 Cool Well, we just get the format sorted out. Thank you all so much for coming Where should I stand this? First of all a massive thank you to Zenka For putting up this conference again and pouring all of his energy Into bringing us here today Especially on a gloomy day like this in Berlin. I thank you all so much for coming all the way through It's my second time being here in this. Oh cool. Here we go perfect format It's my second time being here. So we first came to the blockchain for science conference last year. I had a really amazing time The crowd last year was a lot bigger I think which is a good show of tale of like how the crypto economy and the blockchain economy is changing I think last year there was a lot more hype still kind of pushing the topic forward As Zanker kind of said we came out of that entire ICO boom Lot of money moving around the space now. It's kind of stabilizing and I think with that stabilization kind of stays like a stable How do you say in German? They're hard to count The like the core of the community remains Yeah, so really excited to have you all here today My name is Paul Kolhass I'm gonna present to you today about new avenues for scientific funding and specifically with that given intro to molecule protocol and how we think about scientific funding there and What what we need to change? Perfect, everything's working Okay, so quickly with the agenda. I'm gonna give a quick intro to myself how I came about doing this I want to talk about scientific funding and intellectual property more broadly then specifically I want to talk about the problems in pharma today as one example for An area in scientific funding I want to talk about open science and token engineering as a potential solution Then talking a little bit about bonding curves and curation markets as specific examples of that given intro to molecule And then talk about our launch and the first projects that we're testing this new scientific funding mechanism with So it's it was actually quite cool for me coming back to this conference and thinking how much has happened over the past year And I think it's what's generally happening in the blockchain space now either you've kind of stopped talking And you're really working on something and making real stuff happen, or you've moved along to like something else Yeah, so thank you all for being here again. Cool. How do we fund science today? One government agencies Which do a lot of scientific funding for the public good Government agencies tend to be quite slow Which I think we can see more and more In terms of how resource allocations happens on that level has any of you ever applied for a government grant program Okay, quite a few. How is the how is the the UX? Awful, thank you And insecure, okay great so government agencies have been the dominant source of funding Scientific research we know how like slow government has become over the years I don't think it's the most efficient resource allocation mechanism, but we don't have a better one The other one is private companies private companies are excellent at funding scientific research, but they do it with a lot of bias Mostly to serve their shareholder interests or they're just like private capital interests. They mostly funded for intellectual property Then last we have nonprofits which mostly fund New research for a special interest so this could be like foundation dedicated specifically to a rare type of cancer That kind of thing. Where is the public in all of this? So we talk a lot about public markets Like blockchains was really is really I think a technology that enables the public but in terms of scientific funding The public is mostly excluded It's like decisions are being made for us on behalf of the government mainly so a lot of taxpayer money ultimately flows into funding scientific research So this is an example. I think we completely underestimate the extent of public funding that flows into industry later This is specifically prominent in the United States. So one example is That NIH contributed to every single one of the 210 new pharmaceutical drugs that were approved from 2010 to 2016 So every one of those drugs was developed with publicly funded money So collectively the NIH grant funding for this research was over 100 billion over that period Yet like the taxpayer essentially sees none of that because all of those drugs essentially get privatized And then specifically in the US the drug prices ultimately that companies Bring you medicine to market with are incredibly high So this says it's a very in the US specifically in Europe is a little bit different But it's a very dystopian view of how our scientific funding then flows into industry and the public sees very very little at that Well, so what's the deal with intellectual property anyway, so I think I think the interesting thing about Scientific funding is that it often ends in in IP with an IP is privatized yet Scientific funding is this public good that we think of and I think there's a big disconnect there in terms of how we connect those two things So this is the first pattern that was ever issued It's on July 1790 for the invention of potash, which is a new type of fertilizer And it's really interesting to see how the pattern system has evolved since those first inventions Or like since that time it's actually involved extremely little yet It's kind of one of the primary kind of drivers that we used to fund innovation with And that's something that personally got me really thinking like We really we're really looking for new avenues for how can we make scientific funding better yet? We don't really link it with how Intellectual property innovation works and how society can actually reap the rewards from From IP more broadly So this system has barely barely evolved from a legal perspective What are the big problems in pharma today? So this is what we spend most of our time with It's incredibly expensive