Educational Guide

The Peptide Dosing Problem: Why Online Protocols Can't Be Trusted

Search for peptide dosing and you'll find wildly contradictory advice. One source says 250mcg BPC-157 twice daily. Another says 500mcg once. A third recommends 750mcg. They can't all be right—and the reasons why reveal fundamental problems with how peptide protocols get created and shared.

Peptide Education15 min readJanuary 2, 2026

I was recently helping someone navigate BPC-157 research and watched them spiral through increasingly contradictory dosing advice. Forum A said 250mcg twice daily. Forum B insisted on 500mcg once daily minimum. A "peptide guru" on YouTube recommended 750mcg "for serious results." An underground PDF floating around suggested body-weight-based protocols with no sourcing.

None of them agreed. None of them cited primary research. All of them spoke with absolute confidence.

This is the peptide dosing problem in a nutshell—and it's more dangerous than most people realize.


Where Dosing Information Actually Comes From

To understand why peptide dosing advice is so unreliable, you need to understand its origins.

Source 1: Animal Studies (Scaled Badly)

Most peptide research exists in rodent models. When humans want to apply these findings, they need to convert doses.

The problem: There's no universally accepted method for doing this, and different approaches yield wildly different numbers.

Allometric scaling (based on body surface area) suggests very different doses than simple weight-based scaling. A dose that's 1mg/kg in a mouse might translate to:

  • ~0.08mg/kg by allometric scaling
  • ~1mg/kg by linear weight scaling

That's a 12x difference in the "correct" human dose from the same rodent data.

What actually happens: Someone reads a mouse study, does napkin math, posts a protocol online. That protocol gets copied, modified slightly, and reposted. Within a year, dozens of "recommended doses" exist, all traceable to one person's amateur pharmacokinetic calculation.

Source 2: Historical Clinical Trials (Misapplied)

Some peptides have been tested in humans for specific conditions. These studies provide real human dosing data—for those specific uses.

The problem: People extrapolate these doses to completely different applications.

Example: Thymosin Beta-4 (TB-500) was studied in cardiac patients at specific doses for cardiac repair. These doses get applied to tendon injuries, systemic healing, and recovery protocols—despite no evidence that the cardiac dose is appropriate for these uses.

Source 3: Bro-Science Telephone

This is the dominant source for most online protocols, and it works like this:

  1. Early adopter tries a dose, reports results
  2. Others copy it, some modify up or down
  3. Modifications get reported as "what works for me"
  4. "What works for me" becomes "recommended dose"
  5. Enough people say it that it becomes "established protocol"
  6. New users find this "established" information and treat it as evidence-based

The result: Doses that originated from one person's guess get enshrined as community knowledge without ever being validated.

Source 4: Vendor Marketing

Peptide suppliers have financial incentive to encourage higher doses:

  • Higher doses = faster use = more frequent purchases
  • "More is better" narratives drive sales
  • Conservative dosing recommendations make products seem weak

I've watched vendor "dosing guides" creep upward over time with no new evidence to support the increases.


Case Study: BPC-157 Dosing Chaos

Let's trace how we ended up with such inconsistent BPC-157 recommendations.

The rodent data: Most BPC-157 studies use doses of 10-50mcg/kg in rats and mice, sometimes higher.

Scaled to humans (using allometric conversion): This might suggest doses in the 1-5mcg/kg range, or roughly 70-350mcg for a 70kg human.

What the community recommends: 250-750mcg daily, sometimes higher.

The gap: The commonly recommended doses are at or above the high end of scaled rodent doses—despite no human pharmacokinetic data to suggest this is appropriate.

How we got here: Early adopters, unsure if it was working, tried higher doses. Those who "felt something" (possibly placebo) reported their higher doses. Others copied them. The higher numbers propagated because they seemed "more likely to work."

The reality: We don't know the optimal human BPC-157 dose. We don't know if 250mcg is subtherapeutic, optimal, or excessive. We're guessing—confidently.


Why This Matters More Than You Think

Incorrect dosing isn't just about efficacy. There are real risks.

Subtherapeutic Dosing Wastes Money and Time

If you're running a dose that's too low to produce meaningful effects, you're:

  • Spending money on an expensive placebo
  • Wasting time on an intervention that isn't working
  • Drawing incorrect conclusions about the peptide's utility

Excessive Dosing Has Unknown Risks

Peptides aren't "natural supplements"—they're bioactive compounds that affect signaling pathways. Higher isn't automatically better.

Potential concerns with excessive dosing:

  • Receptor desensitization (less response over time)
  • Off-target effects at higher concentrations
  • Feedback loop disruption
  • Increased side effect probability
  • Unknown long-term consequences

We don't have safety data for the doses the community commonly uses because those doses were never formally studied.

Growth Hormone Secretagogues: A Specific Warning

GH secretagogues (ipamorelin, CJC-1295, GHRP-6, etc.) are particularly concerning for dose escalation.

The pattern I see:

  1. Start at "recommended" dose
  2. Don't see dramatic results (because expectations are unrealistic)
  3. Increase dose
  4. Still not satisfied, increase again
  5. Eventually running doses that produce supraphysiological GH levels

The problem: Chronically elevated GH has known risks (insulin resistance, organ growth, potential cancer associations). The community's dose-escalation tendencies may be pushing people into genuinely risky territory.


