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💊 OBJECTIVE: MAXIMUM CURE ACCELERATION 🚀 |
We are a borg-like entity devoted to minimizing suffering by any and all means necessary. |
Billions of people are suffering needlessly because the current system of clinical research, diagnosis, and treatment sucks because:
- ⏳ Counterproductive Regulatory Barriers to clinical research block life-saving treatments by 7-12 years
- 🚫 97% of patients are excluded from clinical trials
- 💰 Drug development costs of $2.6B are passed on to patients
- ⏱️ Terminal patients wait 4 years for breakthrough therapy approvals
- 📊 The system ignores real-world evidence about effective treatments
The Cure Acceleration Act creates:
- ✅ Universal Trial Access - Every person's right to try safe treatments
- 🤖 Decentralized Autonomous FDA - Free, open infrastructure for real-world evidence collection
- 🏆 50/50 Health Savings Sharing Rewards - Multi-billion dollar incentives for developing actual cures instead of lifetime drug subscriptions
- 📈 Real-Time Analysis of the positive and negative effects of every food, supplement, drug, and treatment on every measurable aspect of human health and happiness
- 🌐 Global Access - Decentralized trials anyone can participate in from home
👉 Read the Full Cure Acceleration Act
The current system of clinical research, diagnosis, and treatment is failing the billions of people are suffering from chronic diseases.
👉 Problems we're trying to fix...
By harnessing global collective intelligence and oceans of real-world data, we hope to emulate Wikipedia's speed of knowledge generation.
👉 How to generate discoveries 50X faster and 1000X cheaper than current systems...
So in the 90's, Microsoft spent billions hiring thousands of PhDs to create Encarta, the greatest encyclopedia in history. A decade later, when Wikipedia was created, the general consensus was that it was going to be a dumpster fire of lies. Surprisingly, Wikipedia ended up generating information 50X faster than Encarta and was about 1000X cheaper without any loss in accuracy. This is the magical power of crowdsourcing and open collaboration.
Our crazy theory is that we can accomplish the same great feat in the realm of clinical research. By crowdsourcing real-world data and observations from patients, clinicians, and researchers, we hope to generate clinical discoveries 50X faster and 1000X cheaper than current systems.
- 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
This is a very high-level overview of the architecture. The three primary primitive components of the framework are:
- Data Silo API Gateway Nodes that facilitate data export from data silos
- PersonalFDA Nodes that import, store, and analyze your data to identify how various factors affect your health
- Clinipedia that contains the aggregate of all available data on the effects of every food, drug, supplement, and medical intervention on human health.
The core characteristics that define the FDAi are:
- Modularity - a set of modular libraries and tools that can be reused in any project
- Protocols - an abstract framework of core primitive components rather than a specific implementation
- Interoperability - a directory of existing open-source projects that can be used to fulfill the requirements of each primitive or component
- Collective Intelligence - a collaborative effort, so please feel free to contribute or edit anything!
FDAi Gateway API Nodes should make it easy for data silos, such as hospitals and digital health apps, to let people export and save their data locally in their PersonalFDA Nodes.
👉 Learn More About Gateway APIs
PersonalFDA Nodes are applications that can run on your phone or computer. They import, store, and analyze your data to identify how various factors affect your health. They can also be used to share anonymous analytical results with the Clinipedia FDAi Wiki in a secure and privacy-preserving manner.
PersonalFDA Nodes are composed of two components, a Digital Twin Safe and a personal AI agent applies causal inference algorithms to estimate how various factors affect your health.
A local application for self-sovereign import and storage of personal data.
👉Learn More or Contribute to Digital Twin Safe
Personal AI agents that live in your PersonalFDA nodes and use causal inference to estimate how various factors affect your health.
The Clinipedia wiki should be a global knowledge repository containing the aggregate of all available data on the effects of every food, drug, supplement, and medical intervention on human health.
👉 Learn More or Contribute to the Clinipedia
A key component of Clinipedia is Outcome Labels that list the degree to which the product is likely to improve or worsen specific health outcomes or symptoms.
👉 Learn More About Outcome Labels
A collective intelligence coordination platform is needed for facilitating cooperation, communication, and collaborative actions among contributors.
👉 Learn More or Contribute to the Collaboration Framework
We'd love your help and input in determining an optimal roadmap for this project.
👉 Click Here for a Detailed Roadmap
Our goal is to develop FAIR (Findable, Accessible, Interoperable, and Reusable) data and analytical tools that can be used by any regulatory agencies, businesses, non-profits or individuals to quantify the effects of every food, drug, supplement, and treatment on every measurable aspect of human health and happiness.
The Monorepo is to achieve maximum interoperability and discoverability between the various projects to maximize the speed of development and minimize costs. This can be done by modularizing the codebase into libraries and plugins that can be shared between the various projects.
We've got a monolithic centralized implementation of the FDAi at apps/dfda-1 that we're wanting to modularize and decentralize into a set of FAIR libraries and plugins that can be shared with other apps.
Currently, the main apps are the Data Collection, Import, and Analysis App and the Journal of Citizen Science.
- Data Collection
- Data Import
- Data Analysis
- Real-Time Decision Support Notifications
- No Code Health App Builder
- Personal AI Agent
- Browser Extension
Collects and aggregate data on symptoms, diet, sleep, exercise, weather, medication, and anything else from dozens of life-tracking apps and devices. Analyzes data to reveal hidden factors exacerbating or improving symptoms of chronic illness.
Web and mobile push notifications with action buttons.
By using the Browser Extension, you can track your mood, symptoms, or any outcome you want to optimize in a fraction of a second using a unique popup interface.
The Analytics Engine performs temporal precedence accounting, longitudinal data aggregation, erroneous data filtering, unit conversions, ingredient tagging, and variable grouping to quantify correlations between symptoms, treatments, and other factors.
It then pairs every combination of variables and identifies likely causal relationships using correlation mining algorithms in conjunction with a pharmacokinetic model. The algorithms first identify the onset delay and duration of action for each hypothetical factor. It then identifies the optimal daily values for each factor.
👉 More info about data analysis
More info about outcome labels
More info about real time decision support
👉 More info about the predictor search engine...
👉 More info about observational studies...
🤝 Join Us: Whether you're a developer, researcher, health professional, regulatory, or simply passionate about health innovation, your contribution can make a monumental difference!
Code or documentation improvements are eternally appreciated!
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.
If you have any questions or need help, please create an issue instead of emailing us so that others can benefit from the discussion.