First Principles Framework

What Is Healing?

Applying the "What is money?" framework to medicine—three evolutionary replays that predict healthcare's transformation

M31 Capital Research February 2026 Working Paper
The Pattern
"We're using the same thing with medicine. That's how medicine goes. How do new treatments get into the mainstream? We've seen it with cannabis. We've seen it with a bunch of other things that were a no and now are not a no."
I
"What is healing?"
Body as software → programmable medicine
II
"How do treatments enter the mainstream?"
Cannabis path → psilocybin replay
III
"What is health?"
Sick care → continuous optimization
Contents

I. The Method: Three Questions

In DeFi, the question "What is money?" predicted the entire ecosystem's development. The same method works for medicine—but the domain requires not one question, but three, each generating its own evolutionary replay.

The "What is money?" framework works because it starts with a fundamental question about what something is, studies how it evolved historically, identifies a binary moment that determines which future unfolds, and then uses the historical sequence as a predictive model.

Medicine is more complex than finance because it involves three overlapping paradigm shifts happening simultaneously. Each requires its own fundamental question:

Each question generates a different evolutionary replay. Together, they create a comprehensive investment map for healthcare's transformation.

Evolutionary Replay I
"What Is Healing?"

II. What Is Healing?

For 5,000 years, medicine treated the body as a machine—broken parts to be fixed, invading pathogens to be killed. A new answer is emerging: the body is programmable, and healing means rewriting the instructions.

The traditional answer to "What is healing?" has been: eliminate the thing causing harm. Cut out the tumor. Kill the bacteria. Block the receptor. Suppress the symptom. This is "body as hardware"—if a part breaks, you fix or replace it.

But starting with the discovery of DNA's structure in 1953 and accelerating through the Human Genome Project (2003), CRISPR (2012), and mRNA platforms (2020), a fundamentally different answer emerged: the body is a set of instructions that can be read, edited, and reprogrammed.

Healing is not eliminating disease. Healing is restoring correct biological programming.

III. The Binary: Hardware or Software?

Like "one currency or many?" for DeFi, the binary question for medicine is: "Is the body hardware or software?" The answer determines which future unfolds.

If Hardware If Software
Surgery, prosthetics, organ transplants Gene therapy, mRNA, cell reprogramming
One-size-fits-all drugs Personalized, genotype-specific treatments
Treat after breakdown Predict and prevent from the code
Blockbuster pharma model persists Entire pharma infrastructure rebuilt
Incremental improvement Paradigm shift—new ecosystem required

CRISPR and mRNA Answered the Question

CRISPR-Cas9 (2012) proved you can edit the body's code. mRNA vaccines (2020) proved you can program the body to produce its own medicine. Just as Ethereum proved currencies are programmable (triggering the entire DeFi ecosystem), CRISPR and mRNA proved the body is programmable—triggering the need for an entirely new medical infrastructure.

The Pivotal Moment
The Body Is Programmable

Once the body is proven programmable, every downstream need becomes inevitable: better code readers (sequencing), better code editors (gene editing), delivery mechanisms (LNPs, viral vectors), personalized diagnostics, AI interpretation, manufacturing at scale.

This is DeFi's logic applied to biology: one foundational capability creates the conditions for an entire ecosystem.

IV. 5,000 Years of Medicine → 20 Years of Biotech

Traditional medicine evolved through a deterministic sequence. Programmable biology is replaying that sequence—compressed.

Primitive Traditional Medicine Programmable Biology
Observation Hippocratic method (~400 BCE) Genomic sequencing (2003)
Anatomy / Structure Vesalius, dissection (~1543) Proteomics, structural biology
Causal Theory Germ theory (1860s) Genetic basis of disease (2000s)
Targeted Treatment Antibiotics (1928) Gene therapy / CRISPR (2012)
Programmable Platform — mRNA platform (2020)
Precision Tools Microsurgery, imaging Base editing, prime editing (2020s)
Delivery Systems Pills, IV, injection LNPs, AAVs, exosomes (emerging)
Manufacturing Pharma factories Cell manufacturing at scale (emerging)
Diagnostics Blood tests, imaging Liquid biopsy, multi-omics (emerging)
AI Interpretation Doctor's judgment AI-powered diagnosis (emerging)
Continuous Monitoring Annual checkups Wearables, biosensors (early)
Regulatory Adaptation FDA drug approval (1938+) New frameworks needed (missing)
Payment Models Fee-for-service insurance Outcomes-based payment (missing)
Investment Implication
The same logic that drove DeFi infrastructure investments applies here: invest in the infrastructure that enables programmable medicine—delivery platforms, manufacturing, AI diagnostics, regulatory technology—not individual therapies that may be displaced.
Evolutionary Replay II
"How Do Treatments Enter the Mainstream?"

