opportunity here. So with regards to the regulatory conversation, like, I mean, I'm not a lawyer and I don't really have too much advice for you other than just like, yeah, you're kind of like pushing up against the boundaries here. And not that I want to encourage any sort of just like, violating the law, but sometimes it takes the bold to push the frontier. And I think the crypto industry is gearing up to fight back against Gary Gensler, and we are currently, Coinbase is currently doing that. And you have a bunch of time, it sounds like, before you enter the fray. And so a lot of new things could have happened by then. But the stories like this and examples of what we could do had we the freedoms that we desire in the crypto space to unlock opportunities like this is exactly the kind of stories that need to be told to the world.

Starting point is 01:15:12 So it's just a matter of earning hearts and minds of the people to say, hey, Gary Gensler, like, back off. Because even members of the SEC are saying that to him, right? And so it's really just this one rogue actor. I don't even want to call Gary Gensler the SEC. He just happens to be in the biggest chair. So that was kind of a rant without any specific answer. But those are all my thoughts for you.

Starting point is 01:15:35 Yeah. Well, I think, to be candid, I think you hit the nail on the head in terms of, how the technology can be better understood and better integrated into broader society, at least in the U.S., where I think it really comes down to individuals and them speaking up about the value it creates for them. You know, as silly as it sounds, I think the analogy that I often think about is actually Uber when it first launched, right, in 2008, 2009, 2010. You know, I remember when it launched in the D.C. market, the local government came in and shut down. Uber. They even arrested and impounded one of the early black cars. that were on the Uber network. And so what ended up happening

Starting point is 01:16:11 and why did Uber end up becoming as successful as it is today and pervasive, even though it was illegal in many cases. Same with Lyft. I think it was because the value to the end customer was so obvious

Starting point is 01:16:24 and the pain point so large that... And the opportunity is so great. And the market so large that everyday Americans found value and use in it because they couldn't find a safe and accessible

Starting point is 01:16:38 mode of transportation from point A to point B. And now this magic piece of software like Uber or Lyft gave them that. And they were willing to vote people out of office who wanted to take that right away. And so I don't think it was easy by any means for Travis or John or any other folks there. But I think it was a circumstance where the world recognizes that this need to exist. It created real value and therefore is willing to advocate for it. And I think crypto is at that point now where it needs to find that same set of opportunities and that same connection to the everyday American. And, you know, maybe it's defy, maybe it's D.Ci.

Starting point is 01:17:16 Maybe it's something else we haven't discussed yet. But I think that's really the key point. I think you sort of hit the nail the head in that regard. Yeah. And I think it's important for the listeners to really imagine that we're talking about this one particular use case, which is attacking the long tail of disease, to get new solutions for that. And that is one application of human coordination and capital coordination that of many, of a full spectrum.

Starting point is 01:17:42 And so think of this story that you've heard today, bankless listener, as one of another set of long-tail applications that are across the entire space of capital coordination and what is at the root of all things, which is money and capital. And so it's not just prevention of already known diseases and solutions for already known diseases that's that we're talking about. That's just one of many applications on a long spectrum of possibility that is being hindered by being able to connect financial upside with long-tail solutions for long-tail problems. I completely agree. And I think the part that intrigued you the most about the long-tail is that when you are in a circumstance where you're not being prioritized or valued by legacy institutions, I think Dow has become a really interesting structure because it empowers communities who care

Starting point is 01:18:34 about that problem, right? Who didn't have a voice prior? Exactly. Now it gives them tools. It gives them people, right? And it gives them capital. And I think those are the pieces that are absolutely critical to tackle everything from climate change to diseases to, you know, who knows what else. Alak, thank you so much. If people are further intrigued by going down this particular rabbit hole for Vibe Bio, where should they go? Yeah. You can check us out on our website at vibebio.com. That's V-I-B-E-B-I-O-com, or you can check us out on Twitter. We're at VibeBio. Who do you want to hear from the most?

Starting point is 01:19:08 What kind of talent or person out there? What's the archetype that you're really missing that you need to talk to? We're looking to talk to any biotech company or academic scientist who has a high potential medicine. They see the future and how it can help patients, but are struggling to be able to get that compound to an inflection point to raise traditional capital. We'd love to be able to help support any biotech company. with a promising drug in that regard to get to an inflection point.

Starting point is 01:19:34 Alok, thank you so much. Thank you. Cheers.

Bankless - DeSci: How Blockchains are Powering Science 3.0 | Zuzalu #7

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