This is a work in progress. Contributions are welcome! Just click the edit button in the lower right corner. It's our goal to avoid any duplication of effort. So please include existing projects that would be interested in fulfilling any part of this global framework.
ΒΆ Mandate
Maximize average healthy human lifespan and minimize net suffering by quantifying the effects of every food, additive, supplement, and medical intervention.
The Wikipedia model demonstrates the tremendous power of crowdsourcing and open collaboration. Despite Microsoft spending billions of dollars hiring thousands of expert PhDs to create Encarta, Wikipedia garnered over 50 times more content in just a few years - all from volunteers. Moreover, studies have shown Wikipedia's accuracy on scientific topics rivals leading encyclopedias.
The Decentralized FDA aims to produce a 50X acceleration in clinical discovery by replicating this model for clinical research. By crowdsourcing real-world data and observations from patients, clinicians, and researchers, the Decentralized FDA could enable orders of magnitude more insights and discovery than the current closed research system.
Rather than a few expensive clinical trials conducted by pharmaceutical companies, the Decentralized FDA would facilitate a massive decentralized clinical trial encompassing millions of patients. This "Wikipedization" of evidence-based research can unlock lifesaving knowledge at a fraction of the cost and time of traditional methods. Just as Wikipedia democratized access to knowledge, the Decentralized FDA can democratize health research and empower people with actionable data to improve lives.
The existing regulatory framework for drug approval presents several challenges, hindering the efficiency and effectiveness of pharmaceutical research and public health advancements:
- Prolonged Time and High Costs: It takes over a decade and $2.6 billion on average to bring a drug to market, with Phase III clinical trials costing around $41k per subject.
- Limited Knowledge on Unpatentable Molecules: There is a significant lack of data on the long-term effects of the majority of synthetic or natural compounds, as there is insufficient incentive to research non-patentable molecules.
- Inadequate Exploration of Off-Patent Treatments: There is a lack of financial incentive to approve drugs for additional conditions after their patent expires, leaving potential treatments for rare diseases unexplored.
- Absence of Long-Term Outcome Data: Due to financial constraints, long-term effects of drugs are often unknown.
- Publication Bias: Negative results are frequently unreported, leading to redundant research efforts and wasted resources.
- Exclusion of Diverse Patient Populations: Clinical trials often exclude a vast majority of the patient population, limiting the generalizability of findings.
- Vast Amount of Unresearched Combinations: The immense number of possible molecule-disease combinations leaves 99.9999998% of potential knowledge undiscovered.
- Bias Towards Rejecting Effective Treatments: Cognitive biases and personal risk aversion among regulators result in a tendency to reject potentially life-saving treatments.
To overcome these perverse incentives and biases, implementing a Decentralized Autonomous Organization (DAO) regulatory body is proposed. This would distribute responsibility among a large group of experts, mitigating individual risk and bias, and fostering a more balanced, efficient, and innovative drug approval process. π Learn More
- Credibility: Cultivate a board that embodies trust, expertise, and a stellar reputation in the health and tech industries.
- Reach: Leverage the network of the board to access a wealth of data, resources, and strategic partnerships.
- Funding: Explore innovative funding avenues, including health-focused prizes like the XPRIZE, grants, and private investments.
- Proven Track Record: Highlight and leverage previous successful initiatives led by board members to instill confidence in stakeholders.
- Mission Alignment: Ensure every board member is passionately aligned with the mission, understanding their role in this transformative journey.
- Incentives: Clearly articulate the value proposition for board members, showcasing the impact and personal/professional benefits of their involvement.
The primary initial deliverable a coordination platform. This platform would act as the nexus for facilitating cooperation, communication, and collaborative actions among various stakeholders. It's designed to harness the collective capabilities of existing entities towards achieving the shared vision of accelerated clinical discovery and better health outcomes.
The coordination platform should ideally provide:
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Communication Channels: Enable seamless communication among stakeholders, fostering a community of shared knowledge and goals.
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Resource Sharing Mechanisms: Facilitate the sharing of data, technologies, expertise, and other resources among partners.
