Binance Research: From Challenge to Opportunity, How Did DeSci Reimagine Science?

Original Article Title: From Challenges to Opportunities: How DeSci Reimagines Science
Original Source: Binance Research

Original Article Compilation, Translation: Will Awang

Since ancient times, emperors and generals have all harbored endless desires for immortality, and today is no exception. This pursuit of life extension and cutting-edge science has taken on a new direction with the help of blockchain technology. The rise of Decentralized Science (DeSci) has provided new hope and possibilities for the exploration of scientific frontiers.

What first caught my attention about DeSci was Pfizer's investment in VitaDAO, which not only marked Pfizer's first investment in the Web3 space but also signaled the traditional pharmaceutical giant's recognition and support for the DeSci field. Combining this with my own background in digital healthcare entrepreneurship led me to contemplate how to rethink business models through DeSci.

In the DeSci research report published by Binance Research titled "From Challenges to Opportunities: How DeSci Reimagines Science," the phenomenon of the "Valley of Death" in the scientific research process is first introduced. Subsequently, DeSci is brought up to address the "Valley of Death" through innovative solutions, and finally, the current landscape of DeSci in the market is summarized, indicating that DeSci is mature enough to influence the way scientific research is conducted today. While there are still some gaps and challenges in the current situation, overcoming the "Valley of Death" in research is a significant step forward.

Following the logic of the research report, in the entire process of transforming scientific research into commercialization, DeSci can further integrate with blockchain technology and Web3. Take medical research and development as an example:

· Data Acquisition: Data from early-stage basic research and translational research can be obtained through DePIN and further strengthened with AI, covering a global scale and providing incentives;

· Data Storage: This data can be stored on-chain using encryption technology to maintain data integrity and security, while also creating a new form of open and universally accessible publication, to some extent addressing the reproducibility and replicability issues of scientific discoveries;

· Community of Interests: Through rules set by DAO organizations, an ecosystem of shared interests between basic research and clinical treatment can be established, and these rules can be further expanded to cover the entire research, clinical, commercialization, doctor-patient scenarios, achieving a win-win situation for all parties involved;

The future envisioned by DeSci will be: a decentralized autonomous organization (DAO) composed of a multi-stakeholder community with a common goal and vision, no longer driven by capital profit, deeply integrating blockchain technology and Web3, promoting scientific discovery, accelerating the implementation of tangible products, and advancing the development of society as a whole.

Although DeSci is still in a very early stage, it is actively influencing the way scientific research is conducted today.

Below is the content of From Challenges to Opportunities: How DeSci Reimagines Science, Enjoy:

01 Core Insights

· The scientific research process faces significant challenges, especially in the translation of basic research into practical applications. The "Valley of Death" phenomenon results in 80%-90% of research projects failing before human trials, with only 0.1% of candidate drugs becoming approved treatments.

· The incentive mechanisms among academia, funding institutions, and industry are inconsistent, resulting in insufficient R&D funding, reduced collaboration between scientists and clinicians, and challenges such as the reproducibility and replicability of scientific discoveries, ultimately causing most research to stagnate in the "Valley of Death."

· Decentralized Science (DeSci) is a movement to create an innovative scientific research model using the Web3 stack to address the aforementioned challenges.

· By using Decentralized Autonomous Organizations (DAOs), blockchain, and smart contracts, DeSci can address key coordination issues. This enables different stakeholder groups to align their interests, incentivizing them to advance research to the clinical stage.

· The market has already identified four key innovation areas in the DeSci field:

- Infrastructure, including funding platforms and DAO tools among sub-industries, forming the foundation of the DeSci DAO.

- Research, including a grassroots DeSci community hosting global events and a DAO with a consistent vision from multiple stakeholders.

- Data services, including publishing and peer-review platforms. These platforms support open-access scientific publications and data management tools that provide robust data integrity and collaborative access control.

- Memes, providing direct funding for scientific experiments or serving as an investment tool for other DeSci projects.

· While the existing stack can already support basic research and translational research, it is less suitable for clinical research, which is the field where a product directly benefits patients.

· In summary, decentralized science is already mature enough to impact the way scientific research is conducted today. Although there are currently some gaps and challenges, overcoming the "Valley of Death" in research is a significant step forward.