The Factors Nobody Accounts For

Even if we had "correct" doses from good research, individual response varies enormously based on factors that online protocols ignore.

Body Composition

Most doses are given in absolute terms (e.g., "500mcg BPC-157") rather than body-weight-adjusted doses.

A 120lb person and a 250lb person getting the same absolute dose are getting very different effective doses.

Administration Route

The same dose produces different effects based on how it's delivered:

  • Subcutaneous vs. intramuscular
  • Injection site location
  • Injection depth
  • Local vs. systemic distribution

Online protocols rarely specify these parameters carefully, and even when they do, they're often arbitrary.

Individual Variation

Pharmacogenomics tells us that drug response varies enormously between individuals due to:

  • Receptor density differences
  • Enzyme activity variations
  • Binding protein levels
  • Underlying health status
  • Concurrent medications

The "optimal dose" for one person might be subtherapeutic or excessive for another.

Peptide Quality Variation

Here's a factor people never discuss: if peptide purity and potency vary between suppliers (they do), then the "same dose" from different sources isn't the same dose at all.

  • 500mcg of 98% pure peptide ≠ 500mcg of 85% pure peptide
  • Degraded peptide may have reduced activity even if weight is correct
  • Mislabeled peptides change the equation entirely

How to Think About Dosing With Limited Information

Given all this uncertainty, how should someone approach peptide dosing? Here's my framework.

Start Lower Than "Recommended"

If the community consensus is 500mcg, consider starting at 250mcg.

Rationale:

  • Community doses tend to drift upward over time
  • Lower doses have lower risk
  • You can always increase; you can't undo excess
  • You might discover lower doses work fine for you

Titrate Based on Response

Rather than jumping to a "target dose," increase gradually:

  • Start at your chosen conservative dose
  • Maintain for a reasonable period (2-4 weeks typically)
  • Assess: Is there response? Side effects?
  • Increase only if needed, in small increments
  • Find the minimum effective dose for you, not the maximum tolerated dose

Define Success Criteria in Advance

Before starting, define what you're looking for:

  • What specific outcome would indicate "working"?
  • What timeline is reasonable to assess this?
  • What side effects would cause you to stop or reduce?

Without pre-defined criteria, you'll rationalize any outcome and lose the ability to make objective assessments.

Keep Records

Document your protocol and response:

  • Date, dose, administration details
  • Subjective effects (energy, recovery, etc.)
  • Objective measures if possible (healing time, bloodwork)
  • Side effects or concerns

This seems tedious but is essential for learning what actually works for you.

Be Willing to Conclude "Not Worth It"

If modest doses aren't producing meaningful effects, increasing indefinitely isn't the answer. Sometimes the conclusion is that a peptide doesn't work for your situation, or that the effect size is too small to justify continued use.

This is valuable information, but only if you're willing to accept it.


What Good Dosing Guidance Would Look Like

For context, here's what evidence-based dosing guidance would require:

Phase 1 Data

Dose-escalation studies in humans measuring:

  • Pharmacokinetics (absorption, distribution, half-life)
  • Dose-response relationships
  • Side effect profiles at various doses
  • Maximum tolerated dose

Phase 2/3 Data

Efficacy studies showing:

  • What doses produce clinical benefit
  • Whether higher doses produce more benefit
  • Optimal dosing frequency
  • Duration of treatment needed

For most research peptides, we have none of this.

That's not a reason to never use them—it's a reason to approach dosing with appropriate humility rather than the false confidence that dominates online discourse.


The Dosing Information We Actually Need

Here's what I'd want to know before trusting any dosing recommendation:

  1. What's the source? Animal data? Human trial? "Bro experience"?
  2. How was human dose derived? What scaling method? What assumptions?
  3. What's the sample size? One guy on Reddit? Hundreds of users? Formal study?
  4. What were the outcomes measured? Subjective? Objective? Both?
  5. What's the range of response? Did everyone respond similarly? Huge variation?
  6. What's the conflict of interest? Is the source selling something?

If a dosing recommendation can't answer these questions, treat it as a starting hypothesis, not established fact.


My Uncomfortable Conclusion

Most peptide dosing protocols circulating online are:

  • Derived from poor-quality extrapolation
  • Propagated through bro-science telephone
  • Influenced by financial incentives to recommend more
  • Presented with false confidence
  • Lacking the data that would actually establish correct doses

This doesn't mean all peptide use is irrational—but it does mean that anyone taking peptides should understand they're making educated guesses, not following validated protocols.

The appropriate response isn't to chase the "perfect dose" from online research. It's to:

  • Start conservative
  • Titrate based on individual response
  • Keep good records
  • Maintain epistemic humility about what you actually know

The peptide dosing problem won't be solved by finding the right forum or the right guru. It requires accepting uncertainty and working within it intelligently.


This represents my opinion on the current state of peptide dosing information. I'm not providing dosing recommendations—I'm explaining why you should be skeptical of anyone who does.

References

Allometric Scaling in Drug Development.

Interspecies Dose Conversion.

Pharmacokinetic Variability in Humans.

Growth Hormone: Risk-Benefit Assessment.

Peptide Stability and Degradation.

DSC

Dr. Sarah Chen

PhD, BiochemistryResearching Peptides Editorial Team

Dr. Chen specializes in peptide biochemistry and has contributed extensively to research literature reviews. Her work focuses on translating complex scientific findings into accessible content for researchers and enthusiasts.