V. How Do Treatments Enter the Mainstream?

This is the most directly actionable question. New treatments follow a deterministic adoption sequence. Study the precedent, map where the new treatment is in the sequence, and predict what comes next.

Cannabis mapped this path completely—from indigenous use through criminalization, through state-level legalization, through banking exclusion, through infrastructure buildout, toward federal acceptance. Psilocybin is replaying the identical sequence, compressed.

The key insight: the adoption sequence isn't random. Each step creates the conditions for the next, just as DEXs created the conditions for lending in DeFi. And critically, you can identify the infrastructure needs at each stage before they're built.

VI. The Cannabis Template

Cannabis provides the complete adoption playbook—every stage from traditional use to mainstream acceptance, mapped over decades.

Millennia → 1930s
Traditional & Medical Use
Widely used medicinally. Cannabis in US Pharmacopeia until 1942. Common in patent medicines.
1937 / 1970
Criminalization
Marihuana Tax Act (1937), then Schedule I under Controlled Substances Act (1970). Federal prohibition complete.
1970s → 1990s
Underground Continuation
Use continues despite prohibition. Counter-culture adoption. Research suppressed but not eliminated.
1996
First State Medical Legalization
California Prop 215—first state to legalize medical cannabis. Federal government threatened to prosecute doctors.
1998 → 2010s
State-by-State Medical Expansion
Oregon, Alaska, Washington (1998), then steady expansion. 39 states eventually legalize medical use.
2000s → present
Banking Exclusion / "Unbanked"
Federal prohibition means traditional banking unavailable. Cash-only businesses. SAFE Banking Act debated for years.
2012
First Recreational Legalization
Colorado and Washington legalize recreational use. Massive shift in public acceptance.
2015 → present
Multi-State Operators & Scale
Professional operators emerge. Institutional investment flows. 24 states now have recreational legalization.
2017 → present
Dumbed-Down Version Goes Mainstream
CBD products everywhere—lotions, pet food, drinks. Low-THC Delta-8 products exploit regulatory gaps. Mass market normalization.
Current
Federal Rescheduling Debates
DEA proposed rescheduling to Schedule III (2024). Federal legalization bills introduced. Still not resolved.
Future
Full Federal Legalization
No state has reversed legalization since 1996. Federal alignment is a matter of when, not if.
The Cannabis Pattern
The Tipping Point Formula

Cannabis didn't legalize because attitudes magically changed. It legalized when there was more money to be made selling it legally than opposing it. Once governments could tax it, once corporations could profit from it, the incentive structure flipped.

Same pattern as Bitcoin and banks: "No, no, no" → ETF launches → "Now we get product around this." Same pattern every time. Track when the money incentive flips.

VII. The Psilocybin Replay

Psilocybin is following the cannabis path step by step—but compressed. Each stage from the cannabis template is playing out in the identical sequence.

✓ Complete
Traditional / Indigenous Use
Millennia of ceremonial and medicinal use. Well-documented indigenous practices across cultures.
✓ Complete — 1950s-60s
Western Discovery & Initial Enthusiasm
Hofmann, Leary, Johns Hopkins research. Therapeutic use explored. Initial promise documented.
✓ Complete — 1970
Criminalization / Schedule I
Controlled Substances Act classifies psilocybin as Schedule I. Research effectively halted for decades.
✓ Complete — 1970s-2010s
Underground Continuation
Use continues despite prohibition. Microdosing culture emerges. Underground therapy networks develop.
✓ Complete — 2010s
Medical Champions Emerge
Johns Hopkins, NYU, Imperial College publish breakthrough clinical data. MAPS advances MDMA research. Scientific legitimacy established.
✓ Complete — 2018-2024
FDA Breakthrough Therapy Designations
MDMA for PTSD (2017). Psilocybin for depression by Compass Pathways (2018) and Usona Institute (2019). CYB003 for MDD (2024). LSD for anxiety (2024).
✓ Complete — 2020-2023
First State-Level Legalization
Oregon Measure 109 (2020): first state to legalize supervised psilocybin therapy. Colorado Proposition 122 (2022): decriminalization + regulated access.
✓ Complete — 2017+
"Dumbed-Down Version" Goes Mainstream
Microdosing normalized in Silicon Valley. Ketamine (legal) clinics proliferate. Functional mushroom products (non-psychoactive) in every grocery store. The "CBD equivalent" of psychedelics.
◐ Now — Psilocybin is HERE
Banking Exclusion & Funding Gaps
Psychedelic companies face same banking challenges as early cannabis. Traditional pharma/VC cautious. MDMA rejected by FDA (Aug 2024)—asking for additional Phase 3 trial. Psilocybin could gain approval within 2 years.
Predicted: 2025-2027
Clinical Infrastructure Buildout
Treatment centers, therapist training programs, dosing protocols, certification standards. The "dispensary infrastructure" equivalent.
Predicted: 2026-2028
More States Adopt Medical Frameworks
Following Oregon and Colorado's lead. State-by-state expansion like cannabis 1998-2012. No state reversal.
Predicted: 2027-2030
FDA Approval / Federal Rescheduling
Psilocybin likely approved before MDMA (based on current trials). Compass Pathways Phase 3 data expected. Federal rescheduling follows.
Predicted: 2028+
Insurance Coverage & Standard of Care
Payer adoption. Integration into mainstream psychiatry. Professional training at medical schools. Full normalization.
Where the Money Flips
Psilocybin will go mainstream when governments can tax it and pharma can profit from it. The tipping point: when the cost of treating mental health with psychedelics is demonstrably lower than the current cost of SSRIs + therapy + disability + lost productivity. That economic case is already being built. Same incentive flip as cannabis, same as Bitcoin + banks.