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Decentralized Collaborative Workspaces: Provide tools and spaces for collaborative research, data analysis, and project development.
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Partnership Agreements: Streamline the formation and management of partnerships, ensuring clarity on roles, responsibilities, and contributions.
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Project Management Tools: Offer tools for planning, tracking, and managing collaborative projects, ensuring alignment and progress towards shared goals.
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Knowledge Repository: Create a centralized or federated repository for collective knowledge, research findings, and best practices.
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Legal and Regulatory Guidance: Provide guidance on navigating the legal and regulatory landscape for collaborative endeavors, ensuring compliance and mitigating risks.
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Impact Tracking: Implement tools for monitoring, evaluation, and reporting on the impact and outcomes of collaborative projects.
The coordination platform encapsulates a digital environment where stakeholders can come together to synergistically work towards the broader objectives of the dFDA initiative. Through this platform, the barriers to collaboration are minimized, and the pace of innovation and discovery is expected to accelerate, aligning with the overarching mission of maximizing human lifespan and minimizing net suffering.
A tool for self-sovereign storage of personal data that enables effortless data sharing with clinical safety and efficacy studies.
Features
- Data Import: Create seamless mechanisms for importing existing health data while ensuring privacy and security. Import data from all your apps and wearables, so you can centrally own, control, and share all your digital exhaust.
- Data Encryption: Implement robust encryption protocols to safeguard sensitive health data.
- Sync to Trusted Instances: Establish secure channels for data synchronization, ensuring integrity and reliability.
- Federated Learning with Homomorphic Encryption: Innovate in secure data analysis, allowing for meaningful insights without compromising data privacy.
- Data Gems NFTs - Data sets can be encrypted and stored in a decentralized manner generating a Data Gem NFT that can be sold on data exchanges granting the possessor access to the data set.
- Digital Twin Skeleton Key NFT - This key gives you the ability to mint Data Gem Data Access NFTs using your imported data.
- The Human File System Protocol SDK - A Simple API for Patient-Controlled Health Data Aggregation, Sharing, and Monetization. Also standard protocol for personal data exchange between studies, apps and devices.
Potential Implementations, Components or Inspiration
- Knowledge Base: Inspiration could be taken from the Psychonaut Wiki. It's a modified version of MediaWiki with additional quantitative metadata storage regarding the pharmacokintics of various substances. This could be expanded to document the quantitative effects of every factor on specific health outcomes.
- Editing Authorization: Implement a robust authorization mechanism to maintain content integrity and trustworthiness.
- AI-Powered Data Population: Leverage AI to efficiently populate the wiki with initial research and data.
- Data Silos Directory: Compile a comprehensive directory of existing data sources, facilitating integration with the Digital Twin Safe.
- Reputation Scoring: Develop a transparent and reliable reputation-weighted voting system for intervention approval.
- Comparative Policy Analysis - Aggregate existing approval and certification data from existing national regulatory bodies
- Food and Drug Outcome Labels - Ultimately, the most useful output of a decentralized FDA would be Outcomes Label that list the degree to which the product is likely to improve or worsen specific health outcomes or symptoms. These are derived from real-world data (RWD) and subject to Futarchical-weighted review by the board members of the dFDA.
- Publish Meta-Analyses - Generate meta-analyses from all completed studies at ClinicalTrials.gov
- Certification of Intervention Manufacturers/Sources via a Decentralized Web of Trust derived from end-user data and reviews traced back though an NFT-tracked supply chain
- Intervention Ranking - Elevate the most promising yet little/known or researched treatments
- Decentralized Clinical Trials - Not only would this increase knowledge but also access and availability of new and innovated treatments to those who need them urgently.
Potential Implementations, Components or Inspiration
Objective: Lay down the groundwork for the Decentralized FDA, defining its scope, audience, and core values.
Tasks:
- Define Project Scope and Goals: Clearly outline what the Decentralized FDA aims to achieve, its target audience, and its core mission.
- Framing and Naming: Develop a strong framing narrative and decide on a compelling name for the initiative.
