Why to Include a Decentralized Trial Platform in the Long COVID Moonshot Bill

The Long COVID Moonshot Bill would provide $1B+ in annual research funding for Long COVID.

This is the perfect opportunity to radically modernize and accelerate medical research through a faster, cheaper, open and decentralized model of determining the safety and effectiveness of treatments.

The inclusion of a standardized decentralized trial platform in the Long COVID Moonshot bill is not just a technological enhancement—it’s a transformative approach that can significantly accelerate research, reduce costs, and democratize patient participation in clinical trials. Here are the compelling reasons why this platform should be an integral part of the legislation:

Dramatic Reduction in Clinical Trial Costs

  • Cost Efficiency: Traditional Phase 1-4 clinical trials are prohibitively expensive, averaging around $60 million. By implementing a standardized decentralized trial platform, we can reduce these costs to approximately $2.4 million per trial—a 96% reduction.
  • Resource Optimization: Lower costs mean that the same amount of funding can support 25 times more trials, exponentially increasing the potential for discovering effective treatments.

Here’s a breakdown of the specific potential savings. There’s more detail in this spreadsheet:

Itemized Cost NameCurrent Cost Phase 1-4Decentralized Automated Trial CostExplanation of Cost Reduction
Data Management Costs$198,014$10,000Automated data collection and AI-driven analysis
Cost Per IRB Approvals$324,081$5,000AI-generated protocols with built-in ethical considerations
Cost of IRB Amendments$6,347$0AI dynamically adjusts protocols within predefined ethical boundaries
SDV Costs$1,486,250$0Blockchain-like technology ensures data integrity
Patient Recruitment Costs$805,785$5,000Automated matching of patients to trials via EHR integration
Patient Retention Costs$76,879$20,000Automated reminders and digital engagement tools
RN/CRA Costs$2,379,605$50,000Mostly automated, with minimal human oversight
Physician Costs$1,966,621$100,000AI interprets most data, physicians review complex cases
Clinical Procedure Total$5,937,819$1,000,000Leveraging existing healthcare infrastructure, automated scheduling
Laboratory Costs$2,325,922$500,000Use of local labs, automated result reporting
Site Recruitment Costs$849,158$0No traditional sites needed in decentralized model
Site Retention Costs$4,461,322$0No traditional sites to retain
Administrative Staff Costs$7,229,968$50,000AI-driven administrative tasks
Site Monitoring Costs$4,456,717$0Automated data monitoring, no physical sites
Site Overhead$7,386,816$0No physical sites required
All Other Costs$17,096,703$100,000Drastically reduced miscellaneous costs
Drug Manufacturing and Distribution(Included above)$500,000Efficient production and direct-to-patient or pharmacy distribution
Technology Infrastructure(Included above)$100,000Costs for maintaining the AI system, servers, and user interfaces
Total$56,987,007$2,440,000

Acceleration of Treatment Discovery

  • Faster Trials: Automated systems streamline the trial process—from recruitment to data analysis—reducing the time required to conduct trials.
  • Increased Trial Volume: With reduced costs and streamlined processes, more trials can be conducted simultaneously, accelerating the pace at which new treatments are identified and brought to market.

Patient Right to Try and Discover the Best Available Treatments

  • Open Participation: By eliminating unnecessary exclusion criteria, the platform ensures that anyone can participate in trials unless there is a clear safety concern. This inclusivity increases sample sizes and diversity, leading to more generalizable and robust findings.
  • Patient Access to Information: The platform provides patients with personalized insights based on comprehensive data analyses, empowering them to make informed decisions about their health.

Standardization and Data Quality

  • Unified Protocols: Standardized study protocols and data collection methods facilitate the aggregation and comparison of data across multiple studies.
  • Improved Data Analysis: Advanced algorithms can apply causal inference techniques more effectively with high-frequency, standardized data, enhancing the reliability of conclusions drawn from research.

Enhanced Collaboration and Innovation

  • Open-Source Platform: Making the platform open source under the GPL license encourages collaboration among researchers, developers, and institutions. This collective effort can lead to continuous improvements and innovations.
  • Third-Party Integration: An OpenAPI specification with OAuth2 authentication allows for secure integration with third-party data sources (e.g., pharmacies, medical records, wearable devices), enriching the dataset and providing a more holistic view of patient health.

Addressing Waste and Duplication of Effort

  • Overcoming Fragmentation: Current research efforts are fragmented, with thousands of separate studies often reinventing the wheel. A centralized platform reduces duplication of effort and resources.
  • Automating the FDA Approval Processes: By collecting comprehensive, standardized data, the platform can streamline the pathway to regulatory approval for new treatments.

Economic and Public Health Benefits

  • Cost Savings for Healthcare Systems: More efficient trials and faster discovery of effective treatments can reduce long-term healthcare costs associated with managing chronic conditions like Long COVID.
  • Stimulating Innovation: Lower barriers to conducting research can encourage small and medium-sized enterprises to invest in developing treatments, fostering economic growth in the biotech sector.
  • Beyond Long COVID: While the immediate focus is on Long COVID, the platform is designed to facilitate research across various health conditions, maximizing the return on investment.

Ethical Responsibility and Public Trust

  • Transparency: Open-source code and open participation policies build public trust in the research process.
  • Equitable Access: Ensuring that treatments are researched and developed efficiently promotes equitable access to healthcare innovations, benefiting society as a whole.

