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CureDAO is a decentralized alliance of individuals, government, businesses, and nonprofits devoted to the minimization of suffering. |
We are creating an open-source framework that overcomes the traditional economic barriers to cooperation and data-sharing in digital health to achieve this.
It consists of two primary components:
-
An Open-Source Platform for Health Data:
- Storage
- Security
- Access Control
- De-identified Data Sharing
-
An Open Plugin Ecosystem enabling anyone to create or use plugins that facilitate:
- Data from any data source
- New Clinical Discoveries through machine learning
- Personalized Real-Time Decision Suggestions to most effectively treat and prevent diseases
- Data Format Transformation to enable interoperability with any system or application
- Patient Management
- Decentralized Clinical Trial Management
- Precision Medicine
- Large-scale, Low-cost Research to discover new ways to prevent and treat diseases
It 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.
Hey, you! 👀
CureDAO is open to anyone interested in preventing suffering and death from chronic diseases and degenerative diseases. Our success in this mission will be an exponential function of the participation of people like you. 🚀
Creating a new software ecosystem for health data not only requires developers but anyone with skills in:
- User interface and user experience design
- Project management
- Communications and marketing
- Web3 technologies
- Business development
- Life sciences
- Medicine
- Data science
Our main philosophy is: It's not what you CAN do but what you WANT to do.
- Introduction and Challenges
- Solution
- Platform
- Incentivization
- Organization
- Tokenomics
- Revenue
- Legal Framework
- Privacy
- Ecosystem
- Roadmap
- References
150,000 people die every single day from preventable diseases. For perspective, this is equivalent to:
Over 2 billion people are suffering from chronic diseases.
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".
Today, there are about 10,000 known diseases afflicting humans. There are as many untested compounds with drug-like properties as there are atoms in the solar system (166 billion). If you multiply the number of molecules with drug-like properties by the number of 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 what is left to be known.
It takes over 10 years and $2.6 billion to bring a drug to market (including failed attempts). (https://www.semanticscholar.org/paper/Innovation-in-the-pharmaceutical-industry%3A-New-of-DiMasiGrabowski/3275f31c072ac11c6ca7a5260bd535720f07df41)
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.
Using the current research system, it costs $41k per subject in Phase III clinical trials. As a result, there are only sufficient incentives to research patentable molecules.
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. If a drug is effective for other diseases after the patent expires, there isn't a financial incentive to get it approved for the other diseases.
No Long-Term Outcome Data
Under the current system, 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.
Negative Results aren't Published
Pharmaceutical companies that sponsor research, tend to only report “positive” results. That leads to poor health outcomes and companies wasting money on conducting the same research.
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.
There has been an explosion in digital health with more than 350,000 new digital health apps. These innovations have produced a 50-fold growth in health data.
Despite this growth, we've seen increased costs and disease burden, and decreased life expectancy.
The reason is incentives.
The isolated health data can only tell us about the past. For example, dashboards filled with descriptive statistics such as our daily steps or sleep.
However, by consolidating the data, using existing clinical research findings, and applying machine learning, we may receive personalized health suggestions.
There are more than 350,000 health apps and each costs an average of $425,000 to develop. Most have significant overlap in functionality, which represents a cost of $157,500,000,000 on duplication of effort. If these efforts were combined, theoretically, 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.
CureDAO will provide data providers with an onsite, easily provisionable OAuth2 API server to facilitate data sharing. That will allow individuals to share their data anonymously.
Solution: How DAOs Overcomes the Free-Rider Problem
- Currently, governments spend billions funding closed-source propriety health software. The Public Money, Public Code initiative, requires governments to recognize software as an open-source public good.
- By encoding contributions to the project with NFTs, we guarantee ongoing compensation for data and software.
The solution is to use the oceans of real-world evidence to discover new cures.
An in silico model of human biology can be developed to discover new interventions and their personalized usage.