- Identify Target Audience: List out the potential board members, disease advocacy organizations, and other key stakeholders.
- Initial Stakeholder Engagement: Begin outreach to potential board members and key stakeholders to introduce them to the project and gauge interest.
Objective: Assemble a diverse and influential Board of Directors to guide and support the initiative.
Tasks:
- Credibility and Reach: Identify and onboard individuals with credibility, reach, and a passion for the projectβs mission.
- Funding Strategies: Develop strategies for funding, exploring options like health-focused prizes, grants, and private investments.
- Define Value Proposition for Board Members: Clearly articulate whatβs in it for them, outlining the impact and benefits of their involvement.
ΒΆ Milestone 3: Collaborations and Partnerships
Objective: Identify and engage with entities already working in similar domains to foster collaboration and knowledge sharing.
Tasks:
- Research Potential Collaborators: Identify entities, initiatives, and experts working on similar projects.
- Initiate Outreach: Reach out to potential collaborators to explore partnership opportunities.
- Develop Collaborative Projects: Work on joint initiatives, sharing knowledge and resources for mutual benefit.
Objective: Implement the Digital Twin Safe with Locally Runnable Nodes, ensuring a secure and efficient data environment.
Tasks:
- Data Import Mechanisms: Develop tools and protocols for importing existing health data.
- Implement Data Encryption: Ensure robust encryption for data at rest and in transit.
- Sync to Trusted Instances: Establish secure and reliable data synchronization channels.
- Federated Learning with Homomorphic Encryption: Innovate in secure data analysis, allowing for insights without compromising privacy.
Objective: Develop and launch the initial version of the Decentralized FDA, populated with initial data and research.
Tasks:
- Develop the Knowledge Base: Utilize a modified version of the Psychonaut Wiki as a starting point.
- Editing Authorization Mechanism: Implement a secure and reliable editing authorization process.
- AI-Powered Data Population: Leverage AI to populate the wiki with initial data and research.
- Compile Data Silos Directory: Create a comprehensive directory of existing data sources for integration.
ΒΆ Milestone 6: Continuous Improvement and Scaling
Objective: Continuously improve the Decentralized FDA, expanding its reach, content, and impact.
Tasks:
- Gather User Feedback: Actively seek feedback from users and stakeholders to identify areas for improvement.
- Implement Updates and Enhancements: Regularly update the platform, adding new features and content based on user feedback and evolving needs.
- Scale Operations: Expand the reach of the Decentralized FDA, engaging with more stakeholders and increasing its impact over time.
- eBay for health data - You can earn magic internet money by selling your data regarding symptoms, treatments, and
factors to pharmaceutical companies, insurance companies, and other data buyers
- Control access and use of your data through fine-grained permissions
- Continuously monitor and audit the data you provide to other organizations
- Connected real-world data yields better insights for your users
- Apps that embed the exchange in their app earn a 0.5% transaction fee for each data sale
- Connect to third-party sources to enrich your data, or easily connect to a user's existing data
- Conduct long-term safety and effectiveness studies by linking their clinical trial data to medical claims and
electronic health record data
- Refine models for finding rare disease patients by linking diagnostic lab, genomic, and imaging data
- Discover new therapeutic candidates with connected data
- Improve value-based care analytics and sharpen total cost of care estimates by linking to EHR and clinical data
- Connect to the nation's largest ecosystem of health data
- Hone risk adjustment factor calculations by linking claims to social determinant's data, to properly estimate the true
cost of patient care
A safe for your digital twin that provides
- Storage
- Security
- Access Control
- De-identified Data Sharing
- API with Advanced Querying Capabilities
- Data import from any source
- Data Format Transformation
- Data visualizations
- Machine learning algorithms
- Data analysis
- Personalized Health Dashboards
Our novel incentive structure overcomes the traditional collaboration and data sharing barriers by encoding contributions through non-fungible tokens (NFTs).
Using smart contracts, the platform will compensate all contributors with royalties.
