Real-world GLP-1 and peptide adherence insights from anonymised observational tracking data.
Halflife Labs publishes aggregate observational findings derived from opted-in protocol tracking data. Insights are published only after sufficient anonymised data has been collected for a specific research question and statistical confidence thresholds have been met. The dataset tracks longitudinal adherence patterns, dose escalation timing, compound stacking behavior, and protocol persistence across GLP-1, peptide, and TRT protocols.
How insights are generated and when they are published.
All insights are observational, non-interventional, and retrospective. Halflife does not assign protocols, control dosing, or influence user behavior. Findings describe observed aggregate patterns in self-reported tracking data — not causal relationships.
Reports are published only when the opted-in dataset reaches a predefined sample size and observation window for a specific research question. Each report defines its own cohort inclusion criteria, minimum sample size, and statistical confidence threshold.
Research questions the current dataset is designed to answer.
Each report will be published when its target sample size and observation window are met. Target thresholds are listed per report.
Comparative week-by-week adherence rates, dose escalation timing, side effect frequency, and dropout patterns between tirzepatide and semaglutide users in a self-managed population. Observational comparison — not head-to-head trial.
Which compounds are most commonly added to tirzepatide and semaglutide protocols, in what order they are introduced, and observed adherence changes after stacking. Compounds of interest: BPC-157, TB-500, CJC-1295/Ipamorelin, testosterone.
Observed starting doses, escalation intervals, and time to steady state in compounded tirzepatide users compared to FDA label recommendations. Includes adherence correlation by escalation speed. Observational only — no dosing recommendations.
How observed adherence rates change as users add compounds to a base TRT protocol — from single-compound TRT to 4+ compound stacks including GH secretagogues, peptides, and GLP-1 medications. Identifies observed adherence inflection points by stack size.
Topics the Halflife dataset is structured to investigate.
Week-by-week adherence, dropout timing, and protocol persistence for tirzepatide and semaglutide users.
Which compounds are combined, in what sequence, and how stacking affects observed adherence and protocol persistence.
Real-world escalation intervals compared to label recommendations for GLP-1 medications.
How the number of simultaneously tracked compounds correlates with observed adherence rates over time.
Long-term adherence patterns for testosterone cypionate protocols with and without concurrent peptide stacking.
Reported side effect frequency correlated with compound type, dose level, and protocol duration.
The Halflife app is the source of all protocol tracking data used in this research.
Every insight published on this page is derived from anonymised injection logs, dose records, weight entries, and symptom reports collected through the Halflife iOS app. Users who opt in to research contribution have their protocol data aggregated at the cohort level for analysis. Published findings are surfaced directly in the app's Discover tab as they become available.
Access observational protocol data for institutional research or integration.
Halflife Labs provides structured access to anonymised, aggregated protocol outcome data for academic researchers, telehealth platforms, and pharmaceutical companies. All access models support IRB-compatible research frameworks and follow opt-in consent standards.
Research collaboration inquiries: contact@halflife-labs.com