Appendix O โ€” ๐Ÿ“‹ HHS Policy Recommendations

This proposal recommends that the Department of Health and Human Services (HHS) sponsor an FDA-X Prize to incentivize the creation of an open-source, decentralized FDA (dFDA) platform. This platform would enable perpetual, patient-driven clinical trials accessible to anyone globally, eliminating inefficiencies in the current phased trial system. The proposal outlines strategies for redirecting NIH research funding, leveraging existing HHS authorities, and adopting outcome-based funding models to maximize trial participation without requiring new legislation. Additionally, it proposes the strategic reallocation of portions of Medicare and Medicaid funding under existing statutory provisions to support broader access to decentralized trials.

A critical component of this proposal is to clarify the potential for drug companies to set a per-participant price when creating trials on the dFDA Infrastructure. Under existing FDA regulations (21 CFR 312.8), companies may charge for investigational drugs to recover direct costs, including employee salaries. This means that drug companies could legally charge the NIH a per-participant price covering all operational expenses, such as manufacturing, distribution, and employee compensationโ€”without requiring pre-approval, provided they do not exceed cost-recovery limits. This structure would enable companies to sustain clinical trial operations while maintaining compliance with regulatory standards, promoting a scalable and sustainable ecosystem for perpetual trials.

Moreover, existing Medicare and Medicaid policies already permit reimbursement for routine patient costs in qualifying clinical trials. By aligning the dFDA Infrastructureโ€™s operational structure with these statutory frameworks, drug companies could expand access to experimental treatments, leveraging government funding mechanisms to cover essential costs. This approach ensures that trial sponsors can sustainably conduct large-scale studies while maintaining affordability and regulatory compliance.

Key Objectives

  1. Create a Decentralized FDA (dFDA) Platform:
  1. Enable Perpetual Trials:
  • Real-time, global patient participation
  • Automated matching of patients to trials
  • Dynamic protocol adjustments based on outcomes
  • Continuous monitoring rather than fixed phases
  1. Clarify Pricing Mechanisms for Trial Sponsors: Allow drug companies to set per-participant prices charged to NIH, covering direct costs (including employee salaries) without profit generation, consistent with FDA regulations (21 CFR 312.8).
  2. Redirect NIH Research Funding: Transition NIH-funded research toward projects leveraging the dFDA system (NIH Budget).
  3. Leverage Medicare and Medicaid for Trial Access: Utilize existing statutory provisions allowing beneficiaries to participate in qualifying clinical trials (CMS Medicare Policy, Medicaid Clinical Trial Coverage Act).
  4. Incentivize Innovation via FDA-X Prize: Launch a $500 million X Prize competition to develop and deploy the dFDA Infrastructure.
  5. Expand Adaptive and Pragmatic Trials: Use NIH funding and Medicare/Medicaid reimbursements to sponsor scalable adaptive trials, ensuring cost-effective and real-world data generation.
  6. Government Co-Funding and Outcome-Based Payment Models: Utilize milestone-based payments and alternative payment models through CMMI to incentivize private-sector participation.

HHS Budget Context and Reallocation Potential

Given the size of the Medicare and Medicaid budgets and existing statutory permissions, redirecting even a fraction of these funds to dFDA trials could enable participation for tens of millions of patients without legislative changes. Furthermore, NIH reimbursements to drug companies for cost-recovery-based per-participant pricing would align with FDA regulations, ensuring compliance and operational sustainability.

Potential Participant Capacity with Proposed Funding

Given the $30.6 billion annual allocation for perpetual and adaptive trial execution and referencing the Oxford RECOVERY Trialโ€™s per-patient cost of ~$500 (RECOVERY Trial Cost), the proposed funding could support:

  • Over 61 million participants annually ($30.6B รท $500 per participant).

Medicare/Medicaid Integration Potential:

  • Existing policies allow for Medicare and Medicaid funds to cover routine patient costs in clinical trials. Expanding this coverage to dFDA trials could support an additional 100+ million participants annually, given the combined scale of these programs.
  • Per-participant pricing by trial sponsors, structured for cost recovery and compliant with 21 CFR 312.8, could further enhance trial scalability without the need for pre-approval.

FDA-X Prize Design

  • Total Prize Pool: $500 million.
  • Prize Structure:
    • $250M for the first team to build a fully functional, open-source dFDA Infrastructure.
    • $150M distributed among teams demonstrating scalable perpetual trials.
    • $100M in milestone prizes for critical technological breakthroughs.
  • Key Requirements:
    • Open-source codebase.
    • Seamless patient onboarding and participation.
    • Integration with NIH-funded adaptive trials and Medicare/Medicaid funding mechanisms.
    • Inclusion of per-participant pricing models for trial sponsors that comply with FDA cost-recovery regulations.
    • Automated insurance integration and risk-sharing models.
    • Real-time safety and efficacy monitoring using AI.
    • Compatibility with global regulatory standards.