to bring a new drug to market. It costs an average 2.5 billion dollars Up to 2.5 billion dollars. It's very very slow. So the average time to market is 10 to 12 years And it's very unprofitable and so this really speaks a little bit and to like How we can actually monetize science so most of most of like the real like what we talked about science happens here But it's also at this stage that like the majority of innovation actually takes place and when you new IP is developed So this kind of brings me back to like how is the public funding this well The public is funding most of it here and then it gets privatized later on Now this would be fine Like this would be fine if it was just the way that it is but increasingly it's very unprofitable for Companies to actually develop drugs and bring them to market. So they're cutting R&D at the base layer Which is really cutting into like the like the very basic of how we push science forward So why? Drug development is kind of where software development was 30 years ago And I think this can be said of like quite a few scientific industries We haven't evolved our the way that we engage with science or that we share data more broadly if you go into a lab and see how people are working there like it's still like Physically writing down lab notes being very protective of their research research going through like many many iterations before it finally gets published That's completely different than how software development is working today So I spent most of the I spent my the past four or four to five years working in deep in software development and it's So this was something that I felt when I got into like scientific research was thinking like what if Science was more like software development. So Research is freely shared. It's openly forked attributions can be made And I think there's a quantum leap that we can make if if the systems that we used To to fund science and to conduct science and to share data were fundamentally more open So what we need is we need new incentives. So one is open science I think open science is I think widely misunderstood probably as a concept I'll just I often just like to equate open science to to open source software I Think there's a lot of similarities that could be drawn in terms of licensing in terms of data sharing And the other is token economics And I think these are two extremely powerful new concepts That would be very valuable to make together Because it essentially takes the way that we can fund scientific research like into the public domain And it makes it natively natively public The other really cool thing that happened in the so this actually takes me back to IP So if you think how soft development was done in in the late 90s and the late 90s Microsoft had a Soft development essentially monopoly over the market mostly And at this point IBM and Macintosh and a lot of the other software companies were getting quite afraid of the monopolistic power That Microsoft had in this market everything was patented everything was proprietary There was nothing like open source like to Microsoft open source was the absolute devil And then the linings foundation was started specifically to combat this and provide a new path forward in terms of commercialization And I think the same thing needs to happen in in the scientific community So How does this compare and I'm specifically again taking the angle of pharma, but like how can we compare these two things? So both science and software is very modular and granular in design So there's different steps to go through if I don't follow a step correctly something is going to break down the line It's relies on rigorous testing and security requirements It has very high R&D costs. So developing software is very expensive But very low marginal production costs So once I've made that discovery or breakthrough once I found that new drug once I proved that it's safe Then the marginal cost of production is incredibly low And the other thing that it has is global scalable impact So these are some examples of what is being done specifically in In the in the pharma scientific research community So there's one initiative that we're working with which is called open source malaria It's from a foundation called open source pharma They are kind of trying to take these Linux models into pharma So they're doing all of their work out in the open in an open source github repository They put in their drug targets. They put all their data there It's all open anyone can join in anyone can start contributing researching one of these drug targets and it's really really interesting and they've actually made quite a few Progresses or like breakthroughs, but the problem is if they publish any of their research On this get-up repository. It becomes unpatentable by design So once you put it out in the open now I can't claim IP on it anymore and We all be like yay No one can claim IP like open science But the problem is that now no one is willing to develop these drugs because if we look back If we look back here the cost of bringing a drug to market here gets like these are just costs That you have to go through to fund the clinical trials Which even for something like malaria would it still be in like the 20 to 50 million dollar range if you actually want to get the FDA approved in the end Which now means who is gonna who's gonna front that cost? Like if I can't protect the revenue from it like if I can't guarantee anyone that I'm actually gonna make money to like pay back Pay that back Again, this is kind of we're often private No, it's not private nonprofit funding comes in so the Gates Foundation to date has funded a lot of malaria research But still like it they're really struggling to get anything to market Yeah, so big problem once you do open source it. How do you how do you actually fund it or like how do you commercialize it? This is another example the community