A Use Case for Crypto: Decentralized Science (DeSci)
A Use Case for Crypto: Decentralized Science (DeSci)
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A Use Case for Crypto: Decentralized Science (DeSci)
In today’s piece, we’ll take a deep dive into a movement that came to light out of the recent hype cycle of crypto and has the potential to advance science and positively impact millions of people around the world — Decentralized Science, or DeSci. Together with Orpheas, a member of the DeSci community and a data platform specialist for a major crypto company, we’ll discuss some of the problems that science faces today and how the DeSci movement promises to build a world in which scientific progress is a collaborative and transparent process.
Let’s get to it!
Actionable Insights
If you only have a couple of minutes to spare, here’s what you should know about Decentralized Science (DeSci).
Science faces systemic and institutional-level issues that hinder breakthrough innovation
It struggles with broken models of funding, cost, and delays from academic journals, lack of transparency, lack of financial rewards for scientists, and irreproducible results
A movement came to light out of the recent hype cycle of crypto with the aim to improve science and redefine how: 1) research is funded 2) knowledge is shared 3) ownership is distributed. It’s called Decentralized Science (DeSci)
DeSci leverages blockchain tech and tools as a means of advancing Open Science — to build a world in which scientific progress is a collaborative and transparent process
Existing efforts range from purely theoretical ideas and small-scale experiments to more established players, funding academic research, and developing the required infrastructure
It’s still day one for DeSci and there are lots of unknowns and a number of challenges to navigate before we consider this a pillar of scientific progress
The hype cycle of crypto
Crypto experienced one of its biggest bull runs in 2021, but the market crash that began at the start of this year and intensified over the past months has extinguished some of the hype, with people looking to separate the wheat from the chaff and figure out where crypto can truly add value.
The monthly volume of NFT marketplaces has plummeted, the Total Value Locked (TVL) in DeFi is down 65% from its November peak of $107 billion, and the “have fun staying poor” and “ngmi” crowd is quiet. This is not the first time crypto experiences a boom and bust cycle. We have seen several Price-Innovation Cycles in the past, where in every cycle, even after prices have dropped, more developers and startups remain in the industry than there were before the cycle began. This sets the foundation for new use cases to emerge and a new cycle to kick in. Think of it as a recurring hype cycle. A technological breakthrough occurs, people believe it’s going to change everything, they realize that it’s not going to change everything, and then they figure out the things it will actually change. The question now is: which use cases coming out of crypto are truly valuable and superior to how we already do things?
Science beyond borders
Such a use case is a movement that saw a meteoric rise during the recent cycle and has the potential to impact millions of lives — Decentralized Science (DeSci). Taking its cue from the Open Science movement and the idea that science should be transparent and accessible to all, scientists and builders around the world want to leverage the blockchain to advance modern science by redefining, amongst others, how: 1) research is funded, 2) knowledge is shared, and 3) ownership is distributed.
DeSci is still in its infancy and existing efforts range from purely theoretical ideas and small-scale experiments to more established players funding research and developing the required infrastructure.
But what problems is DeSci specifically attempting to solve?
Science could be better
For humanity’s continuing and sustained flourishing, we need science. Science is the means through which we can better fulfill the world’s needs for energy, food, shelter, and safety; it is how we understand and cure diseases, and it is how we can live longer and healthier lives. In that sense, science and scientific knowledge are a public good. However, what we are seeing is a capital S “Science” that is often treated as a "factory for producing knowledge". One that is a primarily industrial enterprise, with a linear, centralized hierarchy of authority and power, one that frequently produces perverse incentives. This centralization reinforces current scientific paradigms, going against Thomas Kuhn’s postulation that scientific revolutions often come from outside the system and existing scientific dogmas. As a result, despite increasing amounts of capital being poured into research, returns are diminishing, and the rate of scientific progress is arguably slowing down.