We can achieve it by viewing the human body as a black box with inputs and outputs. We can apply predictive machine learning models to stratified groups based on the following data:
- Genomic
- Transcriptomic
- Proteomic
- Metabolomic
- Microbiomic
- Phenotype
- Diseasomic
- Pharmacomicrobiomic
- Pharmacogenomic
- Foodomic
- Exposome
This will enable the discovery of the full personalized range of positive and negative relationships for all factors without a profit incentive for traditional trials.
- Diagnostics - Data mining and analysis to identify causes of illness
- Preventative medicine - Predictive analytics and data analysis of genetic, lifestyle, and social circumstances to prevent disease
- Precision medicine - Leveraging aggregate data to drive hyper-personalized care
- Medical research - Data-driven medical and pharmacological research to cure disease and discover new treatments and medicines
- Reduction of adverse medication events - Harnessing of big data to spot medication errors and flag potential adverse reactions
- Cost reduction - Identification of value that drives better patient outcomes for long-term savings
- Population health - Monitor big data to identify disease trends and health strategies based on demographics, geography, and socioeconomic
An open-source core platform and plugin framework transform data into clinical discoveries.
The functional scope of the core platform includes:
- Aggregating
- Managing
- Processing
- Storaging
health data from different sources.
Create a foundational technology layer, for any digital health application, providing better interoperability, portability, availability, analysis, and security of the data.
- EHR Systems for healthcare providers
- User-centered dashboards for personal health management
- Data sharing with anyone
- 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
- Niche health applications with specific requirements
The platform consists of two primary components:
- Open-Source Core
- It primarily consists of user authentication, data owner access controls, data storage, data validation, and an API for storage and retrieval.
- The DAO compensates for core contributions.
- Plugin Framework
- Plugins provide data import from specific sources, data mapping to various formats, data analysis, data visualization, and notifications.
- These are either free or monetized by their creator.
- Some might be integrated into the core based on a community voting.
The application programming interface (API) includes an OpenAPI specification for receiving and sharing data with the core database. Software development kits (SDK’s) available for 3rd party applications, allow interaction with the API. SDK’s lets developers implement automatic sharing options in their applications.
Separate plugins enable spreadsheet upload/import and scheduled imports from existing third-party APIs. The API connector framework allows the ongoing regular import of user data after a single user authorization.
- Laboratory and home tests
- Wearables
- Health apps
- User reported symptoms and intervention application
- Electronic Health Records
- Imaging
- Questionnaires
- Functional tests
- Environmental and context data
- Life events, calendars, social media, and lifestyles
- Digital biomarkers
- Locations
- FHIR
- OpenEHR
- LOINC
- SNOMED
- RXNORM
- MedDRA
- ICD-10
- Open mHealth
To preserve originality, in the case of data processing errors or protocol changes, the ingested raw files like CSV files, PDF files, and the raw API responses, are stored separately in a binary data and file storage system. Data is encrypted and stored in its raw format, in flat files, on a secure cloud provider, defined in the framework instance core settings.
Makes the standardized structured storage of health data and the envisioned queries possible. The data is ingested from files or API requests and mapped from many standards and proprietary formats into a standard schema.
The data validation middleware validates the data before it is stored in the time-series database.
To map data from different formats into a standardized one, which is suitable for analysis, requires a reference database with tables of definitions and descriptions for the data mappers and by the API for displaying it in applications. They include biomarkers, health-related variables, interventions, therapies, outcomes, conditions, etc. Examples of reference databases include LOINC, RXNORM, and ICD-10.
The Unified Code for Units of Measure (UCUM) system is used to include all units of measures in international science.
After validation and mapping, the data is stored in a standardized and structured time-series database.
Data is owned by the individual who generated it, throughout the entire data life-cycle.
Ownership management functionalities allow individuals to manage their data and access control settings for sharing purposes.
It allows them to:
- View and access their data
- View the OAuth clients.
