💊The Decentralized FDA
The mandate of the dFDA is to promote human health and safety by determining the comprehensive positive and negative effects of all foods and drugs.
🧞Be Careful What You Wish For
Imagine you met a magical genie. Imagine you wished for it to fulfill the FDA Congressional Mandate to:
Ensure the safety and efficacy of all drugs and medical devices
Q: How could the genie PERFECTLY achieve this? 🤔
A: Ensure that no one ever takes a new drug again.
That would 100% guarantee that no one ever takes a medication that may or may not be effective.
In practice, we've seen a less absolutist interpretation of the mandate. So instead of rejecting all new treatments, we have simply exponentially increased the regulatory barrier. Since 1962, when Congress imposed the current efficacy requirement, the cost of bringing a new therapy to market has increased 15X (1521%).
The Real Goal Is Human Health and Safety
☠️ 60 million people die every year because we don't have adequate treatments for them.
🤒 2.5 billion people suffer from chronic diseases for which we have no cures.
Congress created the FDA to protect and promote human health and safety. Unfortunately, the 1962 efficacy amendment has become a significant obstacle to the work of scientists who are trying to discover new cures.
Problems that Could be Solved with a Decentralized FDA
It takes over 10 years and $2.6 billion to bring a drug to market (including failed attempts). It costs $41k per subject in Phase III clinical trials.
The high costs lead to:
1. No Data on Unpatentable Molecules
🥫No Data on Unpatentable MoleculesWe still know next to nothing about the long-term effects of 99.9% of the 4 pounds of over 7,000 different synthetic or natural compounds. This is because there's only sufficient incentive to research patentable molecules.
2. Lack of Incentive to Discover Every Application of Off-Patent Treatments
Most of the known diseases (approximately 95%) are classified as rare diseases. Currently, a pharmaceutical company must predict particular conditions to treat before running a clinical trial. Suppose a drug is effective for other diseases after the patent expires. In that case, there isn't a financial incentive to get it approved for the different conditions.
3. No Long-Term Outcome Data
It's not financially feasible to collect a participant's data for years or decades. Thus, we don't know if the long-term effects of a drug are worse than the initial benefits.
4. Negative Results Aren't Published
Pharmaceutical companies tend to only report "positive" results. That leads to other companies wasting money repeating research on the same dead ends.
5. Trials Exclude a Vast Majority of The Population
One investigation found that only 14.5% of patients with major depressive disorder fulfilled the eligibility requirements for enrollment in an antidepressant trial. Furthermore, most patient sample sizes are very small and sometimes include only 20 people.
6. We Only Know 0.000000002% of What is Left to be Researched
The more research studies we read, the more we realize we don't know. Nearly every study ends with the phrase "more research is needed".
If you multiply the 166 billion molecules with drug-like properties by the 10,000 known diseases, that's 1,162,000,000,000,000 combinations. So far, we've studied 21,000 compounds. That means we only know 0.000000002% of the effects left to be discovered.
How a Decentralized FDA Could Overcome Perverse Incentives
Overcoming Cognitive Bias Against Acts of Commission
Humans have a cognitive bias towards weighting harmful acts of commission to be worse than acts of omission even if the act of omission causes greater harm. It's seen in the trolley problem where people generally aren't willing to push a fat man in front of a train to save a family even though more lives would be saved.
Medical researcher Dr. Henry I. Miller, MS, MD described his experience working at the FDA, “In the early 1980s,” Miller wrote, “when I headed the team at the FDA that was reviewing the NDA [application] for recombinant human insulin…my supervisor refused to sign off on the approval,” despite ample evidence of the drug’s ability to safely and effectively treat patients. His supervisor rationally concluded that, if there was a death or complication due to the medication, heads would roll at the FDA—including his own. So the personal risk of approving a drug is magnitudes larger than the risk of rejecting it.
In a DAO comprised of a large number of prominent experts, no individual could be blamed or have their career destroyed for making a correct decision to save the invisible lives of the many at the risk of the lives of the few.
It's Impossible to Report on Deaths That Occurred Due to Unavailable Treatments
Here's a news story from the Non-Existent Times by No One Ever without a picture of all the people that die from lack of access to life-saving treatments that might have been.
This means that it's only logical for regulators to reject drug applications by default. The personal risks of approving a drug with any newsworthy side effect far outweigh the personal risk of preventing access to life-saving treatment.
Types of Error in FDA Approval Decision
| Drug Is Beneficial | Drug Is Harmful | |
|---|---|---|
FDA Allows the Drug | Correct Decision | Victims are identifiable and might appear on Oprah. |
FDA Does Not Allow the Drug | Victims are not identifiable or acknowledged. | Correct Decision |
🔮Pre-Determining Clinical Endpoints Requires Psychic Powers❓We Know Next to Nothing
🌎Cost Savings from Decentralized Clinical Trials
Historical Evidence Suggesting That Crowdsourcing Clinical Research Works
There is compelling historical evidence suggesting that large scale efficacy-trials based on real-world evidence have ultimately led to better health outcomes than current pharmaceutical industry-driven randomized controlled trials.