Projected Impact

  • Cost Savings: Trillions in global healthcare savings.
  • Patient Empowerment: Universal access to experimental treatments, including through Medicare/Medicaid channels.
  • Faster Treatment Development: Reduced time from discovery to deployment from years to months.
  • Trial Participation at Scale: Potential to support over 160 million participants annually when combining NIH funding with Medicare and Medicaid support.
  • Operational Sustainability: Enabling drug companies to recover direct costs per participant while maintaining compliance with FDA regulations (21 CFR 312.8).
  • Scalable, Sustainable Ecosystem: Alignment of government and private-sector incentives ensures long-term sustainability.

Evidence of Congressional and Executive Branch Support

Below is a comprehensive list of statutes, executive actions, and related precedents that โ€“ taken together โ€“ reflect longstanding congressional, executive, and regulatory support for modernizing the FDAโ€™s operations and clinical trial infrastructure without the need for new legislation:

  1. FDA Modernization Act of 1997 (FDAMA)

    • Precedent: Laid the groundwork for streamlining drug development and approval processes by reducing bureaucratic barriers.

  2. FDA Amendments Act (FDAAA) of 2007

    • Precedent: Authorized the FDAโ€™s Sentinel Initiative for active post-market safety surveillance, an early example of leveraging digital, real-time data systems to monitor drug safety.

  3. FDA Safety and Innovation Act (FDASIA) of 2012

    • Precedent: Expanded FDAโ€™s regulatory flexibility, including expedited review programs and incentives for innovative trial designs.

  4. 21st Century Cures Act (2016)

    • Statute: A landmark law that accelerates medical product development by modernizing clinical trial designs (including adaptive and decentralized trials), funding cutting-edge research, and encouraging the use of real-world evidence.

  5. Right to Try Act (2018)

    • Statute: Grants terminally ill patients access to investigational therapies that have completed Phase I testing, emphasizing patient autonomy and a more flexible regulatory framework.

  6. Medicare Clinical Trial Coverage Provisions (Social Security Act Amendments)

    • Statute: Allows Medicare to reimburse routine costs incurred in qualifying clinical trials, thereby expanding patient access to innovative treatments without additional legislative changes.

  7. NIH All of Us Research Program

    • Precedent: Launched under the Precision Medicine Initiative (and supported by 21st Century Cures Act funding), this program reflects a federal commitment to patient-driven research and data sharing on a massive scale.

  8. U.S. Digital Service (USDS) and 18F Initiatives

    • Precedent: Established to improve the digital infrastructure and IT systems of federal agencies, including the FDA, these initiatives signal government-wide prioritization of modern, data-driven operations.

  9. Executive Orders on Regulatory Reform

    • Precedent: For example, the 2017 Executive Order on โ€œReducing Regulation and Controlling Regulatory Costsโ€ emphasizes increased efficiency and modernization across federal agencies, implicitly supporting innovations like a decentralized FDA.

  10. Trump Administrationโ€™s Department of Government Efficiency

    • Precedent: the Department of Government Efficiency highlights an executive focus on streamlining operations, reducing waste, and embracing digital transformation in regulatory agencies such as the FDA.

1. Why Previous Initiatives Failed

a. Sentinel Initiative: Limited Transparency and Bureaucratic Constraints

  • Closed Data Silos: Although Sentinel enabled active surveillance for post-market drug safety, it remained closed-source, restricting broader stakeholder engagement, innovation, and iterative improvement. Researchers and developers outside the FDA could not access core tools or data pipelines to enhance or repurpose them for broader clinical trial applications.
  • Bureaucratic Oversight: The complexity of working within federal regulatory frameworks slowed integration with emerging technologies and adaptive trial methodologies. Regulatory inertia prevented agile experimentation with decentralized trial models.
  • Lack of Real-Time Adaptability: Sentinel was primarily designed for post-market surveillance, not real-time adaptive trials, thus failing to impact early-stage drug development timelines.

b. All of Us Program: Centralized Control, Fragmented Incentives

  • Slow Data Utilization: While ambitious in its goal to collect data from a million diverse participants, All of Us remained hindered by centralization, leading to slow data curation, analysis, and deployment in real-world research.
  • Limited Access for Decentralized Innovation: The closed infrastructure prevented decentralized teams from rapidly deploying new analysis tools or integrating with clinical trial ecosystems.
  • Overly Academic Focus: The program primarily served academic research agendas rather than creating direct pipelines for real-time patient participation in clinical trials, missing the opportunity for immediate translational research impact.

c. Cure-ID: Insufficient Incentives and Network Effects

  • Lack of Engagement: Cure-ID, designed for healthcare professionals to share treatment outcomes, struggled with user engagement due to a lack of financial and reputational incentives.
  • No Robust Reward Mechanisms: Without mechanisms like token-based rewards or direct research funding incentives, participation remained minimal.
  • Non-Scalable Architecture: Its limited interoperability with decentralized health data networks reduced its capacity to scale alongside personalized and precision medicine initiatives.

