Granular consent
Per data category, protocols, bloodwork, training, nutrition, outcomes. Opt in to all or some. Every category requires explicit Art. 9(2)(a) consent at the moment of opt-in.
Research
The studies the world can't run anywhere else.
Most clinical research on protocols, peptides, and off-label compounds doesn't exist, because the cohort doesn't exist in any traditional EHR. VitaLog users opt into anonymized aggregate sharing because they want that gap closed. This is the roadmap.
What you're consenting to
If you opt into the Research Program, anonymized aggregate datasets (k-anonymity ≥ 5) may be licensed to academic researchers, contract research organizations, and pharmaceutical sponsors. Aggregate query results only, never your individual records, photos, journal entries, or identity. Every recipient signs a Data Access Agreement that prohibits re-identification attempts and downstream redistribution.
You can withdraw at any time via Settings → Privacy → Research Program. Future contributions stop immediately. Past contributions can be excluded from new aggregate queries by request to privacy@vitalog.io. The Research Program is opt-in by default; if you do not enable it, no data derived from your account leaves the personal-analytics path. Full disclosure in the Privacy Policy § 4.
Harm reduction needs a real evidence base.
Tens of millions of people run protocols, peptide cycles, and off-label compound regimens. Almost none of it shows up in traditional clinical research because (a) it's prescriptively off-label, (b) clinicians don't ask, and (c) the few who do ask get incomplete or selectively-honest answers. The result: the people running these protocols make decisions on anecdote, broscience, and forum lore.
VitaLog flips that. The app is the place people log honestly, because it's their tool, their data stays theirs, and tracking is the whole point. Aggregated across thousands of consenting users, that produces something genuinely new: a longitudinal, multi-modal, consent-based dataset on protocols-as-actually-run. Available, under strict anonymization, to academic researchers running IRB-approved studies.
Every study that gets published using this dataset closes a gap. Better evidence → better harm-reduction guidance → fewer adverse outcomes. That's the loop.
Studies we want to enable.
These are vision-stage, none are yet running. The roadmap is here so prospective users see what their participation makes possible and prospective researchers know what's in scope.
R-01
TRT dose-response and biomarker trajectories
Multi-year longitudinal: how do total-T, free-T, E2, hematocrit, lipids, and SHBG actually move across ester, frequency, and protocol phase? With ancillary subgroups (AI, hCG, etc.) clustered for harm-reduction signal.
R-02
GLP-1 weight-loss adherence & rebound
Discontinuation rates, side-effect-driven titration patterns, post-discontinuation weight rebound, body-composition vs scale-weight changes. The data clinical trials end before they capture.
R-03
Peptide harm-reduction patterns
BPC-157, TB-500, sermorelin, ipamorelin, MK-677, dose, reconstitution, stack composition, self-reported outcomes vs side effects. The cohort literally does not exist anywhere else.
R-04
Cycle & PCT effectiveness
For users running on/off cycles: how do biomarkers actually return, on what timeline, with which PCT protocols? Longitudinal HPG-axis recovery data with statistical confidence.
R-05
Hormonal-cycle-aware training
For users syncing training and nutrition to the menstrual cycle: does periodization actually correlate with strength outcomes, body composition, or recovery markers? Or is the research-grade picture different from the influencer one?
R-06
Supplement-driven biomarker shifts
Magnesium, vitamin D, NMN, creatine, omega-3, etc., paired with bloodwork over time. Cuts through marketing claims with statistical reality.
How participation works.
Free unlock
Joining the Research Program unlocks every research-grade analytics surface in the app, for free. No paid tier; the value exchange is honest.
Anonymization before release
Your data is not a row in any researcher's CSV. Every release is an aggregate query with k-anonymity ≥ 5, run inside our infrastructure. No raw rows leave.
Withdrawal at any time
One toggle in Settings. Future data stops contributing immediately. Past contributions can be excluded from new aggregate queries on request.
Public results
Every study published using the Research Program data gets linked back here, on this page, so the community can see what their participation enabled.
What we won't share
Individual-level rows. Journal entries. Progress photos. Email or location data. Anything that could re-identify you. Architectural promise, not just policy.
Studies enabled by the Research Program.
No publications yet, the Research Program is in early enrollment. As studies wrap, this section turns into a list of preprints, peer-reviewed papers, and conference posters with links.
Coming soon
First studies in the roadmap above are expected to begin enrollment-paired analyses once cohort sizes pass research-grade thresholds. Researchers interested in proposing earlier, see the academic page.
Sign in to opt in.
Joining the Research Program takes 30 seconds. Free account, EU-hosted, granular per-category consent (you pick what aggregates contribute), and you can withdraw anytime, your future data simply stops counting toward releases.
After sign-in, head to Settings → Privacy → Research Program to flip the per-category toggles. Every category requires explicit GDPR Art. 9(2)(a) consent at the moment of opt-in.
Researcher? See the academic-access process at /about/researchers.