For over 99% of recorded human history, the average human life expectancy has been around 30 years.
1893 - The Advent of Safety and Efficacy Trials
In the late nineteenth and early twentieth century, clinical objectivity grew. The independent peer-reviewed Journal of the American Medical Association (JAMA) was founded in 1893. It would gather case reports from the 144,000 physicians members of the AMA on the safety and effectiveness of drugs. The leading experts in the area of a specific medicine would review all of the data and compile them into a study listing side effects and the conditions for which a drug was or was not effective. If a medicine were found to be safe, JAMA would give its seal of approval for the conditions where it was found to be effective.
The adoption of this system of crowd-sourced, observational, objective, and peer-reviewed clinical research was followed by a sudden shift in the growth of human life expectancy. After over 10,000 years of almost no improvement, we suddenly saw a strangely linear 4-year increase in life expectancy every single year.
1938 - The FDA Requires Phase 1 Safety Trials
A drug called Elixir sulfanilamide caused over 100 deaths in the United States in 1937.
Congress reacted to the tragedy by requiring all new drugs to include:
"adequate tests by all methods reasonably applicable to show whether or not such drug is safe for use under the conditions prescribed, recommended, or suggested in the proposed labeling thereof."
These requirements evolved to what is now called the Phase 1 Safety Trial.
This consistent four-year/year increase in life expectancy remained unchanged before and after the new safety regulations.
This suggests that the regulations did not have a large-scale positive or negative impact on the development of life-saving interventions.
1950's - Thalidomide Causes Thousands of Birth Defects Outside US
Thalidomide was first marketed in Europe in 1957 for morning sickness. While it was initially thought to be safe in pregnancy, it resulted in thousands of horrific congenital disabilities.
Fortunately, the existing FDA safety regulations prevented any birth defects in the US. Despite the effectiveness of the existing US regulatory framework in protecting Americans, newspaper stories such as the one below created a strong public outcry for increased regulation.
1962 - New Efficacy Regulations Reduce the Amount and Quality of Efficacy Data Collected
As effective safety regulations were already in place, the government instead responded to the Thalidomide disaster by regulating efficacy testing via the 1962 Kefauver Harris Amendment. Before the 1962 regulations, it cost a drug manufacturer an average of $74 million (2020 inflation-adjusted) to develop and test a new drug for safety before bringing it to market. Once the FDA had approved it as safe, efficacy testing was performed by the third-party American Medical Association. Following the regulation, trials were instead to be conducted in small, highly-controlled trials by the pharmaceutical industry.
Reduction in Efficacy Data
The 1962 regulations made these large real-world efficacy trials illegal. Ironically, even though the new regulations were primarily focused on ensuring that drugs were effective through controlled FDA efficacy trials, they massively reduced the quantity and quality of the efficacy data that was collected for several reasons:
New Trials Were Much Smaller
Participants Were Less Representative of Actual Patients
They Were Run by Drug Companies with Conflicts of Interest Instead of the 3rd Party AMA
Reduction in New Treatments
The new regulatory clampdown on approvals immediately reduced the production of new treatments by 70%.
Explosion in Costs
Since the abandonment of the former efficacy trial model, costs have exploded. Since 1962, the cost of bringing a new treatment to market has gone from $74 million to over $1 billion US dollars (2020 inflation-adjusted).
Increase in Patent Monopoly
Industry agitation surrounding the “drug lag” finally led to the modification of the drug patenting system in the Drug Price Competition and Patent Term Restoration Act of 1984. This further extended the life of drug patents. Thus Kefauver's amendments ultimately made drugs more expensive by granting longer monopolies.
Decreased Ability to Determine Comparative Efficacy
The placebo-controlled, randomized controlled trial helped researchers gauge the efficacy of an individual drug. However, it makes the determination of comparative effectiveness much more difficult.
Slowed Growth in Life Expectancy
From 1890 to 1960, there was a linear 4-year increase in human lifespan every year. This amazingly linear growth rate had followed millennia with a flat human lifespan of around 28 years. Following this new 70% reduction in the pace of medical progress, the growth in human lifespan was immediately cut in half to an increase of 2 years per year.
Diminishing Returns?
One might say “It seems more likely — or as likely — to me that drug development provides diminishing returns to life expectancy.” However, diminishing returns produce a slope of exponential decay. It may be partially responsible, but it’s not going to produce a sudden change in the linear slope of a curve a linear as life expectancy was before and after the 1962 regulations.
Correlation is Not Causation
You might say "I don't know how much the efficacy regulations contribute to or hampers public health. I do know that correlation does not necessarily imply causation." However, a correlation plus a logical mechanism of action is the least bad method we have for inferring the most likely significant causal factor for an outcome (i.e. life expectancy). Assuming most likely causality based on temporal correlation is the entire basis of a clinical research study and the scientific method generally.
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