How Our Pharmacokinetic Models Work

Why Visualizing Medication Levels Matters

When you inject a compound, your body absorbs and eliminates it over time. The question every protocol user wants answered is: “What are my levels doing between doses?”

Blood work gives you a snapshot - one point in time. Regimen’s PK curves give you the full picture between blood draws. They show you:

• Whether your dosing frequency maintains stable levels or creates peaks and valleys
• When you’re at your highest estimated level (peak) and lowest (trough)
• How changing your injection frequency would change your level stability
• Whether your current schedule reaches steady state

This isn’t a replacement for blood work - it’s a tool that helps you understand your protocol and have better conversations with your healthcare provider.

What the Half-Life Visualizer Shows

Regimen’s half-life visualizer and in-app PK curves show estimated medication levels over time for injectable compounds.

Estimated peak concentration

when levels are highest after injection

Estimated trough concentration

when levels are lowest before your next dose

Steady-state visualization

how repeated dosing at regular intervals builds to a stable concentration range

Overlapping compound curves

when tracking multiple compounds, see how their profiles interact on the same timeline

The Pharmacokinetic Model

Regimen uses a one-compartment model with first-order absorption (Bateman) - the most widely used pharmacokinetic model for depot (injected) medications, and the one that produces the characteristic rise-to-peak then decay curve you see in the app.

The core equation

C(t) = D × (ka / (ka − ke)) × (e(−ke × t) − e(−ka × t))

C(t) = estimated concentration at time t

D = dose administered

ke = elimination rate constant, derived from half-life: ke = ln(2) / t½

ka = absorption rate constant, derived from the compound’s time-to-peak (tMax)

t = time since administration

For repeated dosing, the model applies superposition - each new dose adds to the remaining concentration from previous doses, converging toward a steady-state range after approximately 4-5 half-lives.

What this means in practice: If you inject testosterone cypionate (half-life ~6.9 days) every 3.5 days, the model shows how each injection builds on residual levels from the previous dose, eventually reaching a stable peak-trough range. This helps you understand WHY splitting your dose into more frequent injections creates more stable levels.

Data Sources

Half-life values used in Regimen’s models come from:

Published clinical pharmacokinetic studies - peer-reviewed research on specific compounds and esters

FDA prescribing information - for approved medications (testosterone cypionate, semaglutide, tirzepatide (tirz), etc.)

Established pharmacology references - standard pharmacokinetic references for well-characterized compounds

For research peptides (BPC-157, TB-500, ipamorelin, etc.), published human PK data is often limited. In these cases, Regimen uses available animal model PK data, established community protocols where clinical data is absent, and conservative estimates when multiple sources disagree. All half-life values are documented in our half-life data reference.

Important Limitations

These are estimates, not blood tests. PK curves show what standard pharmacokinetic models predict for a given dose and schedule. They do not account for:

Individual variation

Metabolism, body composition, injection site, injection technique, and genetics all affect how your body absorbs and eliminates compounds. Two people on the same protocol will have different actual blood levels.

Bioavailability differences

Subcutaneous vs. intramuscular injection, carrier oil formulation, injection depth, and absorption rate all affect actual concentrations.

Multi-compound interactions

The PK model treats each compound independently. It does not model how compounds may influence each other’s effective levels.

Non-linear kinetics

Some compounds at some doses may exhibit saturable metabolism. The one-compartment Bateman model assumes linear (first-order) absorption and elimination.

Compounded medication variability

Compounded medications may vary in potency and formulation quality between sources. PK models assume the labeled dose is accurate.

The PK visualizer is a tracking tool. It helps you understand the general shape of your dosing curves, compare injection frequencies, and visualize steady-state concepts. It is not a diagnostic tool and should not be used to make medical decisions without consulting your healthcare provider.

How We Handle Updates

When we find better PK data, correct an error, or add a new compound:

1. We update the half-life value in our database

2. We document the change in our half-life data reference

3. Existing PK visualizations update automatically with the corrected data

4. We do not backdate or alter historical dose logs - your tracking data stays exactly as you logged it

Contribute or Correct

If you find a half-life value that seems wrong, or if you know of a published PK study we haven’t incorporated, please email us at support@helloregimen.com with the source. We review and update our data regularly.