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NIH Fails to Institute Health

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war-on-disease, 1-percent-treaty, medical-research, public-health, peace-dividend, decentralized-trials, dfda, dih, victory-bonds, health-economics, cost-benefit-analysis, clinical-trials, drug-development, regulatory-reform, military-spending, peace-economics, decentralized-governance, wishocracy, blockchain-governance, impact-investing

NIH Inefficiency

NIH Inefficiency

The Allocation Scandal

The National Institutes of Health has an annual budget of approximately $51 billion. 55 million people die annually138 while this money gets allocated as follows:

A 2023 JAMA study analyzed $247 billion in NIH spending (2010-2019) and found:

  • 84.9% - Basic research ($209.9B): Mice, molecules, mechanisms - “experimental work…without any particular application in view”
  • 11.8% - Applied research (non-trial) ($29.3B): Research with practical aims, but not actually testing treatments in humans
    • CTSA infrastructure program: ~$1B/year in buildings, overhead, salaries (~1.5% of total budget)
    • Observational studies: Watching patients get sicker without testing treatments (All of Us139: $2.16B, zero treatments tested)
    • Other applied research: Drug characterization, health services research, epidemiology
  • 3.3% - Phased clinical trials ($8.1B): Actually testing if drugs work in humans (Phases 1-3)
    • Phase 1: $1.5B (18.5% of clinical trial budget)
    • Phase 2: $3.5B (43.2%)
    • Phase 3: $2.6B (32.1%) - NIH covers only 3.7-4.3% of Phase 3 costs, then abandons funding
    • Pragmatic trials1 (30x cheaper): Severely underfunded despite proven efficiency

The NIH spends 96.7% of its budget on everything except the highest-value activity: running efficient clinical trials in humans.

This isn’t just inefficiency. It’s a body count.

Breakdown of NIH spending showing the massive disparity between basic research (84.9 percent) and actual human clinical trials (3.3 percent).

Breakdown of NIH spending showing the massive disparity between basic research (84.9 percent) and actual human clinical trials (3.3 percent).

Why This Allocation Exists

This isn’t bureaucratic accident. It’s lobbied outcome.

A conceptual map of the systemic incentives and ‘revolving door’ relationships between the pharmaceutical industry, government funding agencies, and academia that prioritize basic research over cost-effectiveness trials.

A conceptual map of the systemic incentives and ‘revolving door’ relationships between the pharmaceutical industry, government funding agencies, and academia that prioritize basic research over cost-effectiveness trials.

Drug companies benefit enormously from NIH funding basic research. Taxpayers absorb the risk; industry patents the successes. But independent pragmatic trials comparing drugs head-to-head? Those threaten blockbuster profits by revealing which treatments actually work best.

PhRMA, the pharmaceutical lobby, has consistently opposed comparative effectiveness research. When Congress created PCORI in 2010 to fund such research, industry successfully lobbied to prohibit PCORI from making coverage recommendations based on cost-effectiveness140. The message was clear: don’t fund research that might lower drug prices.

The revolving door reinforces this. NIH advisory committees include industry representatives. Former NIH officials join pharmaceutical boards. Academic researchers depend on industry grants and consulting fees. Everyone’s incentives align against the one thing that would actually help patients: cheap, fast trials testing whether expensive drugs outperform generics.

Basic research produces publications. Publications produce tenure. Tenure produces more grants. This self-perpetuating cycle rewards knowledge production over health production.

The 3.3% allocation isn’t a mystery. It’s a business model.

The Efficiency Gap: A Tale of Two Trials

The difference between efficient and inefficient trial design isn’t theoretical. We have a controlled experiment.

RECOVER Initiative (NIH Approach)

A summary of the RECOVER Initiative’s metrics, contrasting its 1.665 billion budget and 4-year timeline against the 30,000 patients enrolled and zero completed trials.

A summary of the RECOVER Initiative’s metrics, contrasting its 1.665 billion budget and 4-year timeline against the 30,000 patients enrolled and zero completed trials.

Budget: $1.665 billion ($1.15B + $515M in 2024) (source141) Timeline: 4 years and counting142 Patients enrolled: ~30,000143 Trials completed: Zero142 Cost per patient: $55,500

RECOVERY Trial (UK Approach)

Budget: $20M (95% CI: $15M-$25M) Timeline: 6 months144 Patients enrolled: 48,00077 Treatments found: Multiple, including dexamethasone145 (saved over 1 million lives) Cost per patient: $500 (95% CI: $400-$2.50K)

The NIH RECOVER Initiative spent 133X more per patient to achieve infinitely less (dividing by zero trials completed). This massive efficiency gap is not unique to RECOVERY; a systematic review of 64 pragmatic trials found a median cost of $97 (95% CI: $19-$478)/patient85.

A comparison between the UK RECOVERY Trial and the NIH RECOVER Initiative, highlighting the 133x difference in cost per patient and the disparity in clinical outcomes.

A comparison between the UK RECOVERY Trial and the NIH RECOVER Initiative, highlighting the 133x difference in cost per patient and the disparity in clinical outcomes.