02 Introduction

2.1 Background of Traditional Scientific Research

The process through which the scientific industry generates new knowledge and inventions can be divided into different stages, primarily into basic research and clinical research. These two main stages are bridged by translational research. The key function of translational research is to translate the outcomes of basic research into practical applications that can be tested through clinical research. The ultimate goal of this process is to commercialize research findings and create products that benefit society.

(Figure 1: The "Valley of Death" represents the stage of most research failures between basic science and clinical science)

However, one of the biggest challenges in this process is the "Valley of Death" phenomenon, where many scientific efforts fail due to a lack of effective translational research.

According to data from the National Institutes of Health (NIH), 80% to 90% of research projects fail before reaching human trials. Additionally, for every drug approved by the FDA, over 1,000 candidate drugs are developed but ultimately fail. Even in later stages, challenges persist - almost 50% of experimental drugs fail during Phase III clinical trials. From this perspective, the probability of a new drug candidate progressing from preclinical studies to FDA approval is only 0.1%. These staggering statistics underscore the significant challenge of translating knowledge and innovations developed by universities and research institutions into practical products or therapies for human use.

(Figure 2: The number of approved new molecules has been declining in each $1 billion of global R&D spending)

Exacerbating these challenges is the increasingly inefficient drug development process. In the United States, the cost of developing and approving a new drug approximately doubles every nine years - a phenomenon known as Eroom's Law, the opposite of Moore's Law. Some reasons for this may include stricter regulatory standards, new medical discoveries meeting higher thresholds for unmet needs compared to existing drugs, and the high costs of designing and running clinical trials by contract research organizations. If this trend continues, by 2043, the cost for the biopharmaceutical industry to develop a drug could reach $160 billion. This financial burden often leads the industry to focus on developing more profitable drugs, which can overshadow the urgency of addressing other key health needs.

This inefficiency will lead to significant economic and social consequences. High R&D costs, coupled with frequent failures, result in continuously rising healthcare costs, which are ultimately borne by patients, governments, and insurance companies. Furthermore, the delay and failure to translate research findings into viable therapies mean that patients often miss out on potentially life-saving opportunities, exacerbating public health challenges. For example, rare diseases and conditions affecting smaller population groups are often overlooked because they are deemed less profitable, despite the urgent need for treatment.

2.2 Why Most Research Cannot Escape the “Valley of Death”

The fundamental problem lies in misaligned incentives, leading to three major challenges: insufficient funding, reduced collaboration between researchers and clinicians, and poor replicability and reproducibility of scientific discoveries. These challenges ultimately result in research getting trapped in the “Valley of Death”.

We will delve deeper into these key challenges in the following sections:

2.2.1 Lack of Funding

The lack of funding, especially when transitioning from the basic research stage to clinical research, can be attributed to the inconsistent incentives between funders and researchers, as well as the lack of transparency in the grant review process.

From the funders' perspective, they are more likely to prioritize research that can be translated into products generating recurring revenue. As a result of this chain reaction, due to the competitiveness of funding acquisition, researchers tend to work more in line with the funders' expectations, making the research more conservative and effectively stifling innovation.

Moreover, the opaque review process means that a single proposal presented to different panels may yield different outcomes. In situations where grant review panelists are uncompensated, this can lead to other complexities such as biased competition among researchers, insufficient attention to details, and significant delays in grant approvals. This implies that researchers tend to spend more time publishing papers to establish their scientific reputation 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 is crucial during the translational research phase.

Effective collaboration facilitates the innovative design of clinical trials, integrating biomarkers from basic research or targeted research approaches. For instance, oncology has made significant strides through collaboration, where genetic and molecular discoveries in the lab directly inform the design of targeted therapies and trials for specific cancer subtypes. This synergy reduces the risk of late-stage trial failures and enhances the possibility of providing effective treatments to patients.

However, there is currently little incentive for basic scientists (focused on discovery) and clinical doctors (focused on patient care and clinical research) to collaborate. The advancement of basic science research is often linked to the amount of funding grants and the number of publications in top-tier journals, rather than contributions to clinical science and medical progress. Conversely, the success of many clinical doctors is dependent on how many patients they treat, and they often lack the time or motivation to conduct research and seek funding opportunities.

