Binance Research: From Challenges to Opportunities, How Can DeSci Reimagine Science?
TechFlow Selected TechFlow Selected
Binance Research: From Challenges to Opportunities, How Can DeSci Reimagine Science?
DeSci has matured enough to influence the way scientific research is conducted today.
Navigating Web3 tides with focused insightsAuthor: Will Awang
Since ancient times, emperors, nobles, and officials have harbored endless aspirations for immortality, and this remains true today. This pursuit of life extension and exploration at the scientific frontier has taken on new directions with the support of blockchain technology. The rise of decentralized science (DeSci) offers fresh hope and possibilities for advancing scientific discovery.
What first drew my attention to DeSci was Pfizer’s investment in VitaDAO—an inaugural move by Pfizer into the Web3 space, signaling recognition and support from a traditional pharmaceutical giant toward the DeSci field. Given my background in digital health entrepreneurship, this naturally led me to consider how business models could be reimagined through DeSci.
Binance Research's DeSci report titled "From Challenges to Opportunities: How DeSci Reimagines Science" initially highlights the phenomenon known as the "Valley of Death" in scientific research, then introduces DeSci as an innovative solution to overcome it, and finally summarizes the current landscape of DeSci, asserting that DeSci is already mature enough to influence how scientific research is conducted today. While there are still gaps and challenges in the current environment, addressing the "Valley of Death" in research represents a significant step forward.
Following the logic of the report, throughout the entire process of transforming research into commercialization, DeSci can integrate even more deeply with blockchain technology and Web3. Let us take medical R&D as an example:
-
Data acquisition: Early-stage basic and translational research data can be gathered via DePIN, further enhanced using AI. The benefit lies in achieving global coverage while providing incentives;
-
Data storage: Such data can be encrypted and stored on-chain, ensuring immutability and security, while establishing a new form of open, universally accessible publication—partially resolving issues of replicability and reproducibility in scientific discoveries;
-
Community of shared interests: Through rules established by DAOs, a shared interest ecosystem between basic research and clinical practice can be realized. These mechanisms can extend further across research, clinical application, commercialization, and patient-care scenarios, enabling win-win outcomes among multiple parties;
The future envisioned for DeSci consists of decentralized organizations (DAOs) formed by diverse stakeholders united by common goals and visions, no longer driven solely by capital profits, deeply integrating blockchain technology and Web3 to accelerate scientific discovery and bring tangible products to market, thereby driving societal advancement.
Although DeSci is still in its very early stages, it is already actively influencing how scientific research is conducted today.
Below is the full content of From Challenges to Opportunities: How DeSci Reimagines Science. Enjoy:
01 Key Takeaways
-
The scientific research process faces major challenges, particularly in translational research—the transition from basic research to practical applications. The "Valley of Death" phenomenon causes 80%-90% of research projects to fail before human trials, with only 0.1% of candidate drugs becoming approved therapies.
-
Inconsistent incentives among academia, funding agencies, and industry lead to insufficient R&D funding, reduced collaboration between scientists and clinicians, and poor replicability and reproducibility of scientific findings, ultimately causing most research to stall in the "Valley of Death".
-
Decentralized Science (DeSci) is a movement leveraging the Web3 stack to create innovative models for scientific research capable of overcoming these challenges.
-
By utilizing decentralized autonomous organizations (DAOs), blockchains, and smart contracts, DeSci addresses key coordination problems, enabling different stakeholder groups to align their financial interests and incentivize progression of research into clinical phases.
-
The market has now clearly identified four key innovation areas within the DeSci domain:
-
Infrastructure—including sub-sectors such as funding platforms and DAO tools—that forms the foundation of DeSci DAOs.
-
Research—including grassroots DeSci communities hosting global events and vision-aligned DAOs representing multiple stakeholders.
-
Data services—including publishing and peer-review platforms that support open-access scientific publications, as well as data management tools offering strong data integrity and collaborative access control.
-
Memes—that directly fund scientific experiments or serve as investment vehicles for other DeSci projects.
-
While the existing stack supports basic and translational research, it is less suited for clinical research—the stage where products deliver direct benefits to patients.
-
In summary, decentralized science is already mature enough to influence how scientific research is conducted today. Despite current gaps and challenges, solving the "Valley of Death" in research marks a significant step forward.