ΒΆ Problem: You and Everyone You Love Will Suffer and Die
Over 2 billion people are suffering and 150,000 people die every single day from preventable diseases.
For perspective, this is equivalent to:
- FIFTY-ONE September 11th attacks every day
- NINE Holocausts every year
The solution is to use the oceans of real-world evidence to accelerate the discovery of new cures and reveal hidden causes of disease.
The human body can be viewed as a black box with inputs (like diet, treatments, etc.) and outputs (like symptom severity). We're creating a mathematical model of human biology to determine the input factors and values that produce optimal health outcomes.
- Discovering Hidden Causes of Illness - Data mining and analysis to identify hidden factors in our daily life that are making us sicker
- Preventative medicine - Predictive analytics and data analysis of genetic, lifestyle, and social circumstances to prevent disease
- Precision medicine - Leveraging aggregate data to determine the precise treatments and dosages for your unique biology
- Accelerated Treatment Discovery - Data-driven medical and pharmacological research to discover new treatments and medicines
- Reduction of adverse medication events - Harnessing big data to spot medication errors and flag potential adverse reactions
- Cost reduction - Driving better patient outcomes for long-term savings through prevention and avoidance of expensive and ineffective treatments
- Population health - Identify health strategies based on demographic, geographic, and socioeconomic trends
It takes over 10 years and 2.6 billion dollars to bring a drug to market (including failed attempts).
It costs $41k per subject in Phase III clinical trials.
The high costs lead to:
1. No Data on Unpatentable Molecules
We still know next to nothing about the long-term effects of 99.9% of the 4 pounds of over 7,000 different synthetic or natural compounds. This is because there's only sufficient incentive to research patentable molecules.
2. Lack of Incentive to Discover Every Application of Off-Patent Treatments
Most of the known diseases (approximately 95%) are classified as rare diseases. Currently, a pharmaceutical company must predict particular conditions to treat before running a clinical trial. Suppose a drug is effective for other diseases after the patent expires. In that case, there isn't a financial incentive to get it approved for the different conditions.
3. No Long-Term Outcome Data
It's not financially feasible to collect a participant's data for years or decades. Thus, we don't know if the long-term effects of a drug are worse than the initial benefits.
4. Negative Results Aren't Published
Pharmaceutical companies tend to only report "positive" results. That leads to other companies wasting money repeating research on the same dead ends.
5. Trials Exclude a Vast Majority of The Population
One investigation found that only 14.5% of patients with major depressive disorder fulfilled eligibility requirements for enrollment in an antidepressant trial. Furthermore, most patient sample sizes are very small and sometimes include only 20 people.
6. We Only Know 0.000000002% of What is Left to be Researched
The more research studies we read, the more we realize we don't know. Nearly every study ends with the phrase "more research is needed".
If you multiply the 166 billion molecules with drug-like properties by the 10,000 known diseases, that's 1,162,000,000,000,000 combinations. So far, we've studied 21,000 compounds. That means we only know 0.000000002% of the effects left to be discovered.
Despite this massive growth in health data and innovation, we've seen increased costs and disease burden and decreased life expectancy.
The reason is awful incentives. There are more than 350,000 health apps.
Each costs an average of $425,000 to develop.
Most have significant overlap in functionality, representing a cost of $157,500,000,000 on duplication of effort.
Isolated streams of health data can only tell us about the past. For example, dashboards filled with descriptive statistics such as our daily steps or sleep.
If this data and innovation efforts were combined, this could increase the rate of progress by 350,000 times.
The obstacle has been the free-rider problem. Software developers that open source their code give their closed-source competitors an unfair advantage, increasing their likelihood of bankruptcy.
How to Overcome the Free-Rider Problem
- Government Grants - Currently, governments spend billions funding closed-source propriety health software. The Public Money, Public Code initiative requires governments to recognize software as a public good that is open source. This would lead to a massive influx in grant funding for open-source digital health projects.
- Open-Source Royalty Compensation - By encoding contributions to the project with NFTs, we can provide ongoing royalty payments to open-source contributors.
