Research-backed guides, tool references, and protocol strategies for people running GLP-1, peptide, and performance protocols seriously.
Adherence rate, dose gaps, and weekly streaks tell different stories. Here's what each metric actually means for your protocol and how to act on low-adherence patterns before they derail a cycle.
How to calculate the exact volume of bacteriostatic water needed for any vial size, and why the math changes when you switch concentration targets.
Understanding the pharmacokinetic window for semaglutide, tirzepatide, and peptides so your injection timing is a deliberate choice, not a guess.
Dual vs single receptor agonism shapes how each compound behaves over time. What the tracking differences look like across 12 weeks — and which metrics diverge first.
Rotating correctly prevents lipohypertrophy and absorption variability. A simple 7-site map and the rotation rules that keep your pharmacokinetics consistent.
Weight on a GLP-1 protocol can mask muscle loss or significant fat change. How to track waist circumference, body fat estimates, and FFMI alongside your weight trend to see what's actually happening — and how to log it so your analytics tell the real story.
Escalation timelines differ by compound. The signals in your symptom and tolerance logs that indicate readiness — versus the signals that say stay put.
BPC-157 has no clinical dosing consensus, which makes structured logging non-optional. Key metrics to establish at baseline and how to use symptom logs to assess response.
A1C, fasting insulin, lipid panel, CMP — the baseline and follow-up bloodwork that gives your weight and adherence data meaningful context.
GLP-1 receptors are present in the brain. The sleep quality and mood data you log during early cycles often predict nausea tolerance and long-term adherence better than dose alone.
A simple formula for calculating runway from current stock, your dose schedule, and typical dose waste — with a reorder buffer you can actually trust.
How to calculate true cost per dose across pen, compounded vial, and oral formats — including reconstitution waste, storage costs, and the breakeven point for annual vs monthly billing.
Most stalls aren't random. Adherence dips, undereating, dose timing drift, and sleep disruption each leave a different signature in the logs. How to use 4–6 weeks of data to diagnose the cause and decide whether a protocol adjustment is warranted — or whether the stall is just biological noise.
Running both simultaneously creates attribution problems. A simple symptom-tagging method that helps you separate compound effects across an 8-week stack.
IV vs subcutaneous vs oral NAD+ have different bioavailability profiles and side-effect curves. What a baseline logging setup looks like for each format and which metrics tend to move first.