What N-of-1 Cannot Do
A single-subject self-experiment cannot produce population-level effect estimates. It cannot establish that a result generalizes from me to anyone else. It cannot rule out my own placebo effect with the cleanliness of a double-blind trial. The published literature on personalized N-of-1 trial methodology is honest about all of this -- the framing is "this can produce defensible personalized answers" rather than "this can produce clinical evidence" 1 2.
Acts by promoting aldehyde and alcohol metabolism of foods.†
† These statements have not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure, or prevent any disease.
The structure-function claims H180 makes are tied to the published mechanism literature on the underlying ingredients (DHM induces ADH and ALDH; SAG delivers intact glutathione; fulvic acid assists membrane transport), not to my self-test data. The self-tests are why I am personally confident the combination works for me. The mechanism literature is why the claims are defensible in front of a regulatory reviewer.
The Fatigue Exception
There is one specific limitation worth calling out by name. The H180 formula reliably reduces my morning-after symptom score against my own placebo baseline at moderate drinking patterns (4-6 drinks). It does not reliably address the fatigue component when drinking happens on top of poor sleep, jet lag, or already-tired baseline state. (the fatigue exception is the limitation that frustrated me most, because it is exactly the use case I would most want the formula to address, and it does not.)
The likely reason is that fatigue from sleep deprivation has a different mechanism from acetaldehyde-related cognitive fog, and DHM and SAG act on the latter rather than the former. Honest framing: the formula does what it does within the boundaries of the patterns I tested, in my own n=1 data at least.
Confounders I Could Not Eliminate
Self-blinding is the largest confounder. I tried opaque capsules with rotating colors but cannot honestly claim full blinding. Order effects -- improvement over time as I got better at the protocol -- were a real risk that I tried to control by re-running placebo and earlier candidates at intervals. Day-of-week, season, and cumulative drinking exposure across the testing window were all observable but not eliminable confounders. I logged them and discounted findings that aligned with them.
What Counts as a Result
Helps you feel fresh.†
† These statements have not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure, or prevent any disease.
A "result" in this protocol meant a difference between treatment and placebo of at least 2 points on the 0-to-10 symptom scale, replicated across at least three independent test nights, with no contradictory result during the same testing window. This is a much weaker bar than statistical significance in a clinical trial, but it is also the appropriate bar for n=1 directional decisions about ingredient inclusion. The 2005 systematic review of hangover-prevention RCTs is a good reminder that even properly-powered RCTs in this category often fail to find effects 3.
Supports balanced consumption of alcohol (from all sources of food and drink).†
† These statements have not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure, or prevent any disease.
What This Page Is Not Claiming
The point of being explicit about limitations is not to undermine the formula but to keep the marketing honest. Self-experimentation gives you defensible personal answers but it does not give you generalizable population claims, adn pretending otherwise is the failure mode that wrecks most supplement-founder narratives. The H180 claims are what the published mechanism literature supports. The self-test data is why I personally trust the formula. Both pieces matter. Conflating them would be dishonest.
For the protocol that produced the self-test data, see 150 Self-Tests -- The Method. For the drink-counting discipline that made the data interpretable, see Drink Counting Methodology.