- Modify read/write permissions for specific OAuth clients
- Restrict data access to specific users, groups, researchers, and applications
- Restrict data access to specific data categories, types, and markers
- Restrict time and expiration of data access
- Configure security measures such as encryption or 2-factor authentication
- Overview of statistics of data
- Export stored data or original files
- Delete data
This feature can be used by user-centered applications and dashboards for personal health management, data sharing with healthcare providers, participation in trials, and research.
The handling of the data alongside its attached value is built natively into the core. Value stream management functionalities allow the exchange of data for value assets.
It allows them to:
- Individuals to share data and receive compensation
- Groups to sell insights for value assets
- Researchers to apply, formulate, and visualize the value of data sets
- Value data for administration purposes
- Create a value-based feedback loop for research or behavioral outcomes
Data Value Scenarios:
- Raw data sets or streams of individuals
- Cohort raw data sets of grouped individuals
- Interpreted data, scores, and recommendations
- Generated insights and IP out of data analysis
- Aggregated data based on the requested needs
- Phenotypic, demographic, lifestyle, condition, and environmental contexts
This feature is used for exchanging data on marketplace applications or clinical trial platforms.
3rd party plugins can interact with the core and provide additional functionality. They are free or monetized by their creator.
The impact of effective and detailed analysis:
- The discovery of root causes of diseases
- Development of new interventions
- The precise and personalized application of these interventions
Data Analysis Plugins 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
- Effect Size Quantification
- Quantification of effect sizes of all factors on symptom severity
- Optimal Daily Values
- Determination of the personalized optimal dosages of nutrients or medications
- Cost-Benefit Analysis
- Determination of the most cost-effective interventions
That mitigates the incidence of illnesses, by informing the user of symptom triggers, such as dietary sensitivities. It also assists patients and clinicians in assessing the effectiveness of treatments. Further, large cohort clinical analysis might reveal new molecules for healthy longevity.
Data visualization plugins convert raw data into useful insights for individuals or multiple subjects. Some ways to visualize data are scatter plots, timeline charts, heatmaps, or novel ways like those in the following outcome labels. Visualizations can be embedded in studies, publications, or personal dashboards.
Example Data Presentation Plugins
- Outcome labels
- Predictor search engines
- Root cause analysis reports
- Observational studies
- Real-time decision support notifications
Many applications and service providers offer direct exchanges of structured health data through an API, which upon user authentication allow access to automated and scheduled exports of the generated data.
Until the success of a common language for all types of health data and between all stakeholders, many API connecting plugins are necessary for this interoperability.
File importing plugins are needed for specific sources or devices, where the user only has access to raw files. Types of files include spreadsheets, PDFs, and raw genomic data.
How we use the DAO structure to reward data sharing and open-source collaboration.
CureDAO provides each participant with more value than their amount of effort.
- Actionable insights to prevent and mitigate illnesses.
- Income for the use of data for research and drug development. The data is encoded into non-fungible tokens (NFTs) and 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.
- An eventual reduction in their employee healthcare costs (one of their most significant expenses) resulting from the discovery of new ways to prevent and mitigate chronic illnesses.
On top of the incentives for businesses listed above, the following incentives will be provided to digital health businesses which enable data sharing:
- A license to use a white-labeled version of the framework. This will dramatically reduce the costs of software development. These reduced costs will allow them to focus on innovating their unique value proposition, making them more competitive in the market.
- Massive free marketing exposure through company branded plugins in the Plugin Marketplace.
- Revenue derived through subscription or licensing agreements for the usage of their plugins in the Plugin Marketplace.
Disease advocacy non-profits will be incentivized to promote observational studies through the anonymous donation data by their members by:
- Accelerated furtherance of their mission to reduce the incidence of chronic illnesses.
- A new method of member engagement more motivating and productive than the traditional charity walk.
Governments will be incentivized by:
- A reduction in government healthcare costs due to the discovery of new ways to prevent and mitigate chronic illnesses.
- Furtherance of their stated reason for existence to protect and promote the general welfare. General welfare is defined as the overall health and happiness of the population.
