Binance Research Report: From challenges to opportunities, how does DeSci reimagine science?

Since ancient times, both emperors, generals and ministers have had endless yearning for immortality, and now they are the same. This pursuit of life continuation and exploration of the cutting-edge scientific research have taken new directions with the help of blockchain technology. The rise of decentralized science (DeSci) has provided new hope and possibilities for the exploration of the forefront of science.

The first thing that attracted my attention to DeSci was Pfizer's investment in VitaDAO. This is not only Pfizer's first investment in the Web3 field, but also marks the recognition and support of traditional pharmaceutical giants in the DeSci field. Based on the entrepreneurial background of digital medical care, we will think about how to reimagine a business model through DeSci.

This DeSci research report "From Challenges to Opportunities: How DeSci Reimagines Science" released by Binance Research first proposed the phenomenon of "Death Valley" in the scientific research process, and then led to DeSci and responded through DeSci's innovative solutions. "The Valley of Death" finally summarizes the current DeSci pattern in the market, indicating that DeSci is mature enough to influence the way scientific research is carried out today. Although there are some gaps and challenges in the current situation, solving the "Valley of Death" in research is a big step forward.

Following the research and report ideas, in fact, in the process of transforming scientific research into commercialization, DeSci can also be combined with blockchain technology and Web3 more. Let’s take medical research and development as an example:

• Data acquisition: Data from early basic research and translational research can be obtained through DePIN, and AI can be used to further strengthen these data. The advantage is that it can cover a global scale and provide incentives;
• Data storage: This data can be stored on the chain through encryption technology, maintaining the invariance and security of the data, while building a new form of publication that is open and accessible to everyone, to some extent, addressing the replicability and ability of scientific discoveries. Repeat questions;
• Community of interests: Through the rules formulated by DAO organizations, a community of interests between basic research and clinical treatment can be realized. This rule can be further expanded, covering the entire research, clinical, commercialization, doctor-patient scenarios and other links, and achieving multi-party sharing. win;

In the future, DeSci will present a picture: a decentralized organization (DAO) composed of a multi-party interest community, with common goals and vision, no longer be entangled by capital profits, and deeply combines blockchain technology and Web3 to promote Scientific discoveries, accelerate the implementation of substantial products, and promote the development and progress of the entire society.

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

The following is From Challenges to Opportunities: How DeSci Reimagines Science content, Enjoy:

01 /Core Views

• The scientific research process faces major challenges, especially in the transformation of basic research to practical application. The "Gain of Death" phenomenon caused 80%-90% of research projects to fail before human trials, and only 0.1% of drug candidates became approved treatment options.

• Inconsistent incentive mechanisms between academia, funding agencies and industries have led to challenges such as insufficient funding for R&D, reduced collaboration between scientists and clinicians, and poor replicability and reproducibility of scientific discoveries, which ultimately lead to the majority of studies in the “ Stagnated in the Valley of Death.

• Decentralized Science (DeSci) is a campaign to create innovative scientific research models that can meet the above challenges using the Web3 stack.

• By using decentralized autonomous organizations (DAOs), blockchains and smart contracts, DeSci can solve key coordination problems. This enables different stakeholder groups to coordinate their capital interests, thereby motivating them to advance their research to the clinical stage.

• Currently, the market has identified 4 key innovation areas in the DeSci field:

• Infrastructure, including sub-industry such as financing platforms and DAO tools, forms the cornerstone of DeSci DAO.

• Research, including grassroots DeSci community hosting events around the world and a consistent vision from multiple stakeholders DAO.

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

• Memes, directly funding scientific experiments, or as an investment vehicle for other DeSci projects.

• While the existing stack can already support basic and translational research, it is not very suitable for clinical research, which is an area where the product has direct benefits for patients.

• All in all, decentralized science is mature enough to influence the way today's scientific research is. Although there are some gaps and challenges under the current situation, solving the "Valley of Death" in research is a big step forward.