Cannabis → Psilocybin: The Predictive Map

Using cannabis as the template, specific infrastructure needs become predictable at each stage:

Infrastructure Gap
Alternative Funding
Psilocybin companies are "unbanked" like early cannabis. Create ways to fund them—same opportunity M31 seized in early crypto.
Cannabis parallel: Cash-only businesses → cannabis banking infrastructure
Infrastructure Gap
Treatment Center Networks
State-level legalization requires physical locations. Treatment centers, retreat facilities, clinical supervision infrastructure.
Cannabis parallel: Dispensary networks → multi-state operators
Infrastructure Gap
Therapist Training & Certification
Psychedelic-assisted therapy requires trained therapists. Training programs, certification bodies, supervision frameworks.
Cannabis parallel: Budtender training → medical marijuana doctor networks
Infrastructure Gap
Manufacturing & Supply Chain
GMP-grade psilocybin production, standardized dosing, quality control. State-by-state compliance systems.
Cannabis parallel: Cultivation → processing → distribution infrastructure
Infrastructure Gap
Regulatory Technology
Compliance tracking, patient registries, outcome measurement systems. Same need cannabis created for seed-to-sale tracking.
Cannabis parallel: Seed-to-sale tracking → Metrc, BioTrackTHC
Infrastructure Gap
Insurance & Reimbursement Platforms
Coverage models for psychedelic therapy. Outcome measurement proving cost-effectiveness vs. existing treatments.
Cannabis parallel: Still largely missing even for cannabis
Evolutionary Replay III
"What Is Health?"

VIII. What Is Health?

The healthcare system was assumed to be the better path. It is now becoming the more painful—too expensive, not holistic, siloed, and incentivized away from the patient. The assumption is ripe for change.

The current healthcare system answers "What is health?" with: the absence of disease. You're healthy until you're sick. Then you enter the system, get diagnosed, get treated, get billed. This is reactive, episodic, and standardized.

But a fundamentally different answer is emerging: health is the continuous optimization of biological systems. You're not "healthy" or "sick"—you're on a spectrum, and the goal is to maintain optimal function, not just avoid breakdown.

Sick Care (Current) Health Optimization (Emerging)
Wait until symptomatic Monitor continuously
Diagnose → treat → bill Predict → prevent → optimize
One-size-fits-all protocols Personalized to your biology
Doctor as gatekeeper Individual as owner
Pharma: chronic management Root cause resolution
Insurance: pays for intervention Pays for outcomes
Siloed specialists Integrated systems view

The Logical Chain

Once you accept health = continuous optimization (not absence of disease), each subsequent need becomes inevitable:

→ Continuous optimization requires continuous monitoring (wearables, biosensors)
→ Continuous data requires personalized baselines (genomics + phenomics)
→ Complex data requires AI interpretation (pattern recognition at scale)
→ Personalized insights require personalized interventions (precision nutrition, supplements, therapies)
→ Proactive care requires new payment models (outcomes-based, not visit-based)
→ Alternative treatments require new regulatory frameworks (beyond pharma-centric FDA)
→ New frameworks require new evidence standards (real-world evidence, n-of-1 trials)
→ All of the above requires new training models (doctors trained in systems biology, not just pathology)
"The healthcare system was assumed to be the better path. It is now becoming the more painful because it's too expensive, people don't trust it, it's not holistic, it's too siloed. The incentives around the insurance companies and the doctors is not towards the patient. The exact pressure is ripe for change." — M31 Investment Framework Discussion

The Technology Unlocks

Multiple technological breakthroughs are converging to make this shift inevitable—just as smartphones + broadband + GPS converged to enable ride-sharing and food delivery:

IX. The Suppression Signal

All three replays share a common feature: active suppression by established interests. In M31's framework, this is the most powerful contrarian indicator.