- Licensing - The project core framework will be open-source for any non-commercial purpose. However, we will utilize a Fair-code or Fair Source licensing model to generate revenue when used by for-profit entities. Licensing fees will be negotiated such that a fraction of the profits generated by the licensee's project use.
- Managed Software-as-a-Service - Digital health companies can save months of development time and tens of thousands of dollars using our platform instead of reinventing the wheel. A usage-based subscription platform for health application developers would start at $0.50/end-user per month.
- For-Profit Plugins - WordPress, the most widely used web framework globally, is open-source. Businesses earn revenue by creating for-profit plugins. They contribute to improvements of the open-source core WordPress platform because these improvements benefit their business directly.
A global open-source platform and plugin framework will enable the transformation of data into clinical discoveries.
The functional scope of the platform includes:
- Aggregation
- Managing
- Processing
- Storage
of health data from different sources.
Create a basic foundational technology layer suitable for any digital health application that provides better interoperability, portability, availability, analysis, and data security.
- EHR Systems for healthcare providers
- User-centered dashboards for personal health management
- Data sharing with doctors, health coaches, or family members
- Decentralized clinical trial platforms
- Patient recruitment services for clinical trials
- Citizen science platforms
- Health data marketplaces
- Open health databases for research
- Algorithm and scores development (e.g., in-silico trials)
- Niche health applications with specific requirements or custom integrations
The platform consists of two primary components:
- Core Open-Source Platform - The core platform is open-source and includes only universally necessary features. This primarily consists of user authentication, data owner access controls, data storage, data validation, and an API for storage and retrieval.
- Plugin Framework - Plugins will provide additional functionality like data import from specific sources, data mapping to various formats, data analysis, data visualization, notifications. These may be free or monetized by their creator.
Data Ingestion and Access API
The Unified Health application programming interface (API) includes an OpenAPI specification for receiving and sharing data with the core database. Software development kits (SDKs) will enable developers to implement easy automatic data access and sharing options in their applications.
Data Mapping and Validation
Data from files or API requests can be mapped from many different proprietary formats into a standard schema.
Data Ownership
Data should be owned by the individual who generated it. It should remain under their control throughout the entire data life-cycle from generation to deletion.
Data Compensation
Value stream management allows the exchange of data for tokens.
3rd party plugins can interact with the core and provide additional functionality. They may be free or monetized by their creator. These include:
- Data Import Plugins
- Data Visualization Plugins
- Machine Learning Plugins
- Electronic Health Record System Plugins
- Clinical Trial Management Plugins
Data Analysis Plugins
Data Analysis Plugins will apply statistical and machine learning methods to the ocean of high-frequency longitudinal individual and population-level data. The resulting value will include:
- Personalized Effectiveness Quantification - Determination of the precise effectiveness of treatments for specific individuals
- Root Cause Analyses - Revelation of hidden factors and root causes of diseases
- Precision Medicine - Determination of the personalized optimal values or dosages based on biomarkers, phenotype, and demographics
- Combinatorial Medicine - Discover relationships between variables or combinations of interventions
- Optimal Daily Values - Determination of the personalized optimal dosages of nutrients or medications
- Cost-Benefit Analysis of interventions by weighing clinical benefit against costs in terms of side effects and financial impact
Example Data Presentation Plugins
We use the DAO structure and NFT IP royalties to reward data sharing and open-source collaboration.
This illustrates the flow of value between different stakeholders. Unlike traditional zero-sum games, CureDAO provides everyone with more value from participation than they have to put into it.
Incentives for Patients to share their de-identified data will include:
- Actionable ways to prevent and mitigate chronic illnesses.
- The ability to license and earn a share of income for the use of their data for research and development by pharmaceutical companies and other businesses. NFTs will be linked to the user's cryptographic wallet address. Using a smart contract, the user will receive an ongoing royalty share of the profits for any product developed using their data for research and development.
Businesses housing data silos include health insurers, pharmacies, grocery delivery services, digital health apps, hospitals, etc. These will be incentivized to allow individuals to easily share their data via a well-documented OAuth2 API by:
- A share of income for using their data for research and development.