02 /Introduction

2.1 Background of traditional scientific research

The process of generating new knowledge and new inventions in the scientific industry can be divided into different stages, mainly divided into two stages: basic research and clinical research. These two main stages are connected by translational research. The key function of translational research is to transform the results of basic research into practical applications that can be tested by clinical research. The ultimate goal of this process is to commercialize research and discoveries and create products that benefit society.

However, one of the biggest challenges in this process is the Valley of Death phenomenon, and many scientific efforts have failed due to the lack of effective translational research.

According to the National Institutes of Health (NIH), 80% to 90% of research projects fail before human trials are conducted. In addition, more than 1,000 drug candidates were developed but ultimately failed for each FDA-approved drug. Even in the later stages, the challenge remains—almost 50% of experimental drugs fail during Phase III clinical trials. From this perspective, the probability of a new drug candidate from preclinical research to FDA approval is only 0.1%. This stunning statistics highlights the significant challenges of transforming knowledge and innovation developed by universities and research institutions into practical products or treatments for human application.

What aggravates these challenges is the increasingly inefficient R&D process in drug development. In the United States, the cost of developing and approving a new drug doubles approximately every nine years—a phenomenon known as Eroom’s law, the opposite of Moore’s law. Some reasons may be stricter regulatory standards, high barriers to new medical discoveries to meet different needs than existing drugs, and high costs for contract research organizations that design and run clinical trials. If this status quo continues, the biopharmaceutical industry may cost as much as $16 billion by 2043. This financial burden often leads the industry to focus on developing more profitable drugs, which often obscures the urgency of addressing other key health needs.

This inefficiency will lead to significant economic and social consequences. The high cost of R&D, coupled with frequent failures, has led to rising medical costs, which are ultimately borne by patients, governments and insurance companies. Furthermore, delays and failures in translating research findings into viable therapies mean that patients often do not have access to potentially save lives, exacerbating public health challenges. For example, rare diseases and conditions that affect smaller groups are often overlooked because they are considered to be less profitable, despite urgent need for treatment.

2.2 Why most studies cannot get out of the "Gao of Death"

The fundamental problem is the misalignment of incentive mechanisms, leading to three major challenges: insufficient funding, reduced collaboration between researchers and clinicians, and poor replicability and repeatability of scientific discoveries. These challenges ultimately lead to the study falling into the "Gail of Death".

We will explore these major challenges in more detail below:

2.2.1 Lack of funds

The lack of funding, especially when moving from the basic research stage to clinical research, can be attributed to inconsistencies in incentive mechanisms between funders and researchers, and a lack of transparency in the funding review process.

From the funder’s perspective, they will prioritize research that translates into products that can generate recurring revenue. The resulting ripple effect is that, given the competitiveness of obtaining funds, researchers tend to work as funders expect, which makes research more conservative and effectively stifle innovation.

Furthermore, an opaque review process means that a single proposal to different groups may produce different results. In the absence of compensation from the grant review team, other complexities may result in such biases by competing researchers, insufficient attention to detail, and serious delays in grant approval. This means that researchers tend to spend more time publishing publications to establish a position in the scientific community rather than conducting experiments.

2.2.2 Reduced collaboration between researchers and clinicians

Given that most studies stagnate in the Valley of Death, coordination between basic researchers and clinicians during translational studies is crucial.

Effective collaboration has facilitated the design of innovative clinical trials that integrate biomarkers or targeted research methods for basic research. For example, oncology has made significant progress through collaboration, with the laboratory’s genetic and molecular discovery directly informing targeted therapies and trial designs for specific cancer subtypes. This synergy reduces the risk of late trial failure and increases the likelihood of providing effective treatment to patients.

However, basic scientists (focused on discovery) and clinicians (focused on patient care and clinical research) have little motivation to collaborate at present. Promotion in basic scientific research is often related to the number of grants funded and the number of publications in top journals rather than contributions to advances in clinical science and medicine. Instead, the success of many clinicians depends on how many patients they treat, and they usually don’t have the time or motivation to conduct research and seek funding opportunities.