Now — let’s dive a bit deeper into the specifics of what’s wrong with our current model of science:
Academic Publishers & Journals
For most scientists, their ultimate goal is to get published. Getting published is seen as one of the primary means of contributing to the advancement of scientific knowledge and to sharing findings with the scientific community. Scientific journals, in particular peer-reviewed ones, function as validators and legitimizers of one’s research. The problem is not the process of publication per se, but rather the fact that more than half of academic journals — with these journals also accounting for a big share of citations — is controlled by an oligopoly of publishers, with said publishers effectively acting as gatekeepers. Academic publishers and journals are for profit, so research articles essentially become an opportunity to extract as much value as possible. Scientists are required to pay large amounts to get published, even though they are effectively the ones producing most of the value. And if a scientist wants to publish their research in an Open Access journal, they have to pay an additional fee.
Value extraction does not end there — academic institutions and libraries have to pay exorbitant amounts, ranging from a few hundred thousand to millions, for access to published papers.
Capital Allocation
It is easy to forget that scientific research does not happen in a vacuum; funding is necessary for scientists to be able to pay for supplies and equipment, access computational resources, lease or purchase research facilities, hire specialists, and other activities related to the research process. Under the current model of scientific funding, capital is allocated via grants from public (state or local governments) or private (private benefactors, corporations, and industry in general) sources. Under the grant model, researchers develop funding proposals, which often demand them to go into explicit detail about how the research will be conducted and what the expected results of their research will be. Proposals are then evaluated by panels/committees based on their clarity, specificity, and feasibility. One can imagine how the push for scientists to know exactly what to expect from their research, severely limits what research is conducted, pushing scientific research to chase safe, certain results, and incrementalism. Not to mention the overhead involved, with researchers spending about 40% of their time chasing after funding, either directly (writing grant proposals) or indirectly (visiting companies, giving talks, building relationships).
As if that was not enough, narrow evaluating panels of limited size, especially during times when available capital is limited, are naturally susceptible to biases and decisions driven by self-interest, often limiting research to a certain number of areas within the current scientific dogma, once again favoring “safer” research that can function as additive to current scientific knowledge, over more ambitious projects which might not be able to guarantee any positive outcome. One such example is longevity research, as it breaks the current paradigm of disease-oriented research, while also having no endpoint to measure against, other than death.
This incentive to only publish positive results ends up hindering transparency of the scientific process, often leading scientists to re-conduct experiments that might have previously failed, experiments which they have no way of knowing about. The pressure for positive results also plays a part in the replication crisis many scientific fields are facing, by incentivizing researchers to favorably interpret their own results.
Lack of transparency
Despite its central role when it comes to evaluating the quality of research, the peer review process severely lacks transparency. Typically, journals don't publish specific evaluation criteria, or the identities of peer reviewers, so that they can avoid any potential conflict-of-interest breaches (or even discrimination).
To add to that, scientists are often not required to disclose the raw data accompanying their research, or how their data is analyzed. This makes it difficult for readers to independently verify and potentially replicate the findings of a research, effectively fully outsourcing research quality to journals, publishers, and opaque review processes. This is proving, time and time again, to have serious consequences, not just for scientists but for everyone who relies on scientific findings to inform their decision-making. Just recently, a key theory on Alzheimer’s disease was found to be based on fabricated data.
Additionally, grant allocation decisions are made with limited transparency, which means that decision-makers are less accountable for their actions and that scientists have limited lines of communication about decisions that may detrimentally affect them. Moreover, as science becomes increasingly a topic of public discussion, the biases of allocators may often trump evidence in decision-making.
Lack of financial incentives
There’s little financial windfall for scientists — so much brain power goes into, for example, sports betting because there is a financial incentive. Imagine if financial incentives really existed in science
— Patrick Joyce, Co-founder of ResearchHub
With such little financial reward involved in conducting scientific research —and such lofty expectations from society for science itself — it’s no wonder there are so many people entering industries with, arguably, inconsequential effects on human progress and flourishing.
Sure, in principle, the vast majority of scientists may not be driven by the need for financial gain. However, that is not a good enough reason to not reward them for their contributions.
