Research Timeline Calculator
See how a peptide builds up and clears over a research protocol. Enter a half-life and dosing frequency to chart time-to-steady-state, accumulation, and washout.
Educational model — research use only
Long half-life — accumulates ~2× over the first month of weekly dosing.
The compound's terminal elimination half-life.
How often a dose is administered (one dose every 7 days).
8 doses modelled, then washout.
Time to steady state
35 days
~97% (5 half-lives) · ~90% by 23.2 days
Accumulation ratio
2.00×
peak ≈ 200% of a single dose
Steady-state swing
50%
peak 200% → trough 100%
Washout after last dose
35 days
~97% cleared (5 half-lives)
Steady state
When doses are given repeatedly, the amount in the system rises until the amount cleared between doses equals the amount added. That plateau is "steady state." It takes roughly five half-lives to reach (~97%), regardless of how often you dose — a longer half-life means a longer build-up.
Accumulation ratio
This is how much higher the steady-state peak sits versus a single dose. It is driven by the half-life relative to the dosing interval: dosing more often than the compound clears (a long half-life) produces more accumulation. The formula used is R = 1 / (1 − e−k·τ), where k is the elimination rate and τ is the dosing interval.
Washout
After the last dose, the curve decays by the same half-life — about five half-lives to fall to ~3% of the steady-state level.
Model assumptions
A simplified one-compartment model with instantaneous input and first-order elimination, plotted as a percentage of one dose. It deliberately ignores absorption rate, bioavailability, distribution phases, active metabolites, and individual variation, so treat it as an illustration of timing — not a prediction of blood levels.
Research-use-only educational model. This illustrates the general shape of accumulation and washout from a compound's half-life — it is not a blood level, not a recommended dose or schedule, and not medical advice. Real pharmacokinetics vary between individuals and depend on absorption, bioavailability, and other factors not modelled here.