Therefore, both groups end up being independent, which means the possibility of combining laboratory findings with clinical relevance is reduced.

2.2.3 Replicability and reproducibility of scientific discoveries

Repeatability refers to the ability to obtain consistent results using the same data, methods and calculation steps as the original study. Replicability, on the other hand, involves conducting a new study to draw the same scientific findings as before. If scientific discoveries are not reproducible and replicable, it will be difficult to prove the effectiveness and rationality of basic research, and thus it will be difficult to expand to clinical applications.

The challenge of converting animal studies into human studies has led to inefficiency—only 6% of animal studies are said to be able to translate into human responses. Other issues, such as methodological differences (such as the type of coating on the test tube, the temperature of cell growth, how to stir cells in culture) can also lead to the complete inability to replicate the results.

While the scale of the problem can be largely attributed to the complexity of science, inconsistencies in incentive mechanisms between publishers and early researchers are also one of the reasons for the lack of repeatability and reproducibility of scientific discoveries. Publishers play an important role in nurturing early researchers, and published works can increase credibility and thus increase opportunities for funding. Therefore, researchers who obtained statistically significant results on the first attempt were less willing to repeat the experiment and instead published it directly.

03 /Decentralized Science 101

3.1 What is DeSci?

Decentralized Science (“DeSci”) is a campaign to create new scientific research models using the Web3 stack.

Blockchain has unique advantages to address the above challenges. It provides a trustless way to coordinate funds while ensuring a transparent and immutable way to track and record progress, allowing the interests of all stakeholders to be considered.

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

3.2 How DeSci deals with "Gao of Death"

As mentioned earlier, most studies failed in the Valley of Death because of inconsistent incentive mechanisms that resulted in challenges such as insufficient funding, reduced cooperation, poor replication and reproducibility of scientific results. DeSci can solve this coordination problem by using decentralized autonomous organizations (DAOs), blockchains and smart contracts.

Below, Binance Research summarizes how DeSci provides solutions to existing challenges, first presented in tabular form for clarity and comprehension and then explained in detail. As a sport, DeSci meets these challenges in the following ways:

3.2.1 How DeSci solves the problem of funding shortage

DAOs can act as capital formation tools for research funds, and participants can be a mixture of patients, researchers, and investors’ communities. Since the shared goal of stakeholders is to get research into the clinical stage and ultimately commercialize it, they share a common motivation to help research cross the “valley of death.”

Decisions are made through decentralized token governance, and voting can be conducted in a transparent and democratic way. The smart contract then executes the parameters determined by the DAO while ensuring transparency. Examples include milestone funding programmatically released, intellectual property (IP) tokenization generated by funded scientific research, subdividing intellectual property rights and distributing them to all DAO participants to coordinate interests, etc.

Overall, DAOs in the DeSci field can coordinate various stakeholders in a trustless manner and collaborate towards common goals, thereby providing an integrated end-to-end approach from basic research to clinical research.

3.2.2 How DeSci solves the problem of reduced collaboration between researchers and clinicians

As mentioned above, the main reason for the reduction in collaboration is the difference in incentive mechanisms between researchers and clinicians. This can be solved by participating in the DAO, where research hypotheses, experimental methods and parameters can be agreed upon at the time of DAO creation, thereby coordinating the research results. Coupled with IP tokenization, researchers and clinicians can receive enough incentives and rewards to advance the research to the clinical stage.

Other tools to promote greater collaboration include platforms that encourage peer reviews, which can be distributed programmatically through smart contracts after successful reviews. This can bring clinicians closer to researchers and, by providing early input, can guide the research towards practical implementation of the clinical stage once successful. On-chain reputation systems can also be established around members of the scientific community based on their contributions to various DeSci DAOs, peer review work, clinical implementation, etc., in which any work done for scientific progress will be appropriately attributable.

3.2.3 How DeSci solves the problem of low replication and repeatability of scientific discoveries

One way to solve this problem is to record research methods, experimental design, and every step on the blockchain. Blockchain is an immutable ledger, which ensures that other researchers have a comprehensive understanding of the experiments being conducted and that if they wish to repeat the experiments, they can query each variable.