It’s not just that researchers often have to “beg” for funding, or that they have to pay for their research to get published — even when they produce novel research and inventions, scientists frequently do not even own the intellectual property (IP) to their work. IP tends to be owned by the institution(s) researchers are affiliated with, thus robbing them of both credit, as well as from being able to generate financial capital via the monetization or trading of IP.
It is also worth pointing out that the lack of financial incentives not only impacts scientists, but patients, downstream, too. This is especially the case with generic and off-patent drugs that may have the potential to significantly decrease disease burden by being repurposed — unfortunately, the high costs of running clinical trials to prove efficacy, combined with the lack of potential returns to pharmaceutical companies, means many of these drugs never gain the necessary approvals for widespread public use.
Collaboration
Despite science essentially being a collaborative effort, our current model frequently makes collaboration between scientists and researchers harder. All the aforementioned — centralized funding, paywalls, IP limitations — play their part. The competitive grant funding environment frequently leads scientists to limit collaborations and withhold information that could potentially be used by other researchers when pursuing funding. Additionally, the lack of a mechanism to immutably and transparently track contributions often creates issues and contentions when it comes to crediting contributors on a paper; it should thus come as no surprise that researchers can end up avoiding collaborations outside of their immediate networks, for fear of their work going uncredited.
These are of course not the only blockers to scientific collaboration. Often, researchers’ exclusive attachments to their home institutions, as well as limitations placed by grant allocators, tend to have restrictive effects, while the sharing of scientific resources (datasets, laboratory equipment, etc.) also tends to be slow, cumbersome, and mired with bureaucracy.
Beyond the hype: The promise of DeSci
Science is essential for human progress. Decentralized science is a way to make science more open and frictionless, from publishing to funding. This will enable more scientific progress by allowing for more people to participate in the scientific process.
— Vincent Weisser, Product lead at Molecule and VitaDAO
Utilizing crypto’s capacity for transparency, verifiability, and the financialization of on-chain assets, the goal of DeSci is to catalyze an open and decentralized system capable of fostering global collaboration and innovation. While the DeSci movement is still nascent, there are players in the space that are already creating real-world value, providing funding, and building decentralized infrastructure to support scientific research and collaboration and solve the problems plaguing the way science works today.
Here are some of the most important ones and the problems they are trying to address:
Molecule Protocol
Addressing: Capital Allocation, Lack of Transparency, Collaboration
Molecule, which recently raised a $12.7m seed round and is one of the earliest entrants in the space, has developed a marketplace specifically for discovering, funding, and collaborating on early-stage biopharma research projects. Molecule is also the creator of the IP-NFT. A patent token or a digital asset whose holder can prove ownership of a certain patent. With that, IPs can become financialised — held by scientific communities, transferred, borrowed against, and sold on NFT marketplaces, in an attempt to build self-sustaining scientific ecosystems and bring value back to those that produce it.
In addition, Molecule also functions as a biopharma DAO incubator. One of those DAOs, VitaDAO, completed the first IP-NFT transaction, receiving the IP rights to findings arising out of a University of Copenhagen study, regarding the potential repurposing of drugs to support longevity. In return for receiving the research’s IP rights, it will provide $500,000 of total funding for the study.
VitaDAO
Addressing: Capital Allocation, Lack of financial rewards
VitaDAO, one of Molecule’s incubated DAOs, is a community focused on accelerating R&D in the longevity space, where IP rights are notoriously exclusive and siloed. People can join the community by acquiring, or completing bounties to earn VITA, VitaDAO’s native token. VITA holders can then vote on proposals for community governance, as well as for funding longevity research proposals. In a year, apart from funding the aforementioned University of Copenhagen study in return for IP rights, the DAO has funded more than 10 projects, from a feasibility study on the pay-for-success model for biopharma, to reversing the periodontal disease in the elderly, having deployed a total of $2.5m. A full list of governance and funding proposals can be found here.