02 Introduction
2.1 Background of Traditional Scientific Research
The process by which the scientific industry generates new knowledge and inventions can be divided into distinct stages, primarily categorized into basic research and clinical research. These two main phases are connected through translational research. The key function of translational research is to transform the outcomes of basic research into practical applications testable through clinical studies. The ultimate goal of this process is to commercialize research findings and develop products that benefit society.
(Figure 1: The "Valley of Death" is the phase where most research fails between basic and clinical science)
However, the biggest challenge in this process is the "Valley of Death" phenomenon, where many scientific efforts fail due to ineffective translational research.
According to data from the National Institutes of Health (NIH), 80% to 90% of research projects fail before entering human trials. Moreover, over 1,000 candidate drugs are developed for every single drug approved by the FDA. Even in later stages, challenges persist—nearly 50% of experimental drugs fail during Phase III clinical trials. From this perspective, the probability of a new drug candidate progressing from preclinical research to FDA approval is merely 0.1%. These staggering statistics highlight the immense difficulty in translating knowledge and innovations developed in universities and research institutions into real-world products or treatments for humans.
(Figure 2: The number of approved new molecules per $1 billion in global R&D spending has been declining)
These challenges are exacerbated by increasingly inefficient R&D processes in drug development. In the U.S., the cost of developing and approving a new drug doubles approximately every nine years—a phenomenon known as Eroom’s Law, the inverse of Moore’s Law. Contributing factors may include stricter regulatory standards, high thresholds for novel medical discoveries to meet unmet needs distinct from existing drugs, and the high costs of contract research organizations responsible for designing and running clinical trials. If this trend continues, the biopharmaceutical industry could face drug development costs as high as $16 billion by 2043. This financial burden often leads the industry to focus on developing higher-profit drugs, overshadowing urgent but less profitable health needs.
This inefficiency leads to significant economic and social consequences. High R&D costs combined with frequent failures drive up healthcare expenses, ultimately borne by patients, governments, and insurers. Additionally, delays and failures in translating research into viable therapies mean patients often miss out on potentially life-saving opportunities, worsening public health challenges. For instance, rare diseases affecting smaller populations are often neglected because they are considered less profitable, despite urgent treatment needs.
2.2 Why Most Research Fails to Escape the "Valley of Death"
The root problem lies in misaligned incentives, resulting in three major challenges: funding shortages, reduced collaboration between researchers and clinicians, and poor replicability and reproducibility of scientific findings. These challenges ultimately cause research to stall in the "Valley of Death".
We will explore these primary challenges in greater detail below:
2.2.1 Lack of Funding
Funding shortages, especially when transitioning from basic to clinical research, stem from misaligned incentives between funders and researchers, as well as a lack of transparency in grant review processes.
From funders’ perspectives, priority is given to research that can be transformed into products generating recurring revenue. This creates a ripple effect: considering the competitiveness of securing funding, researchers tend to work according to funders’ expectations, making research more conservative and effectively stifling innovation.
Furthermore, opaque review processes mean a single proposal submitted to different panels might yield varying results. When grant review panelists receive no compensation, additional complications may arise—such as bias from competing researchers, insufficient attention to detail, and severe delays in grant approvals. As a result, researchers tend to spend more time publishing papers to build reputations within the scientific community rather than conducting experiments.
2.2.2 Reduced Collaboration Between Researchers and Clinicians
Given that most research stalls in the "Valley of Death", coordination between basic researchers and clinicians during translational research is crucial.
Effective collaboration fosters the design of innovative clinical trials integrating biomarkers or targeted approaches from basic research. For example, oncology has made significant progress through collaboration, where genetic and molecular discoveries from labs directly inform targeted therapies and trial designs for specific cancer subtypes. This synergy reduces the risk of late-stage trial failures and increases the likelihood of delivering effective treatments to patients.
However, basic scientists (focused on discovery) and clinicians (focused on patient care and clinical research) currently have little incentive to collaborate. Advancement in basic science typically depends on the number of funded grants and publications in top-tier journals, not contributions to clinical science or medical advancements. Conversely, many clinicians measure success by the number of patients treated, leaving them with little time or motivation to conduct research or pursue funding opportunities.