This proves the problem isn’t that curing disease is hard. The problem is that the NIH funds the wrong things.

The Death Toll: Opportunity Cost of Misallocation

When you misallocate $40 billion a year into low-efficiency research instead of high-efficiency clinical trials, you aren’t just wasting money. You are burning lives.

A conceptual infographic contrasting the outcomes of allocating 40 billion to low-efficiency research versus high-efficiency clinical trials, highlighting the human lives lost as an opportunity cost.

A conceptual infographic contrasting the outcomes of allocating 40 billion to low-efficiency research versus high-efficiency clinical trials, highlighting the human lives lost as an opportunity cost.

Cost Per QALY (Quality-Adjusted Life Year)

  • Standard NIH Portfolio: $50K (95% CI: $20K-$100K) per QALY76 (generous estimate)
  • Pragmatic Platform Trials: $4.00 (95% CI: $1.71-$10) per QALY
  • NIH pragmatic trials funding: Capped at $500K planning + $1M/year implementation1. This is a tiny fraction of the $47B budget

The Multiplier:

Every $1 spent on efficient pragmatic trials buys 12.5kx (95% CI: 2.3kx-51.5kx) more health than a dollar spent on the current NIH mix.

Yet pragmatic trials remain severely underfunded1 despite the ADAPTABLE trial proving they cost 30x less than traditional RCTs1 ($14M (95% CI: $14M-$20M) vs $420M).

Bar chart comparing the cost efficiency of the Standard NIH Portfolio vs. Pragmatic Platform Trials, demonstrating the massive return on investment difference.

Bar chart comparing the cost efficiency of the Standard NIH Portfolio vs. Pragmatic Platform Trials, demonstrating the massive return on investment difference.

The “Death Equivalent” of Budget Misallocation

Annual Opportunity Cost (Central Estimates):

  • QALYs Lost: ~100 million life-years per year
  • Deaths NOT Prevented: ~7 million death-equivalents per year

Conservative 90% Confidence Interval:

  • QALYs Lost: 10 million to 820 million per year
  • Deaths NOT Prevented: 0.7 million to 64 million per year

Even in the most conservative 5th-percentile scenario, NIH misallocation costs ~10 million QALYs and prevents ~700,000 deaths’ worth of health gains annually.

In the 95th-percentile scenario, it’s burning health equivalent to most of the global death toll (60M deaths/year).

The NIH isn’t just inefficient. By blocking the shift to high-efficiency trial platforms, the current budget allocation is actively destroying the equivalent of millions of lives annually compared to the optimal allocation.

Mathematical Conclusion:

\[ \text{Efficiency Loss} = 1 - \frac{\text{Current QALYs gained}}{\text{Potential QALYs gained}} \approx 98\% \]

We are operating at ~2% of our potential theoretical capacity to save lives.

The Translation Crisis: Concept Rich, Trial Poor

Here is the “Stock vs Flow” problem in one sentence: We are not short of hypotheses; we are short of trial slots.

  • FDA-approved drugs: >20,000 known safe in humans
  • Repurposable compounds: ~4,700-6,800 clinically-tested candidates146 (including 3,422 marketed drugs) sitting on shelves
  • Plausible dementia interventions: Hundreds
  • Clinical trials available for your grandma in St. Louis: Zero

We have a massive stock of safe molecules that have never been systematically evaluated for new uses. But the flow of trials is a trickle.

A visualization of the ‘Stock vs. Flow’ crisis illustrating the massive reservoir of potential drug candidates compared to the narrow bottleneck of clinical trial availability and final approvals.

A visualization of the ‘Stock vs. Flow’ crisis illustrating the massive reservoir of potential drug candidates compared to the narrow bottleneck of clinical trial availability and final approvals.

The result is a system that produces papers, not cures:

  • Papers published: 2.5 million annually147
  • New treatments approved: ~50 annually27
  • Conversion rate from paper to patient: 0.002%

Knowledge Production: Saturated. Translation Capacity: Starved.

The bottleneck isn’t ideas. It’s execution:

  • Biomedical papers produced: 2.5 million per year147
  • Adults who’ve participated in trials: ~5%25
  • Adults willing to participate if invited: ~50-75%78
  • Adults actually invited: ~9-11%78

We’re drowning in hypotheses while patients are starving for trial slots.

The system produces millions of papers testing ideas in mice, but offers trial participation to only 5% of humans. Even though half would say yes if asked.

That’s not an information failure. That’s a capacity failure.

We know everything about how cancer works in mice. We’ve mapped every pathway, gene, and protein. We have Nobel Prizes for understanding mechanisms.

The ‘Funnel of Failure’ illustrating the bottleneck between the massive stock of published research and safe molecules versus the trickle of approved treatments.

The ‘Funnel of Failure’ illustrating the bottleneck between the massive stock of published research and safe molecules versus the trickle of approved treatments.

What we don’t have: Cures.

Because understanding disease and curing disease are completely different things. The NIH chose understanding. Patients needed cures.