2. How an Open-Source, X Prize Model Can Succeed Where Others Failed

a. Open-Source Infrastructure: Transparency, Flexibility, and Global Collaboration

  • Unrestricted Access: Open-source architectures allow researchers, biotech startups, and patient communities worldwide to contribute to and improve core trial platforms.
  • Interoperability: Seamless integration with digital health records, wearables, and real-world data streams can drive perpetual, adaptive trials at a scale impossible under closed systems.
  • Reduced Duplication: Open codebases prevent redundant efforts, accelerating the iteration of improved trial designs and AI-driven analysis tools.

b. X Prize Model: Incentivizing Breakthrough Innovation

  • Outcome-Driven Rewards: Unlike bureaucratic grants that fund effort rather than results, X Prizes reward successful outcomes, spurring ambitious, results-oriented innovation.
  • Attracting Diverse Talent: A substantial prize pool attracts interdisciplinary teams, fostering cross-sector solutions involving AI, blockchain, genomics, and data science.
  • De-Risking Radical Ideas: The prize model encourages moonshot thinking that traditional funding mechanisms avoid, accelerating paradigm-shifting breakthroughs in clinical trial methodologies.

c. Technological Advancements: AI, Blockchain, and Edge Computing

  • AI for Adaptive Trials: Machine learning models can personalize patient pathways, optimize trial endpoints, and monitor safety in real-time, radically shortening timelines from discovery to deployment.
  • Blockchain for Trust and Transparency: Immutable records of trial data, drug provenance, and patient consent build trust and eliminate fraud risks, ensuring regulatory compliance without manual oversight.

Sources

  1. JAMA Internal Medicine: โ€œEstimated Costs of Clinical Trials Supporting FDA Approvalsโ€ โ€“ Median cost per patient in pivotal clinical trials is approximately $41,413. (Source)

  2. RECOVERY Trial Summary: University of Oxfordโ€™s trial achieved a per-patient cost of $500. (Source)

  3. NIH Budget Information: The National Institutes of Healthโ€™s annual budget is approximately $51 billion. (Source)

  4. HHS Budget Overview (FY 2025): The total HHS budget is $1.843 trillion. (Source)

  5. Medicare Clinical Trial Coverage: Details on Medicare coverage of clinical trial costs. (Source)

  6. Medicaid Clinical Trial Coverage Act: State Medicaid programs must cover routine patient costs for beneficiaries in qualifying clinical trials. (Source)

  7. HRSA Budget Justification: Overview of HRSA budget allocations. (Source)

  8. FDA Regulation (21 CFR 312.8): Guidelines on charging for investigational drugs under cost-recovery provisions. (Source)

Implementation Timeline

Phase 1 (Months 0-6)

  • Launch FDA-X Prize competition
  • Establish technical requirements and evaluation criteria
  • Form advisory board of regulators, clinicians, and technologists

Phase 2 (Months 6-18)

  • First working prototypes of dFDA Infrastructure
  • Pilot trials with 3-5 drug candidates
  • Integration with existing EHR systems
  • Security and compliance audits

Phase 3 (Months 18-36)

  • Full platform launch
  • Onboarding of 50+ trial sponsors
  • Integration with Medicare/Medicaid systems
  • International regulatory alignment

Risk Mitigation

  1. Data Privacy & Security
  1. Clinical Safety
  • AI-powered adverse event detection
  • Real-time safety monitoring
  • Automated trial pausing mechanisms
  • Independent safety review board
  1. Regulatory Compliance
  • Built-in regulatory checkpoints
  • Automated compliance verification
  • Clear audit trails
  • Regular FDA consultation

Success Metrics

  1. Trial Efficiency
  • 80% reduction in trial setup time
  • 50% reduction in per-patient costs
  • 90% reduction in administrative overhead
  1. Patient Impact
  • 100x increase in trial participation
  • 70% reduction in time-to-treatment
  • Geographic access expanded to 95% of population
  1. Innovation Metrics
  • 5x increase in novel drug candidates
  • 3x increase in rare disease trials
  • 10x increase in adaptive trial designs