- 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 using open-source software. All publicly funded digital-health software projects should be free, secure, and open-source. Currently, the majority of government contracts go to closed-source and proprietary software. This leads to massive waste as governments worldwide are paying to reinvent the wheel instead of sharing the costs. Shockingly, there is even a great deal of wasted money on duplicated software contracts between different agencies within the same governments.
- International cooperation for all public health efforts to reduce wasted duplication of effort and take advantage of natural experiments resulting from differing public health regulations between nations.
- Epidemiological discoveries would be made by allowing citizens to anonymously share their data in a global database. This will enable us to take advantage of natural experiments resulting from differing public health regulations between nations. For instance, 27 countries have banned the use of the pesticide glyphosate due to concerns about the health effects. If no overall change in the health of the populations is observed, it will suggest that the health concerns may be unfounded.
Citizens of the DAO will be incentivized to contribute to the development of the platform by:
- Gitcoin Bounties for specific tasks
- Encoding git commits with NFTs entitling the developer to ongoing royalties in proportion to their contributions.
Compensation for various tasks will be determined democratically by voting.
CureDAO is a laboratory consisting of many experiments.
It’s a global laboratory where the 7 billion human “natural experiments” revealing the effects of various factors on human health and happiness are conducted.
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 be constantly experimenting with new ways to execute this mission. We recognize the importance of using real-world evidence in the mission of improving human health. Execution within the working groups should take the same data-driven approach to execute their area of the overall mission.
Accordingly, the organization is composed of three primary components
- Citizen Scientists - DAO data donors or token holders with voting rights
- DAO Laboratories - Working groups consisting of a Lab Manager who helps Lab Technicians carry out the duties of their Laboratory in accordance with the will of the Citizen Scientists.
- External Service Providers - Individuals or entities outside the DAO deemed necessary to carry out the will of the Citizen Scientists.
As 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 aDAO Governance Tokens granting full governance rights over the actions of DAO Lab Staff.
Citizens may participate in:
- Governance Debate on Discourse
- Token-Based Voting by staking their Governance Tokens on smart contracts
Lab Staff comprises the Laboratory working groups who carry out the will of the DAO. Citizens can apply to join Laboratories based on their experience or expertise. Laboratories may elect Lab Managers, who are responsible for coordinating between Laboratory Technicians. Laboratories may decide to create incentives for their Citizen Scientists in a variety of forms, including paying them for services or creating bounties.
In cases where Lab Staff are paid, Citizens may choose to compensate them with any of the following:
- DAO Governance Tokens
- Ethereum
- Fiat Currency
- Other Incentives
The initial Laboratories will be created to carry out the following primary functions:
- Governance Lab - Changes governance and how proposals are created and deployed. Handles technical aspects of DAO token creation and distribution. Develops the DAO’s smart contracts.
- Legal Lab - Handles legal matters regarding business structure, health data, liability issues, and business contracts.
- Coordination Lab - Handles operational matters such as human resources, compensation, project management, and onboarding. Provides resources for Lab Staff.
- Communications Lab - Promotes community engagement with DAO and the broader world. Promotes DAO’s presence in the public discourse. Includes designers, writers, social media experts, and any other relevant skills.
- UI/UX/Dev Lab - Creates a user-friendly interface for the platform front end. Implements the platform back end and user interface.
- Collab Lab - Coordinates partnerships between individuals and organizations.
- Fin Lab - Facilitates financing of DAO projects.
- Data Lab - Integrates data from various sources and formats. Conducts research on data science and machine learning. Handles analytics required for informing all other labs of the effectiveness of their processes.
- Med Lab - Focuses on formal clinical research and partnerships.
Service providers provide services to CureDAO, such as:
- development work
- IP sourcing and conversion to NFTs
- marketplace services
- public relations
- legal services
- data science
- customer support
- marketing
CureDAO will contract service providers and pay for their services with any of the following:
- DAO Governance Tokens
- Ethereum
- Fiat Currency
- Other Incentives
The DAO will utilize Laboratory working groups which use a scientific experimentation-based approach to effectively carrying out the will of its Citizen Scientist voting members.