Recommendations

  • Legislative Action: Amend the Long COVID Moonshot bill to explicitly include the development and implementation of the standardized decentralized trial platform as described.
  • Stakeholder Engagement: Collaborate with researchers, patient advocacy groups, technology experts, and regulatory bodies to ensure the platform meets the needs of all parties involved.
  • Funding Allocation: Allocate sufficient resources within the bill’s budget to support the development, deployment, and maintenance of the platform.
  • Pilot Programs: Initiate pilot studies to demonstrate the platform’s effectiveness, scalability, and impact on reducing trial costs and accelerating research outcomes.

Proposed DCT Amendment

Here is the proposed amendment to the “Long COVID Research Moonshot Act”:

Establishment of a Decentralized Trial Platform.

(a) In General.—The Secretary of Health and Human Services, acting through the Director of the National Institutes of Health and in coordination with the Commissioner of Food and Drugs, shall establish an open-source decentralized trial platform to facilitate and accelerate research on various health conditions, including but not limited to Long COVID.

(b) Platform Requirements.—The decentralized trial platform shall include:

  1. A comprehensive relational database to store and analyze:
  • (A) Clinical trial protocols for a wide range of health conditions.
  • (B) Observational and randomized control trial data related to various treatments and interventions.
  • (C) Interventional data related to the safety and efficacy of treatments for multiple health conditions.
  • (D) Any additional data deemed necessary by the Secretary for quantifying the safety and efficacy of treatments, including treatments, diet, lifestyle factors, and symptoms.
  1. An OpenAPI Specification and APIs to enable:
  • (A) Third parties such as pharmacies, grocery stores, supplement vendors, medical record systems, and others to register their applications.
  • (B) Secure sharing and access of patient data using OAuth2 protocols for authentication and authorization, in compliance with privacy regulations.
  • (C) Integration of data sources including purchase histories, medical records, symptom tracking apps, and other relevant data to enhance research and analysis.
  • (D) Developers to build applications that can interact with the platform, expanding its functionality and reach.
  1. Advanced algorithms to quantify safety and efficacy:
  • (A) Quantify the safety and efficacy of treatments based on time-series data.
  • (B) Perform quantitative cost-benefit analyses to inform decisions on potential treatments.
  • (C) Generate meta-analyses of all available data to provide patients with information on the most effective treatments for their specific conditions.
  • (D) Publish analyzed data in a user-friendly format, including:
    • (i) A ranked list of effective treatments for various health conditions.
    • (ii) Information on factors that may exacerbate or alleviate symptoms.
  1. An automated system for clinical trial creation and participation, allowing:
  • (A) Researchers to create trials by entering interventions and desired outcomes.
  • (B) Automatic generation of protocols based on provided information.
  • (C) Patients to view all available trials and join instantly through the platform, with no exclusions unless there is a clear safety concern.
  • (D) Automated scheduling of medication delivery and necessary lab tests for trial participants.
  • (E) Direct submission of survey responses and relevant data by patients through the platform.

(c) Open Participation Policy.—No individual shall be excluded from participating in any trial facilitated by the platform unless there is a clear safety argument not to. Exclusion criteria, if necessary for specific analyses, shall be applied during data analysis by segmenting data for specific cohorts rather than restricting participation.

(d) Open Source Requirement.—The entire codebase for the decentralized trial platform, including the database structure, OpenAPI specifications, APIs, SDKs, and AI algorithms, shall be made open source under the GNU General Public License to allow for community contributions, and facilitate adoption by other research institutions.

(e) Privacy and Security.—The Secretary shall ensure that the platform complies with all applicable privacy and security regulations, including HIPAA, while maintaining its open-source nature. OAuth2 protocols shall be utilized for secure authentication and authorization of third-party applications accessing patient data.

(f) Collaboration.—In developing and implementing the platform, the Secretary shall collaborate with relevant research programs, institutions, and stakeholders to maximize the platform’s effectiveness across various health conditions.


SEC. 302. Patient Access and Empowerment

(a) Treatment Efficacy Information.—The platform shall provide a user-friendly interface allowing any patient to:

  1. Input their specific symptoms and conditions, treatments, diet, and other factors.
  1. Receive meta-analyses of all available data showing the most effective treatments for their particular case.
  1. Access detailed information about potential treatments, including efficacy rates, side effects, and ongoing clinical trials.

(b) Clinical Trial Participation.—The platform shall enable patients to:

  1. Instantly join suitable clinical trials directly through the website, without exclusion unless a clear safety concern is present.
  1. Receive automated scheduling for medication delivery and required lab tests.
  1. Submit surveys and upload relevant health data directly to the platform.
  1. Track their progress and contribute to the overall body of research on various health conditions.

(c) Third-Party Integration.—The platform shall allow patients to:

  1. Authorize third-party applications—such as pharmacies, grocery stores, supplement vendors, and medical record systems—to share or access their data via OAuth2 authentication.
  1. Control their data-sharing preferences, including the ability to grant or revoke access to specific third-party applications at any time.

SEC. 303. Data Collection for FDA Approval

(a) Comprehensive Data Collection.—The platform shall be designed to collect and store all necessary time-series treatment and outcome data required to support FDA approval processes for treatments across multiple health conditions.

(b) Data Standardization.—The Secretary shall work with the FDA to ensure that data collected through the platform meets or exceeds the standards required for consideration in treatment approval decisions.


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