Additionally, a new form of release that is open and accessible to everyone can be built using the Web3 primitive, where all studies (even failed studies) can be shared. This will eliminate the publishing bias, that is, only successful experiments will be published, because the data from failed experiments are still valuable.

Another area where DeSci can help is data integrity and compliance. While traditional archive storage can also meet this requirement, they usually rely on tape, which makes data retrieval very slow. Given the dynamic nature of scientific research, involving processing the same data across multiple parties, while maintaining the invariance and security of the data, decentralized storage and data warehouses can be solutions. They can provide the necessary data access control, providing greater redundancy by eliminating single points of failure while providing fast data retrieval for collaborative work. This will promote more stringent scientific research and increase the likelihood of replicable and reproducible results.

04 / DeSci Pattern Overview

4.1 Key innovation areas

Binance Research has identified 4 key innovation areas in the DeSci landscape: infrastructure, research, data services and Memes.

Infrastructure includes sub-industry such as financing platforms and DAO tools (such as IP tokenization, DAO formation and legal agreements). These form the cornerstone of DeSci DAO, which is at the forefront of scientific discoveries.

Research includes grassroots communities such as DeSci Global and DeSci Collective, which host events around the world to connect with DeSci enthusiasts and DAOs that bring common interests from multiple stakeholders. These DAOs are often focused on different scientific fields such as longevity, hair loss, women's health, and more.

Data Services include publishing and peer review platforms that enable open access to scientific publications, thereby facilitating more collaboration, as well as data management tools to provide strong data integrity and appropriate access control.

Memes represents the interests of retail investors in the market and can bring more knowledge and education to the DeSci field, which is usually limited to the academic community. Some Memecoin directly fund scientific experiments, while others serve as investment vehicles for other DeSci projects.

4.2 Sub-industry worth paying attention to

A. Infrastructure: IP tokenization/fragmentation of intellectual property rights

IP tokenization of IP plays a transformative role in promoting transformational science by addressing a fundamental obstacle in research and innovation, namely the monetization and liquidity of IP (IP).

Traditional IP management and transaction systems are cumbersome, centralized, and often inaccessible to smaller stakeholders, limiting the speed at which discovery can be commercialized and translated into real-world applications. By leveraging blockchain technology, IP tokenization creates a decentralized and transparent framework that enables researchers, investors and other stakeholders to participate and fund innovative projects more effectively.

IP tokenization involves converting intellectual property into digital assets, making it tradable and liquid. Projects like Molecule reflect this process by introducing the concepts of IP-NFT (intellectual property non-fungible tokens) and intellectual property tokens (IPT). IP-NFT brings intellectual property to the chain, while fragmentation allows multiple stakeholders to jointly manage intellectual property. The desired outcome is coordination of stakeholders to ensure that sufficient funding is available to advance the research to the clinical stage and ultimately commercialize it.

B. Infrastructure: DAO construction

DAO infrastructure represents a key innovation in the decentralization of science, enabling the community of patients, scientists and biotechnology professionals to jointly fund, manage and own scientific projects. Traditional scientific funding is often limited by centralized institutions, strict gatekeepers and opaque processes. DAO infrastructure breaks this model by providing a transparent, decentralized framework for the planning, funding and governance of scientific programs.

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

C. Infrastructure: Funding Platform

The Web3 funding platform is changing the way scientific research is funded through process decentralization and enabling wider participation. Traditional research funding often relies on grants and institutional support, which can be slow, bureaucratic and limited in scope. Through crowdfunding, it provides researchers with opportunities to connect directly with funders, communities and collaborators, thereby promoting a more transparent and inclusive funding ecosystem.

These funding platforms may also differ in funding beneficiaries. For example, Catalyst (to fund DeSci IPs), Bio.xyz Launchpad (to fund DeSci DAO) and pump.science (to fund compound testing).