As a result, these two groups ultimately operate independently, meaning the likelihood of combining laboratory findings with clinical relevance is reduced.

2.2.3 Low Replicability and Reproducibility of Scientific Discoveries

Reproducibility refers to the ability to obtain consistent results by 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 scientific finding as before. If scientific discoveries lack reproducibility and replicability, it is challenging to demonstrate the effectiveness and validity of basic research, making it difficult to translate into clinical applications.

The challenge of translating animal research into human research has led to inefficiency—reportedly, only 6% of animal studies can be translated into human responses. Other issues, such as methodological differences (e.g., coating types on test tubes, temperature of cell growth, how cells are stirred in culture), may also lead to results that are entirely irreproducible.

While the scale of the problem is largely attributed to the complexity of science, the inconsistent incentive mechanisms between publishers and early-stage researchers are also one of the reasons for the lack of replicability and reproducibility in scientific discoveries. Publishers play a crucial role in nurturing early-stage researchers, and published works can enhance credibility, thereby increasing funding opportunities. Therefore, researchers who achieve statistically significant results on their first attempt are less willing to replicate experiments and instead opt to publish directly.

03 Decentralized Science 101

3.1 What is DeSci?

Decentralized Science ("DeSci") is a movement to create a new scientific research model using the Web3 stack.

Blockchain has unique advantages that can address the challenges mentioned above. It provides a trustless way of coordinating funds while ensuring a transparent and immutable way of tracking progress and records, allowing the interests of all stakeholders to be taken into account.

DeSci is still in its early stages in the crypto industry. This can be seen from its total market cap just surpassing $1.75 billion, and only 57 projects are tracked under the DeSci category on CoinGecko. From this perspective, DeFAI (Defi x AI Agent) has only 41 projects with a total market cap of $2.7 billion, while the broader Crypto AI has a total market cap of $47 billion (as of January 15, 2025).

3.2 How DeSci Addresses the "Valley of Death"

As mentioned earlier, most research fails in the "Valley of Death" due to inconsistencies in incentives, resulting in challenges such as insufficient funding, reduced collaboration, poor reproducibility and repeatability of scientific results, among others. DeSci can address this coordination issue by using decentralized autonomous organizations (DAOs), blockchain, and smart contracts.

Below, Binance Research summarizes how DeSci provides solutions to existing challenges, first in a tabular form for clarity and then with detailed explanations. As a movement, DeSci tackles these challenges in the following ways:

3.2.1 How DeSci Addresses Funding Shortages

DAOs can act as a capital formation tool for research funding, with participants being a mix of patients, researchers, and investor communities. Since the stakeholders share a common goal of advancing research to the clinical stage and eventually commercializing it, they have a shared motive to help research cross the "Valley of Death."

Decisions are made through decentralized token governance, with voting conducted transparently and democratically. Subsequently, smart contracts execute the parameters of the DAO decisions while ensuring transparency. Examples include milestone-based funding programmatically issued, tokenization of intellectual property (IP) generated from funded scientific research, subdividing IP and distributing it to all DAO participants to coordinate interests, and more.

Overall, DAOs in the DeSci space can coordinate various stakeholders in a trustless manner towards a common goal, fostering collaboration from basic research to clinical research through an integrated end-to-end approach.

3.2.2 How DeSci Addresses Reduced Collaboration Between Researchers and Clinicians

As mentioned above, the main reason for reduced collaboration is the differing incentive structures between researchers and clinicians. This can be addressed through participation in a DAO, where at the DAO's creation, research hypotheses, experimental methods, and parameters can be agreed upon to coordinate research outcomes. Coupled with IP tokenization, both researchers and clinicians can receive sufficient incentives and rewards to advance the research to the clinical stage.

Other tools that facilitate greater collaboration include platforms that incentivize peer review, where upon successful review, rewards can be programmatically distributed through smart contracts. This can bring clinicians closer to researchers, providing early input that can guide research towards actual implementation in the clinical stage upon success. Moreover, a blockchain-based reputation system can be built around scientific community members based on their contributions to various DeSci DAOs, peer review work, clinical implementations, where any work done for scientific advancement receives appropriate attribution.