The Public Goods vs. Club Goods Scam

The NIH defends its existence by claiming to produce “Public Goods” (open science, data, training). In reality, it spends taxpayers’ money to produce “Club Goods” for private industry.

A flow diagram of the drug development pipeline showing how taxpayer funding covers high-risk basic research and training, while private industry privatizes the successful outputs through patents, creating a cycle of socialized risk and privatized profit.

A flow diagram of the drug development pipeline showing how taxpayer funding covers high-risk basic research and training, while private industry privatizes the successful outputs through patents, creating a cycle of socialized risk and privatized profit.

The Scam in Numbers:

  • Direct commercialization support: ~3-5% of budget
  • Indirect subsidy to profitable firms: ~40-60% of NIH spending148 functions as a de facto subsidy to industry. This includes funding basic research, training scientists, and generating patents that private companies exploit
  • NIH contribution to approved drugs: Funded research for 99% of new drugs149 (356 drugs, 2010-2019), but covers only ~10% of clinical trial costs
  • Who pays for translation: NIH covers only ~10% of what industry spends148 on clinical trials for approved drugs

The pattern is clear: taxpayers fund 40-60% of the knowledge pipeline (~$20-30B/year), industry patents the winners, and the public pays again through high drug prices.

When a discovery leads to a blockbuster drug, the IP is privatized. When the research leads to a dead end, the public eats the loss.

Socialized Risk, Privatized Profit.

True public goods would be unpatentable but high-value assets like:

  • Open pragmatic trial platforms: 30x cheaper than traditional trials1, yet receive minimal NIH funding
  • Re-purposing generic drugs: 4,700+ clinically-tested compounds146 where no patent exists
  • Comparative effectiveness data: Head-to-Head trials that would reveal which drugs actually work best

Private companies cannot profitably fund these, so they are the only thing the NIH should be funding. Instead, the NIH explicitly avoids them to “not crowd out industry.” Translation: We won’t run the trials that would lower drug prices or fix problems without a patent attached.

The Patient Disconnect: Zero Correlation with Health Outcomes

Here’s the most damning statistic of all:

Correlation between NIH funding priorities and actual disease burden: 0.07150

That’s essentially random. You’d get better allocation by throwing darts at a list of diseases.

A comparison chart illustrating the disconnect between NIH funding levels and actual disease burden, highlighting the negligible 0.07 correlation.

A comparison chart illustrating the disconnect between NIH funding levels and actual disease burden, highlighting the negligible 0.07 correlation.

What patients want

  • Treatments that work
  • Access to experimental therapies
  • Trials they can actually join
  • Cures for their specific disease

What NIH funds

  • Understanding molecular mechanisms
  • Publishing papers in prestigious journals
  • Building research empires
  • Protecting institutional overhead

The system optimizes for everything except patient outcomes. Because patients don’t control the money. Committees do.

A conceptual diagram showing the flow of NIH funding controlled by committees toward institutional goals like papers and overhead, while patient outcomes remain disconnected from the primary incentive loop.

A conceptual diagram showing the flow of NIH funding controlled by committees toward institutional goals like papers and overhead, while patient outcomes remain disconnected from the primary incentive loop.

The Track Record

Since 1970, the NIH has spent over $1.1 trillion (inflation-adjusted).

Number of diseases eradicated: Zero151.

This isn’t because eradicating disease is impossible:

  • The WHO eradicated smallpox for $300 million103
  • Jonas Salk developed the polio vaccine in a university lab
  • Veterinarians have eradicated multiple animal diseases152 while the NIH was forming subcommittees

The problem isn’t capability. It’s allocation.

What Would Actually Work

The UK RECOVERY trial proved the alternative: $500 (95% CI: $400-$2.50K) per patient instead of $41K (95% CI: $20K-$120K), 100 days instead of years, and over 1 million lives saved.

A comparison between the traditional clinical trial model and the streamlined RECOVERY trial approach, illustrating the dramatic differences in cost, speed, and methodology.

A comparison between the traditional clinical trial model and the streamlined RECOVERY trial approach, illustrating the dramatic differences in cost, speed, and methodology.

What it requires:

  1. Pay for results: Cure = payment, no cure = no payment
  2. Published everything: Including failures (especially failures)
  3. Eliminated gatekeepers: Let patients vote with participation
  4. Automated administration: Smart contracts > committees

For how to scale this globally and make it permanent, see A Decentralized Framework for Drug Assessment.

The legal framework already exists for cost recovery in trials (21 CFR 312.8153).

You could implement efficient trials tomorrow. But that would upset the grant-writing industrial complex.

The Bottom Line

For $1.1 trillion since 1970, the NIH built the world’s most expensive grant-writing academy. Zero diseases eradicated. Millions of papers nobody reads. Thousands of administrators. Hundreds of committees.

A comparative visualization of the NIH’s massive resource inputs and bureaucratic outputs against the lack of eradicated diseases, contrasted with a streamlined alternative model.

A comparative visualization of the NIH’s massive resource inputs and bureaucratic outputs against the lack of eradicated diseases, contrasted with a streamlined alternative model.

The alternative exists and has been proven to work.