- An on-site instance of the OAuth2 server to retrieve required data from their on-premise databases.
- Reduction in their employee healthcare costs (one of their most significant expenses)
- Reduced costs of software development.
- Massive free marketing exposure through company branded plugins in the Plugin Marketplace.
- Revenue derived from their plugins in the Plugin Marketplace.
Disease advocacy nonprofits will benefit from promoting studies to their members by:
- Furtherance of their mission to reduce the incidence of chronic illnesses.
- Member engagement more productive than the traditional charity walk.
- A reduction in healthcare costs due to discovering new ways to prevent and mitigate chronic illnesses.
- Furtherance of their stated reason for existence to protect and promote the general welfare.
- Their duty to protect the rights of individuals' data. To fulfill this, they must require businesses in possession of it to give them the ability to access and share their data via a well-documented OAuth2 API
- Cost-savings from international cost-sharing by using global open-source software.
- Epidemiological discoveries on the effectiveness of different public health regulations between nations.
- Gitcoin bounties for specific tasks
- Encoding git commits with NFTs entitling the developer to ongoing royalties in proportion to their contributions.
- Dework bounties for tasks
- Other benefits - depending on the involvement
CureDAO is a laboratory consisting of many experiments.
It's a global laboratory where the 7 billion human "natural experiments" are conducted, revealing the effects of various factors on human health and happiness.
It's an experiment to determine if a new model for clinical research using real-world data can more effectively reduce the global burden of chronic illness.
It's an experiment to see if a new economic model called Collaborationism can reward the creation of open-source "public goods" and overcome the failures of Capitalism and Communism.
It's an experiment to determine if a direct democracy can produce better results than traditional hierarchical command and control organizations.
Given the unprecedented nature of such a project, each working group will constantly be experimenting with new ways to execute this mission. We recognize the importance of using real-world evidence to improve human health. Execution within the working groups should take the same data-driven approach to manage their area of the overall mission.
Accordingly, the organization is composed of three primary components.
- Citizen Scientists - CureDAO is an open and permissionless organization. Anyone has the right to earn their Citizenship through the contribution of labor or resources. In exchange, the Citizen Scientist will receive CureDAO tokens granting full governance rights over the actions of DAO Lab Staff
- DAO Laboratories - Internal working groups that carry out the Citizen Scientists' wishes
- External Service Providers - Individuals or entities outside the DAO deemed necessary to carry out the Citizen Scientists' wishes.
The dFDA could provide innovative tools, resources, and frameworks, the dFDA empowers Contract Research Organizations, Certifying Agencies, and Regulatory Agencies to perform their roles more effectively, accelerating safety and innovation.
- dFDA Governance Protocol - By implementing a continuous improvement process and a Futarchical Voting mechanism, the dFDA aims to enhance the quality of drug approvals and health policies.
- Regulatory Enhancements - The ideal framework for drug approvals aims to harness the collective intelligence of a diverse and knowledgeable crowd, ensuring rigorous, transparent, and inclusive decision-making processes and algorithmic optimization of outcomes using quantititative cost benefit analysis of every intervention for each condition
- Support of Real World Evidence - Large-scale efficacy trials based on real-world evidence, utilized prior to the pharmaceutical industry-driven randomized controlled trials mandated post-1962, were more effective in improving health outcomes, as evidenced by a consistent increase in human life expectancy during their implementation.
- dFDA Legal Structure - In considering the optimal legal structure for the dFDA, it is crucial to evaluate the advantages, disadvantages, and suitability of various options to ensure that the organization can fulfill its mission effectively while remaining compliant with legal and regulatory requirements.
- Life Force NFTs - Gamification to Incentivize Healthy Behaviour with Life Force Score. NFT's with an avatar and Life Force Score metadata updated daily based on performing healthy activities, such as having a good sleep schedule, hydrating, and exercising.
- DeSci Exchange - A free market for personal data in the form of an embeddable SDK with a configurable transaction fee for the apps embedding it.