3.2.3 How DeSci Addresses the Low Reproducibility and Replicability of Scientific Discoveries Issue

One way to address this issue is to document the research methodology, experimental design, and each step on the blockchain. The blockchain serves as an immutable ledger, ensuring that other researchers can fully understand the conducted experiment. If they wish to replicate the experiment, they can query each variable.

Furthermore, a new form of open and accessible publication can be built using Web3 primitives, where all research (even failed research) can be shared. This will eliminate publication bias, where only successful experiments are published, as data from failed experiments still hold value.

Another area where DeSci can provide assistance is data integrity and compliance. While traditional archive storage can also meet this need, they often rely on tapes, which makes data retrieval slow. Given the dynamic nature of scientific research, involving multiple parties processing the same data while maintaining data immutability and security, distributed storage and data warehouses can be a solution. They can provide necessary data access control, offer greater redundancy by eliminating single points of failure, and provide fast data retrieval for collaborative work. This will promote more rigorous scientific research and increase the likelihood of replicable and reproducible results.

04DeSci Landscape Overview

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-industries such as funding platforms and DAO tools (e.g., IP tokenization, DAO formation, and legal protocols). These form the cornerstone of the DeSci DAO, which sits at the forefront of scientific discovery.

· Research comprises grassroots communities such as DeSci Global, DeSci Collective, which host global events to connect DeSci enthusiasts and future DAOs that capitalize common interests from multiple stakeholders. These DAOs typically focus on different scientific fields like longevity, hair loss, women's health, among others.

· Data Services encompass publishing and peer-review platforms that enable open access to scientific publications, fostering more collaboration, as well as data management tools to provide robust data integrity and proper access controls.

· Memes represent the interest of retail investors in the market, bringing more awareness and education to the DeSci field, which is usually limited to the academic world. Some Memecoins directly fund scientific experiments, while others serve as investment tools for other DeSci projects.

4.2 Sub-Industries Worth Watching

A. Infrastructure: Intellectual Property (IP) Tokenization / Fractionalization

Intellectual Property (IP) tokenization addresses a fundamental barrier in research and innovation, which is the monetization and liquidity of intellectual property (IP), playing a transformative role in driving scientific translation.

Traditional IP management and transaction systems are cumbersome, centralized, and often inaccessible to smaller stakeholders, limiting the speed of discovery commercialization and translation into real-world applications. By leveraging blockchain technology, IP tokenization has created a decentralized and transparent framework that enables researchers, investors, and other stakeholders to more effectively participate in and fund innovative projects.

IP tokenization involves converting intellectual property into digital assets, making it tradable and liquid. Projects like Molecule embody this process by introducing the concept of 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-manage intellectual property. The desired outcome is stakeholder coordination to ensure sufficient funding to advance research to the clinical stage and ultimately commercialize it.

B. Infrastructure: DAO Formation

DAO infrastructure represents a key innovation in decentralized science, enabling patient, scientist, and biotech professional communities to collectively fund, manage, and own scientific projects. Traditional scientific funding is often restricted by centralized institutions, stringent gatekeeping, and opaque processes. DAO infrastructure disrupts this model by providing a transparent, decentralized framework for the planning, funding, and governance of scientific initiatives.

Through DAOs, stakeholders can pool resources, make collective decisions, and directly influence the trajectory of scientific research. The BIO Protocol is an example that supports the creation, funding, and governance of BioDAOs. Each BioDAO has its own expertise and focuses on different scientific fields such as longevity (VitaDAO), cryopreservation (CryoDAO), hair loss (HairDAO), women's health (AthenaDAO), among others.

C. Infrastructure: Funding Platform

Web3 funding platforms are changing the way scientific research is funded by decentralizing the process and enabling broader participation. Traditional research funding often relies on grants and institutional support, which can be slow-moving, highly bureaucratic, and limited in scope. Through crowdfunding, it provides researchers with the opportunity to directly engage with funders, the community, and collaborators, promoting a more transparent and inclusive funding ecosystem.