The dCURES token is the economic driver of the CureDAO platform. dCURES is obtained by contributing work, data, IP, or funds to CureDAO. The core function of $dCURES is to incentivize data sharing and open-source collaboration.
dCURES tokens grant Citizen Scientists the right to decide:
- How data will be monetized
- How the platform will be monetized
- How contributors to the platform will be compensated
- How the platform is architected
- The terms on which strategic partnerships will be created
- Which Gitcoin Grants or Bounties receive funds
- What IP contributors will receive funds and how much
- How internal DAO Laboratories budgets and projects are funded
- How CureDAO is governed
- How the CureDAO treasury will be managed
30% of the total supply will go to the community during the initial genesis, and 70% remain unminted and available in CureDAO’s treasury to ensure the sustainability of the platform. Members may elect to issue further tokens at any time to the public or select strategic entities and funders. Furthermore, CureDAO may allocate tokens to various incentive mechanisms as proposed herein or by the community.
The goal of CureDAO is for every human on earth to share the natural experiments that define their existence. The world’s population is projected to peak at 9.4 billion around 2070. To enable everyone to become a Citizen Scientist, upon genesis, 9.4 billion $dCURES tokens will be created as ERC20 tokens controlled by CureDAO. CureDAO’s token begins unable to exceed that number - it is a capped ERC20 token. Our core collective mission at This token supply may only increase if the world population exceeds 9.4 billion.
The genesis distribution event will make 10% of CureDAO’s total token supply available to interested participants using a fair and open smart contract auction on the Ethereum blockchain.
| Token Quantity | Fraction of Total | Recipient |
|---|---|---|
| 940M | 10% | Community Genesis |
| 940M | 10% | Service Providers (Voted) |
| 940M | 10% | DAO Laboratories (Voted) |
| 6.58B | 70% | Treasury |
| 9.4B | 100% | Total |
Since CureDAO’s genesis operates via a public auction, the community decides the initial token price. We estimate a minimum of $5,000,000 will be required to support the first iteration of the platform.
CureDAO will be fully decentralized and community-owned from inception. No entity will own $dCURES tokens before the genesis contribution event.
dCURE’s genesis contribution event will run via a fair launch public auction, granting all successful auction participants equal governance rights per $dCURES. Once issued the first 10% of tokens, the CureDAO core community will begin voting on the first governance proposals to allocate additional tokens to DAO Laboratory working groups and service providers.
The approval of these allocations to DAO Laboratories, contributors, and service providers is at the full discretion of genesis Citizen Scientists and their approval. They form the core of CureDAO’s decision-making and executive body.
CureDAO generates revenue streams to compensate IP and data contributors sustain and grow the project.
The biotech and pharmaceutical industries are two of the fastest growing sectors of the U.S. economy. 
These factors all point to a massive potential for the revenue necessary to sustain this project. The primary sources of revenue include:
- Sale of high-frequency longitudinal de-identified data to
- pharma for drug discovery
- research institutions for funded studies
- Grants from governments modernizing their programs to take advantage of real-world data
- Digital health companies wishing to accelerate product development using existing white-label software or hosted software-as-a-service (SaaS) options
Digital health companies can save months of development time and tens of thousands of dollars by 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.
106,000 people die annually in the U.S. from properly prescribed drugs. The number of people having in-hospital, adverse reactions to prescribed drugs to be 2.2 million per year. The total number of deaths caused by conventional medicine is 783,936 per year. Pharmaceutical companies spend over $2 billion a year on over 314,000 events attended by doctors.
Initial sponsor applications focus on tracking adverse reactions to the medications known to produce the most adverse reactions. Using our treatment, and symptom tracking application can reduce the number of deaths and costs of intervention by alerting patients and their practitioners to conditions before they become irreversible. Additionally, the opportunity to meet and promote these applications to physicians would also serve as a novel new way for pharmaceutical manufacturers to connect with physicians.