As a result, these two groups operate in silos, reducing the chances of combining laboratory discoveries with clinical relevance.
2.2.3 Low Replicability and Reproducibility of Scientific Findings
Reproducibility refers to the ability to obtain consistent results using the same data, methods, and computational steps as the original study. On the other hand, replicability involves conducting a new study to arrive at the same prior scientific finding. Without reproducibility and replicability, it becomes difficult to validate the validity and credibility of basic research, hindering its expansion into clinical applications.
The challenge of translating animal studies to human research leads to inefficiencies—reportedly, only 6% of animal studies translate to human responses. Other issues, such as methodological differences (e.g., coating types in test tubes, cell growth temperature, stirring methods in culture), may also lead to completely irreproducible results.
While the scale of the issue largely stems from scientific complexity, misaligned incentives between publishers and early-career researchers also contribute to the lack of reproducibility and replicability. Publishers play a critical role in nurturing early researchers, as published works enhance credibility and increase chances of securing funding. Consequently, researchers who achieve statistically significant results on their first attempt are less inclined to repeat experiments and instead proceed directly to publication.
03 Decentralized Science 101
3.1 What is DeSci?
Decentralized Science ("DeSci") is a movement leveraging the Web3 stack to create new models for scientific research.
Blockchain offers unique advantages in addressing the aforementioned challenges. It provides a trustless way to coordinate funding, while ensuring transparent and immutable tracking and recording, allowing all stakeholders' interests to be considered.
DeSci is still in its infancy within the crypto industry. This is evident from its total market cap just exceeding $1.75 billion and only 57 projects tracked under the DeSci category on CoinGecko. For comparison, DeFAI (Defi x AI Agent) hosts only 41 projects yet reaches a $2.7 billion market cap, while broader Crypto AI stands at $47 billion (as of January 15, 2025).
3.2 How DeSci Addresses the "Valley of Death"
As previously noted, most research fails in the "Valley of Death" due to misaligned incentives leading to funding shortages, reduced collaboration, and poor replicability and reproducibility. DeSci can address these coordination issues using decentralized autonomous organizations (DAOs), blockchains, and smart contracts.
Below, Binance Research summarizes how DeSci provides solutions to existing challenges, first presented in table format for clarity, followed by detailed explanations. As a movement, DeSci tackles these challenges by:
3.2.1 How DeSci Solves Funding Shortages
DAOs can act as capital formation tools for research funding, with participants comprising a mix of patients, researchers, and investor communities. Since stakeholders share a common goal—to advance research into clinical stages and eventually commercialize it—they have aligned motivations to help research cross the "Valley of Death".
Decisions are made through decentralized token-based governance, enabling transparent and democratic voting. Smart contracts then execute parameters decided by the DAO, ensuring transparency. Examples include milestone-based funding disbursed programmatically, tokenization of intellectual property (IP) generated from funded research, fractionalizing IP ownership, and distributing it among all DAO participants to align interests.
Overall, DAOs in the DeSci space can coordinate various stakeholders in a trustless manner, collaborating toward a shared objective, thus offering an integrated end-to-end approach from basic to clinical research.
3.2.2 How DeSci Solves Reduced Collaboration Between Researchers and Clinicians
As mentioned earlier, differing incentives are the primary reason for reduced collaboration. This can be addressed through DAO participation, where research hypotheses, experimental methods, and parameters can be agreed upon during DAO formation, aligning research outcomes. Combined with IP tokenization, both researchers and clinicians receive sufficient incentives and rewards to push research into clinical stages.
Other tools promoting greater collaboration include platforms incentivizing peer review, where rewards can be programmatically distributed via smart contracts upon successful review. This brings clinicians closer to researchers, allowing early input that can guide research toward practical implementation in clinical settings. Additionally, an on-chain reputation system can be built around members of the scientific community based on their contributions to various DeSci DAOs, peer-review activities, clinical implementations, etc., ensuring proper attribution for any work contributing to scientific advancement.
3.2.3 How DeSci Addresses Low Replicability and Reproducibility
One approach to solving this issue is recording research methodologies, experimental designs, and every step on the blockchain. As an immutable ledger, blockchain ensures other researchers can fully understand the experiments conducted and query each variable if attempting to replicate them.