The composability of Web3 enables different crowdfunding platforms to coordinate research on stakeholders at all stages, thereby facilitating seamless funding ecosystems. For example, DeSci DAO funded by Bio.xyz can organize funding for specific IP research through Catalyst, or test and validate compounds in a transparent manner through pump.science.

D. Data Service: Publishing/Peer Review Platform

Traditional scientific research publishing models are usually slow, expensive and difficult to access, with high article processing fees (APCs), and limited transparency in peer review. Furthermore, researchers rarely receive honors or compensation for their contribution to the peer review process. This slows down the scrutiny and increases the possibility of bias due to conflicts of interest. Overall, this hinders the pace of scientific advancement and limits access to knowledge for a wider audience.

The motivational peer review and publishing platform aims to address these issues by creating open and transparent systems, where researchers are rewarded for their contributions, including publishing, reviewing, and collaboration. By integrating blockchain technology and community governance, these platforms democratize access to scientific knowledge, accelerate the dissemination of research, and promote collaboration among global researchers. ResearchHub is an example where researchers can earn token rewards through peer-reviewed articles or work with like-minded people in the science field they are interested in. Positive contributions to the scientific community can be recorded on the chain, establishing a reputation for scientists, and unlocking features such as auditing and access control

This is also interesting to intersect with artificial intelligence. Projects such as yesnoerror are already online, an artificial intelligence agent that uses OpenAI to discover mathematical errors. It can detect mathematical errors, identify forged data, and detect inconsistencies in numerical values ​​that may impair scientific integrity on scale, with little downtime in between.

E. Data Services: Data Interoperability and Integrity

The healthcare and biomedical research industry is plagued by fragmentation of data systems, a lack of transparency and a lack of patient-centered practice. Patients often donate valuable data and biological samples for research, but cannot understand and control how their contributions are used and rarely benefit from the scientific or commercial value generated. These gaps have led to distrust, privacy breaches and decreased engagement, especially in marginalized and underrepresented communities.

Data interoperability and integrity are designed to address these issues by creating systems that give patients transparency, control and shared benefits while enabling seamless collaboration between researchers, institutions and businesses. Interoperability systems allow coordination of different data sources so that they can be used on the network while protecting data privacy and integrity. This ultimately accelerated scientific discoveries, simplified clinical research and development, and built trust in biomedical research.

AminoChain is an example, a decentralized platform designed to connect healthcare institutions and support user-owned healthcare applications. It allows patients to control their own data and samples, ensure transparency in how data is used, and allow them to share the value generated by their research. Other decentralized data solutions include Filecoin, Arweave, Space and Time, where data is stored securely without single point of failure, while providing flexible access control to ensure data is processed adequately.

05 /Written at the end

We are in the early stages of DeSci, and this decentralized approach to science will become increasingly prominent in today's way of science. DeSci has the potential to coordinate stakeholders from the early stages of the study to ensure that there is sufficient interest to advance the study to the clinical stage.

Infrastructures that coordinate research in a decentralized way already exist. Consistent stakeholders can formalize their shared interests in scientific research in the form of DAOs, provide funding and conduct research, and they can have the resulting intellectual property rights to share data securely within the scope of data protection guidelines to enhance Cooperation between different scientific communities.

However, existing stacks are more suitable for basic and translational studies than for clinical studies. The previous research phase required more trustless coordination, while the latter needed coordination with centralized groups such as regulators, pharmaceutical companies, and physical laboratories.

Furthermore, the legitimacy of DAO remains an area of ​​ongoing debate and regulatory development. In the Ooki DAO case, the US District Court of Northern District of California ruled that Ooki DAO is a "person" under the Commodity Exchange Act, setting a precedent for DAO to bear legal liability. This decision has a significant impact on DAO members because it indicates that token holders involved in governance may be personally responsible for the DAO’s actions. Given the lack of clarity on the DAO’s handling, this may discourage potential funders.

All in all, DeSci is mature enough to influence the way scientific research is conducted today. Although there are some gaps and challenges in the current situation, solving the "Valley of Death" in research is a big step forward.