These funding platforms may also differ in terms of the beneficiaries of the funding. For example, Catalyst (aimed at funding DeSci IPs), Bio.xyz Launchpad (aimed at funding DeSci DAO), and pump.science (aimed at funding compound testing).

Web3's composability allows different crowdfunding platforms to coordinate stakeholders across various stages of research, facilitating a seamless funding ecosystem. For example, a DeSci DAO funded through Bio.xyz could receive funding for a specific IP research organization through Catalyst or transparently test and validate compounds through pump.science.

D. Data Service: Publishing / Peer Review Platform

The traditional scientific research publishing model is often slow, expensive, and hard to access, with high Article Processing Charges (APCs) and limited peer review transparency. Additionally, researchers rarely receive recognition or compensation for their contributions to the peer review process. This slows down the review process, increases the likelihood of bias due to conflicts of interest, and overall hinders the pace of scientific progress, limiting avenues for broader access to knowledge.

Incentivized peer review and publishing platforms aim to address these issues by creating open and transparent systems where researchers are rewarded for their contributions (including publication, review, and collaboration). By integrating blockchain technology and community governance, these platforms democratize access to scientific knowledge, accelerate research dissemination, and foster collaboration among global researchers. ResearchHub is one example where researchers can earn token rewards for peer-reviewing articles or collaborating with like-minded individuals in their field of interest. Positive contributions to the scientific community can be recorded on the blockchain, establishing a scientist's reputation and unlocking features such as peer review and access control.

This is also where it intersects with artificial intelligence. Projects like yesnoerror have already launched, which is an AI agent that uses OpenAI to find mathematical errors. It can discover mathematical errors, identify fraudulent data, and detect numerical inconsistencies that could potentially harm scientific integrity at scale, all with minimal downtime.

E. Data Service: Data Interoperability and Integrity

The healthcare and biomedical research industries are plagued by data system fragmentation, lack of transparency, and a lack of patient-centered practices. Patients often donate valuable data and biospecimens for research but are unable to understand and control how their contributions are used, with little ability to benefit from the resulting scientific or commercial value. These gaps have led to distrust, privacy breaches, and decreased engagement, especially in marginalized and underrepresented communities.

Data interoperability and integrity aim to address these issues by creating systems that empower patients with transparency, control, and shared benefits while enabling seamless collaboration among researchers, institutions, and businesses. Interoperable systems allow for the coordination of diverse data sources, enabling them to be used across networks while safeguarding data privacy and integrity. This ultimately accelerates scientific discoveries, streamlines clinical development, and fosters trust in biomedical research.

AminoChain is an example of such a system, being a decentralized platform designed to connect healthcare institutions and support user-owned healthcare applications. It enables patients to control their own data and samples, ensures transparency in data usage, and allows them to share in the value generated by research. Other decentralized data solutions include Filecoin, Arweave, Space and Time, where data is securely stored, free from single points of failure, while providing flexible access controls to ensure data is handled properly.

05 Final Thoughts

We are at an early stage of DeSci, where this decentralized way of doing science is becoming increasingly prominent in today's scientific practice. DeSci has the potential to coordinate stakeholders from the early stages of research to ensure sufficient interest in advancing research to clinical stages.

The infrastructure for coordinating research in a decentralized manner already exists. Aligned stakeholders can formalize their common interests in scientific research through DAOs, providing funding and conducting research, owning the intellectual property generated, securely sharing data within data protection guidelines to enhance collaboration across scientific communities.

However, the current stack is more suited to basic and translational research rather than clinical research. The former requires more trustless coordination, while the latter necessitates coordination with centralized entities such as regulatory bodies, pharmaceutical companies, physical labs, etc.

Furthermore, the legality of DAOs remains a continuously debated and evolving area of regulation. In the case of the Ooki DAO, the U.S. Northern District of California court ruled that the DAO qualifies as a “person” under the Commodity Exchange Act, setting a precedent that DAOs can bear legal responsibility. This decision has significant implications for DAO members, as it suggests that token holders participating in governance may be personally liable for DAO actions. Given the lack of clarity in handling DAOs, this may deter potential funders.

In conclusion, DeSci has matured enough to impact the way scientific research is conducted today. While there are currently some gaps and challenges, addressing the "valley of death" in research is a significant step forward.

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