Additionally, Web3 primitives can enable a new form of open, universally accessible publishing where all research—even failed studies—can be shared. This eliminates publication bias, where only successful experiments get published, since data from failed experiments still holds value.
Another area where DeSci can help is data integrity and compliance. While traditional archival storage meets this need, it often relies on tapes, making data retrieval slow. Given the dynamic nature of scientific research involving multiple parties processing the same data while maintaining immutability and security, decentralized storage and data warehouses offer a solution. They provide necessary data access control, greater redundancy by eliminating single points of failure, and fast data retrieval for collaborative work. This promotes more rigorous scientific research and increases the likelihood of reproducible and replicable results.
04 Overview of the DeSci Landscape
4.1 Key Innovation Areas
Binance Research has identified four key innovation areas in the DeSci landscape: Infrastructure, Research, Data Services, and Memes.
Infrastructure includes sub-sectors such as funding platforms and DAO tools (e.g., IP tokenization, DAO formation, legal agreements). These form the foundation of DeSci DAOs, which sit at the forefront of scientific discovery.
Research includes grassroots communities like DeSci Global and DeSci Collective, which host global events to connect DeSci enthusiasts, as well as DAOs that unify shared interests from multiple stakeholders. These DAOs often focus on different scientific fields such as longevity, hair loss, women’s health, etc.
Data Services include publishing and peer-review platforms that promote open access to scientific publications, fostering greater collaboration, along with data management tools offering robust data integrity and appropriate access control.
Memes represent retail investor interest, bringing greater awareness and education to the DeSci space, which is often confined to academic circles. Some memecoins directly fund scientific experiments, while others serve as investment vehicles for other DeSci projects.
4.2 Sub-Sectors to Watch
A. Infrastructure: IP Tokenization / Fractionalization
IP tokenization plays a transformative role in advancing translational science by addressing a fundamental barrier in research and innovation—monetization and liquidity of intellectual property (IP).
Traditional IP management and trading systems are cumbersome, centralized, and often inaccessible to smaller stakeholders, limiting the speed at which discoveries are commercialized and translated into real-world applications. By leveraging blockchain technology, IP tokenization creates a decentralized and transparent framework enabling researchers, investors, and other stakeholders to participate in and fund innovation more efficiently.
IP tokenization involves converting intellectual property into digital assets, making them tradable and liquid. Projects like Molecule exemplify this process by introducing concepts such as IP-NFTs (Intellectual Property Non-Fungible Tokens) and Intellectual Property Tokens (IPT). IP-NFTs bring IP onto the blockchain, while fractionalization allows multiple stakeholders to co-own and manage IP. The desired outcome is coordinated stakeholders ensuring sufficient funding to advance research into clinical stages and eventual commercialization.
B. Infrastructure: DAO Formation
DAO infrastructure represents a key innovation in scientific decentralization, enabling communities of patients, scientists, and biotech professionals to jointly fund, manage, and own scientific projects. Traditional scientific funding is often constrained by centralized institutions, rigid gatekeeping, and opaque processes. DAO infrastructure disrupts this model by offering a transparent, decentralized framework for planning, funding, and governing scientific initiatives.
Through DAOs, stakeholders can pool resources, make collective decisions, and directly influence the trajectory of scientific research. BIO Protocol is one example, supporting the creation, funding, and governance of BioDAOs. Each BioDAO has its own specialization, focusing on different scientific domains such as longevity (VitaDAO), cryopreservation (CryoDAO), hair loss (HairDAO), women’s health (AthenaDAO), etc.
C. Infrastructure: Funding Platforms
Web3 funding platforms are transforming scientific research financing by decentralizing processes and enabling broader participation. Traditional research funding typically relies on grants and institutional support, which can be slow, bureaucratic, and limited in scope. Through crowdfunding, researchers gain direct access to funders, communities, and collaborators, fostering a more transparent and inclusive funding ecosystem.
These funding platforms may also differ in their beneficiaries. For example, Catalyst (aimed at funding DeSci IPs), Bio.xyz Launchpad (designed to fund DeSci DAOs), and pump.science (focused on funding compound testing).