for open antimicrobial drug discovery So there's a lot of areas in drug discovery that are like that are going into these nonprofit models But none of them work. So this has been around for five years They've had some good breakthroughs, but nothing is really like taking foot. No, no like no new money is coming in So what can we do? Lastly I want to talk about the big limitations and problems with open science again looking at it through the angle of drug development So we're still in meat space. So we need physical Spaces in biologic testing although a lot of that is increasingly being automated Decision-making in open science and I think the open source is a huge problem Like how how do we do go go versus no go decisions? Should we go with this compound or this compound it often takes someone's instinct to be like this is the research direction We should take regulatory filing and legal liability if we have a drug that is developed open source by like a consortium of people Who's liable who's going to do the regulatory filing at the end of the day? You still need a company somewhere and Then yeah, what are the business models? So this is what I just talked about. How do we create incentives for open source to actually work? Do we need new licensing frameworks really long do we redesign how patents work or do we repackage them? And create new forms of IP It's okay. I don't see the time. How am I doing on time? I'm just wondering Okay, okay, cool. So how do we change systems? so Because I've been in the blockchain space for a while. I've I drank the the Kool-Aid quite a lot So I think but I actually fundamentally think that token engineering holds a Key to a lot of these problems So what we want to do is we want to design new economic incentive markets because we agree that our current markets are not functioning properly Then we want to change stakeholder behavior through these new markets And we need to be extremely humble when we approach this. These are really early-stage experiments. They're not blueprints And we want to simulate behavior before testing and actually Michael Zargham, who's just after me is going to give an amazing Amazing talk on that. I'm assuming It's very very early days for this for the stuff Cool, so let's look at the problem briefly again So in drug discovery what we do what the whole industry does is it sifts through this like universe of potential molecules or new proteins Or drug targets to then treat a specific disease But now every company does this individually So every company is trying to do the same thing and protects all the innovation inside of it Just because that's how they get to monetize it So we went at this and we asked what if we open up this thing into like an open market and there was a really interesting concept that came about in in I think late 2016 which was all curation markets It's pioneered by someone called Simon de la Ruvier, which was essentially creating initially creating markets to trade memes Like any kind of meme on the internet anyone could create a market for a meme Be it the doge meme or I don't know a Donald Trump meme or anything And then people could bet on the popularity of those memes trading tokens So we thought cool. Could we apply this for more complex situations like Scientific ideas Zonka has been talking a lot about this like could we openly fund and trade interest in scientific ideas? And we thought cool Well, we could also openly trade and fund interest in intellectual property and molecules Quite a bit more complex, but that's kind of where we're going So briefly for anyone who hasn't heard about bonding curves. I want to give a very brief Just description there. It's a new type of smart contract that can create a tokenized market around any type of thing So you give it any type of asset and what the smart contract enables is a price discovery mechanism using an algorithm If you want to ask me more about it come come to me afterwards I don't want to lose myself in the details but we can basically use this to autonomously fund and Enable price discovery for assets that were previously very illiquid So IP is a very illiquid asset like a meme is also a very illiquid asset Like what is the value of a meme? Let the people decide And what they also enable are continues financing mechanisms. So we can now autonomously finance new These types of assets based on people's interest And this was kind of born out of all the Like the problems that came with ICOs So a bonding curve really tries to go against it and provide something that is much more reasonable In some ways So the second concept that I want to introduce briefly are Crypto-cities, so thank you briefly talked about non-fundable tokens It's really cool. A lot of the great innovation in the blockchain space come through gaming and and like just Joyful experimentation So we thought cool. Well, these are like unique digital cats like pictures of cats that we attach to an unfungible token on an open network Well, couldn't we just replace the cat picture JPEG data with data of an actual piece of IP or of a scientific breakthrough? It could be a paper it could be anything So now we have two really interesting design concepts. This is kind of where token engineering gets interesting So IP is usually based on patents and proprietary data So we attach that data to a non-fundable token and then we set the owner address of that non-fundable token to a bonding curve and Boom, I mean, this is very oversimplified, but now we can trade interest and finance IP or new ideas in an open market So this is essentially and now we're lasting now these open markets can serve as prediction as prediction markets for that IP Because now what you're creating is you're creating an incentive structure for people to release positive data Because it's likely to increase the price of the IP or negative data, which is likely to decrease the price of the IP Very very simple