Additionally, VitaDAO has launched the Longevity Prize in collaboration with Foresight Institute and the Methuselah Foundation, and is funded through Gitcoin contributors and Vitalik Buterin, amongst others. Through the Longevity Prize, VitaDAO posts longevity research bounties that researchers can work on and receive monetary compensation for. VitaDAO is also running its own Fellowship, funding people with need-based grants, in order to help them get more involved in the longevity space.
ResearchHub
Addressing: Publishing, Collaboration
ResearchHub, co-founded by scientist Patrick Joyce and the co-founder of Coinbase, Brian Armstrong, is a platform which allows people to collaborate on scientific research in an efficient way, similar to what GitHub has done for software engineering. Users can upload articles, summarize their work, and discuss and build on top of others’ findings. ResearchCoin (RSC) is ResearchHub’s native token, which is used both as a reward mechanism for users contributing to the platform, as well as a reputation mechanism to indicate the quality of contributions from users. ResearchHub runs its own virtual conference, SciCon, giving the stage to various contributors across the DeSci and Open Science movements.
Ocean Protocol
Addressing: Lack of Transparency, Lack of financial rewards, Collaboration
Ocean Protocol has developed a data marketplace where datasets are tokenized, allowing users to publish, share, sell, and even stake datasets. Users can also set bounties for analysts and data scientists to conduct analyses and develop models on their datasets, while data itself can remain private via Ocean Protocol’s Compute-to-Data feature.
DeSci Labs
Addressing: Publishing, Lack of Transparency, Lack of financial rewards, Collaboration
DeSci Labs is developing infrastructure to support the decentralization of science. Their Nodes product, which is currently in alpha testing, is a decentralized ledger designed to store scientific articles for generations; a repository of scientific findings that cannot be censored, altered or destroyed. Manuscripts stored on a node, are directly connected to the data and the code used to produce manuscript articles, so that readers and other scientists can freely attempt to replicate findings. Manuscripts also can be annotated, forked, and iterated upon, while scientists can also provide rewards for other scientists conducting peer-reviews on their articles. At the same time, Open Science badges are conferred to each manuscript, to certify open science practices. Nodes is estimated to go into beta testing in September 2022.
LabDAO
Addressing: Collaboration
LabDAO is building a decentralized, peer-to-peer network of wet and dry labs, allowing scientists and researchers to access underutilized laboratory resources, driving down the cost of life science research. The platform is at the pre-launch stage, initially starting out with what they call “web labs”, focusing on access to computational resources. Also worth noting — LabDAO co-authored a recently published paper on a “Python library for automated retrieval of scientific literature”, marking one of the first times a DAO is listed as a co-author of an academic paper.
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These are some of the few that are already creating value in the space — lots more in the process of starting up and development, including working on funding for psychedelics, distributed compute, patient-driven trials and experiments, personal data economies, among others.
It’s still day one for DeSci
Emerging from the previous crypto hype cycle, the Decentralized Science movement has the potential to impact millions of lives. Still, there remain many unknowns and challenges to navigate. How do we make sure we don’t end up developing a speculative bubble for scientific projects? Can the space attract builders that want to push the goals of Open Science forward and create real-world impact vs. people who just follow the hype? How do we introduce new incentive mechanisms within the scientific community without replicating the same problems science currently faces? It was humans who built the existing mechanisms after all. What makes things different now?
Science is the foundation of knowledge and progress. As an essential public good, science needs to be reliable, transparent, independent, and openly accessible. And DeSci enters the race for scientific progress with a promise for a transparent and self-governing system, one that will fund breakthrough research that will accelerate our understanding of disease and the therapies that come with it. Is this going to be a use case coming out of crypto that’s superior to how we already do things and justifies the hype and the billions of dollars pouring into the space? Time will tell.
A huge thank you to Spyridon Antonopoulos, Rik Smith-Unna, Dr. Jocelynn Pearl, Vincent Weisser and Esha Bora for their suggestions, input, and help.
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Thanks for reading,
Alex