Web3 composability enables different crowdfunding platforms to coordinate stakeholders across research stages, facilitating a seamless funding ecosystem. For instance, a DeSci DAO funded via Bio.xyz could organize capital through Catalyst for a specific IP research project, or use pump.science to transparently test and validate compounds.
D. Data Services: Publishing / Peer Review Platforms
The traditional model of scientific publishing is often slow, expensive, and inaccessible, with high article processing charges (APCs) and limited transparency in peer review. Moreover, researchers rarely receive credit or compensation for their contributions to the peer review process. This slows down the review pace and increases the possibility of bias due to conflicts of interest. Overall, it hinders the speed of scientific advancement and restricts broader access to knowledge.
Incentivized publishing and peer-review platforms aim to resolve these issues by creating open, transparent systems where researchers are rewarded for their contributions—including publishing, reviewing, and collaborating. By integrating blockchain technology and community governance, these platforms democratize access to scientific knowledge, accelerate dissemination, and foster collaboration among global researchers. ResearchHub is one example, where researchers earn token rewards for peer-reviewing articles or collaborating with like-minded individuals in their fields of interest. Positive contributions to the scientific community can be recorded on-chain, building reputations for scientists and unlocking features such as moderation and access control.
This is also an interesting intersection with artificial intelligence. Projects like yesnoerror have launched—an AI agent using OpenAI to detect mathematical errors. It can identify math mistakes, spot fabricated data, and detect numerical inconsistencies that could undermine scientific integrity at scale, all with minimal downtime.
E. Data Services: Data Interoperability and Integrity
The healthcare and biomedical research industries suffer from fragmented data systems, lack of transparency, and absence of patient-centric practices. Patients frequently donate valuable data and biosamples for research but have little understanding or control over how their contributions are used, and rarely benefit from the resulting scientific or commercial value. These gaps lead to distrust, privacy breaches, and reduced engagement, especially within marginalized and underrepresented communities.
Data interoperability and integrity aim to solve these issues by creating systems that grant patients transparency, control, and shared benefits, while enabling seamless collaboration among researchers, institutions, and enterprises. Interoperability systems allow integration of disparate data sources, making them usable across networks while protecting data privacy and integrity. This ultimately accelerates scientific discovery, streamlines clinical R&D, and builds trust in biomedical research.
AminoChain is one example—a decentralized platform designed to connect healthcare institutions and support user-owned healthcare applications. It empowers patients to control their own data and samples, ensures transparency in data usage, and enables them to share in the value generated from research. Other decentralized data solutions include Filecoin, Arweave, Space and Time, where data is securely stored without single points of failure, while offering flexible access control to ensure proper data handling.
05 Final Thoughts
We are in the early stages of DeSci, and this decentralized approach to science will become increasingly prominent in how science is conducted today. DeSci has the potential to coordinate stakeholders from the earliest stages of research, ensuring sufficient momentum to advance research into clinical phases.
The infrastructure for coordinating research in a decentralized manner already exists. Aligned stakeholders can formalize their shared interests in scientific research through DAOs, provide funding, conduct research, own resulting intellectual property, and securely share data within data protection guidelines to strengthen collaboration across scientific communities.
However, the existing stack is better suited for basic and translational research than for clinical research. The former stage requires more trustless coordination, whereas the latter demands coordination with centralized entities such as regulators, pharmaceutical companies, and physical laboratories.
Moreover, the legal status of DAOs remains an ongoing debate and area of regulatory development. In the Ooki DAO case, the U.S. District Court for the Northern District of California ruled that Ooki DAO qualifies as a "person" under the Commodity Exchange Act, setting a precedent that DAOs can bear legal liability. This decision significantly impacts DAO members, indicating that token holders participating in governance may be personally liable for the DAO’s actions. Given the lack of clarity in DAO regulation, this could deter potential funders.
In summary, DeSci is already mature enough to influence how scientific research is conducted today. While there are still gaps and challenges in the current environment, solving the "Valley of Death" in research represents a significant step forward.
Join TechFlow official community to stay tuned
Telegram:https://t.me/TechFlowDaily
X (Twitter):https://x.com/TechFlowPost
X (Twitter) EN:https://x.com/BlockFlow_News
0xWillmfer