concept and now you can you've kind of created this primitive that Incentivizes people to publish data more openly because they stand to have an economic gain from it Yeah, it's very interesting what this would do to insider trading But yeah, that's the base concept Cool. So maybe just to round it up. What are we doing in molecule at molecule? We're building an open market for for R&D and funding of intellectual property specifically in the farm industry It's really a distributed marketplace and networks that can power these new forms of R&D out in the open What does it look like it's essentially a two-sided market where IP comes in on the one side and on the other side You'd have patients academia investors and pharma that are now collectively able to invest in new drugs and to fund research around them from their earliest stages It's kind of an early screen of what this what the system looks like you basically have different types of Disease targets different type of IP that is listed on the system and then developed in an open manner You can access funding through that you can access different data that is ascribed it you can also define different different access rights We're launching our first alpha So as I kind of said in the beginning if you're long enough in this space You really want to build something and then like really start just Testing and experimenting. So we're launching pilots with three early-stage therapeutic research projects One is an air rare and orphan diseases one is in longevity and biogeontology and one is in psychedelic studies They're with the University of Johns Hopkins in the US University of Copenhagen and University of Toronto Okay Oh, yeah, I can say that Yeah, so basically what these research projects are doing they're all in basic research But there's a chance that that basic research will generate new IP and so what we're doing is for the first time We're funding the research from these institutes and it's all labs and research at those respective institutes working in those fields They essentially create a market on our system and that market now funds their research. So it's like a it's like a crowd-funded grant But the tokens that the funders receive in that project If the project is successful can be converted into real IP And we're testing this at a very small scale So the markets that we're initially launching are the fund I have funding goals between 40 to 80 thousand dollars And they're essentially like consecutive funding rounds based on how well the research is going So you go through different grants as your research progresses and Now as a researcher you have an incentive to continuously upload your data and upload your results Which for us is like a completely different is a paradigm shift to I have to if I get private grant funding The private grant funder often controls how when I publish when I release my research often also controls some of the IP And if not, then I often wait two to three years Before I actually publish my results before I get into nature or whatever I'm aiming for so this is really tries to turn that on its head because the more Continuously when you release data to your funders the more money you receive Unless your research doesn't go well within it probably shouldn't be continued to be funded Yeah, this is just a screen of what the early system looks like What essentially happens, I just explained this so the system will be on main at ethereum Beginning of this no end of this year. We're launching our first market with the University of Toronto So researchers funder stake die-in and if part of that part of that die Which is a stable current ethereum goes to the researcher a part of it stays in a reserve pool Then the researcher continuously releases project results and the funders get a stake in that project So these are two of the project examples that we're doing the first one is a high-impact clinical trial to study the effects of micro dosing So Simon and the other one is discovering interventions leading to healthy aging and longer lifespan This one's from the University of Copenhagen. They've essentially screened over a hundred different molecules They can prolong human lifespan and out of those hundred they've selected three and they're not revealing them so they're saying we have molecule X Y and Z and If you if any of these are promising they will claim IP on one of those compounds And then whoever funded that in this early stage trial receives a share in that in that IP We can talk about the legal as well ask me privately a lot of things still need to be worked out in how these early Economies can interface with our real world legal system, but I think it's a really exciting challenge to Yeah, to take that on and try to build new systems that work Yeah, just giving a shout out to block science as well. I didn't know as our government's here So we're engineering a lot of this we're trying to simulate a lot of this behavior And there's a company called block science that has built a really great Simulation tool called cad cad Where you can essentially simulate a lot of this behavior you define different parameters system parameters in our case it would be It would be the the curved slopes of the bonding curves that we use how much the return is going to be You could model things like pump-and-dump behavior So maybe you have someone that comes in and doesn't actually want to fund the project. They just want to like They just want to manipulate the market Yeah, that kind of thing Cool also little reminder at the end. There's a workshop this afternoon if you really want to go deeper into these specific topics It's called New Deals on Science. It's at 4 30 this afternoon Let by my co-founder done fronts would love to see you there And I think that workshop will be a much more open discussion. We can dive into some of these tools Explore what they do in other areas Yeah, cool. Thank you so much