This technology can also be used to dramatically drive down the costs of pharmaceutical post-marketing research. Sponsor apps using the platform can be provided to hospitals, insurers, and pharmaceutical companies who wish to improve patient outcomes and potentially gather patient-authorized anonymized patient data. Pricing would follow a subscription model starting at $2 per end-user per month.
Electronic health records (EHRs) can be used to support randomized controlled trials (RCTs). A meta-analysis found that the per-patient cost in EHR-supported trials varied from $44 to $2000. Using NFTs we can link donated data to the patient so that they may receive ongoing royalty payments for the use of their data once new interventions reach the market. A fraction of the revenue, to be determined democratically by the patients and DAO Citizens, may be directed to the DAO treasury to sustain the project.
Although 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 utilized by for-profit entities. Licensing fees will be negotiated such that a fraction of the profits generated by the licensee's use of the project.
This will ensure that anyone can afford to use it, while still providing compensation to the developers of the platform.
A decentralized autonomous organization, or a “DAO,” is an “organization” encoded as a transparent computer program, controlled by the organization members, and not by a central corporate entity.
In order to facilitate the entering of contracts, CureDAO will utilize an unincorporated nonprofit association (UNA) as a ‘wrapper’. Unincorporated nonprofit associations are broadly defined and, in many jurisdictions, can consist of just a few people agreeing to work, either orally or with an agreement, on a charitable endeavor together.
The Uniform Unincorporated Nonprofit Association Act (UUNAA) allows the DAO members to loan IP to the UNA. Then DAO members may be repaid with interest from the UNA.
A potential means by which personal liability could be limited for the members of the DAO may be through the creation of a public benefit limited liability company. The downside is that the DAO would need to more formally adopt a corporate structure than a UNA requires. However, it would also create limited liability for its members as a matter of law.
To protect privacy, CureDAO will use deidentification and obfuscated but equivalent data synthetically derived from actual patient data.
Data de-identification is the process of eliminating Personally Identifiable Data (PII) from any document or other media, including an individual’s Protected Health Information (PHI). The HIPAA Safe Harbor Method is a precise standard for the de-identification of personal health information when disclosed for secondary purposes.
ARX is an open-source tool that anonymizes sensitive personal information. It supports a range of privacy and risk models, techniques for data transformation, and techniques to analyze the utility of output data.
The deid software package includes code and dictionaries that automatically locate and remove PHI in free text from medical records. It was developed using over 2,400 nursing notes that were methodically de-identified by a multi-pass process including various automated methods as well as reviews by multiple experts working autonomously.
Synthea is an open-source, synthetic patient generator that models the medical history of synthetic patients. Our mission is to provide high-quality, synthetic, realistic but not real, patient data and associated health records covering every aspect of healthcare. The resulting data is free from cost, privacy, and security restrictions, enabling research with Health IT data that is otherwise legally or practically unavailable.
- Create Whitepaper, Website, Media presence
- Define collaborators and partners (DAO infrastructure, health data tech)
- Setup DAO architecture and infrastructure
- Build community, social media content
- Fundraising phase (Genesis)
- Collaborators vote for core features
- Build MVP along side use in show case trial
- Closed Testing with collaborators
- Release V1 of the Software Framework
- Open Testing with partners
- Integrate with other tech architecture (storage providers, data marketplaces, analysis software, etc.. )
- Integrate with operating health data standards and Electronic Health Record
- Build show case plugins
- Release V2 of the Software Framework
- Promote broader usage
Accompany pilot programs and partners for applications in the fields:
- Open shared health database for research access
- Trials platform with participation royalty payback
- User centered health management
- Algorithm and scores development
- Data marketplaces
- Manage personal health to prevent disease
- Share health data to research
- Get to know new insights
- Take newly developed interventions
- Educate loved ones about longer health span
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.