The healthcare paradigm shift exhibits exactly the suppression patterns that drove M31's early Bitcoin and Ethereum success:

Suppression Pattern Crypto (Validated) Healthcare (Current)
Regulatory attack SEC lawsuits, exchange shutdowns FDA rejection of MDMA, Schedule I classification
Banking exclusion Debanking of crypto companies Cannabis & psychedelic companies unbanked
Incumbent opposition "Bitcoin is a fraud" — Jamie Dimon Pharma lobbying against alternatives
Media dismissal "Bitcoin obituaries" (400+ times) "Alternative medicine is pseudoscience"
Incentive misalignment Banks had no revenue from crypto Pharma profit = chronic management, not cures
Then the flip ETFs approved → banks want in Govts realize tax revenue > pharma lobbying spend
Nathan's Tipping Point Formula
When Is More Money to Be Made Accepting Than Opposing?

"They didn't want to sell cannabis until all of a sudden there's some tipping point where once they've got enough skin in the game, they realize actually we can make a lot of money selling cannabis versus it's disruptive to our current [business]."

"Now shocker. Exact same thing with Bitcoin. Banks were like, no, no, no. No skin in the game. No incentive to support it. Now an ETF. And then it's like now we get product around this."

Track when the incentive flips. That's the tipping point. For psilocybin: quantify for government that tax revenue + reduced healthcare costs > pharma lobbying opposition.

X. Investment Map

Three evolutionary replays create a comprehensive investment landscape. Infrastructure over applications—the same principle that drove DeFi returns.

Replay I: Programmable Biology Infrastructure

Now — Building
Delivery Platforms
Lipid nanoparticles, viral vectors, exosomes. The "pipes" that get genetic instructions to the right cells. Infrastructure, not individual therapies.
Now — Building
Cell Manufacturing
Scalable production of cell therapies, gene-edited cells, mRNA. The bottleneck between lab success and patient access.
Now — Emerging
AI Drug Discovery
AI-powered target identification, molecule design, clinical trial optimization. Also natural compound discovery—AI finding things in nature we couldn't find before.
Future — Missing
Regulatory Technology
FDA frameworks not built for programmable medicine. Whoever builds regulatory infrastructure for personalized, gene-based therapies captures massive value.

Replay II: Psychedelic Therapy Infrastructure

Now — Opportunity
Alternative Funding Vehicles
"Are the psilocybin people going to be unbanked at the beginning? Yeah, so maybe we create ways to fund them." Same playbook as early crypto.
Now — Early
Ketamine Clinic Networks
Ketamine is already legal. 3,500+ certified clinics for Spravato. This infrastructure becomes the foundation for psilocybin when approved.
Next — Building
Treatment Center Roll-Ups
Oregon and Colorado creating first regulated treatment centers. Multi-state operator model follows—same as cannabis MSOs.
Next — Needed
Therapist Training Infrastructure
Psychedelic-assisted therapy requires specially trained therapists. Training programs, certification, supervision systems.

Replay III: Health Optimization Infrastructure

Now — Growing
Continuous Monitoring Platforms
Wearables + AI interpretation. Moving from fitness tracking to clinical-grade health monitoring. Data infrastructure is the play.
Now — Early
Preventive Medicine Clinics
"Do we need to invest in alternative, preventive medicine clinics? Because they are the ones that are going to be distributing and therefore accessing this market."
Now — Building
Personalized Nutrition & Supplements
Genomics-informed nutrition. Precision supplementation. The "dumbed-down version" already going mainstream—ashwagandha, adaptogens in everything.
Future — Missing
Outcomes-Based Payment Systems
Current insurance pays for sickness, not health. New payment models that reward prevention and optimization. Whoever builds this captures the shift.
The Meta-Framework
Three Questions, One Method

"What is healing?" → Body is programmable → Invest in programmable biology infrastructure

"How do treatments enter the mainstream?" → Cannabis template → Invest in psilocybin infrastructure before demand

"What is health?" → Optimization, not absence of disease → Invest in prevention/optimization infrastructure

Same method every time: ask the fundamental question, study the historical precedent, identify where the new paradigm is in the sequence, invest in infrastructure for what inevitably comes next.

Cross-Reference: The "Dumbed-Down Version" Indicator
When a dumbed-down version goes mainstream, the full paradigm shift is imminent. ChatGPT was the dumbed-down version of AI—and the entire TAM expanded to billions in a day. CBD was the dumbed-down version of cannabis. Functional mushrooms and microdosing are the dumbed-down version of psychedelic therapy. Ashwagandha and adaptogens are the dumbed-down version of alternative medicine. Track when the simplified version hits mass adoption—that's the leading indicator.