Create a network of state-level FDA agencies, each with authority over their jurisdiction.
Federal FDA becomes a coordinating body, setting minimum standards and facilitating inter-state cooperation.
Break down the FDA into specialized divisions for different product categories (e.g., pharmaceuticals, medical devices, food safety).
Each division operates semi-autonomously with its own review processes and experts.
Implement a blockchain-based voting system for major regulatory decisions.
Qualified experts from academia, industry, and government can participate in decision-making processes.
¶ 4. Open Data and Transparency
Create an open data platform where all non-confidential regulatory data is publicly accessible.
Use distributed ledger technology to ensure data integrity and traceability.
Develop AI systems to assist in the initial screening of applications and adverse event reports.
Human experts make final decisions, but AI streamlines the process.
Establish a framework for decentralized clinical trials using telemedicine and wearable devices.
This allows for more diverse patient populations and faster data collection.
Create local community boards that provide input on regulatory decisions affecting their areas.
These boards can flag local concerns and provide context for regulatory decisions.
Implement a token-based incentive system to reward participants who contribute to the regulatory process (e.g., reviewing applications, reporting adverse events).
Establish protocols for seamless collaboration with other decentralized regulatory bodies (e.g., EPA, USDA) on overlapping issues.
Design the system to be interoperable with international regulatory bodies, facilitating global harmonization of standards.
Amend the Federal Food, Drug, and Cosmetic Act to allow for this decentralized structure.
Create a new "Decentralized FDA Act" that outlines the legal basis for this new structure, including:
Jurisdiction of state-level agencies
Authority of the blockchain-based voting system
Legal standing of AI-assisted decisions
Privacy protections for open data
Liability frameworks in this decentralized model