Dose Proportionality

A drug shows dose-proportional pharmacokinetics when clearance, volume of distribution and bioavailability do not themselves depend on dose. Under that condition exposure scales linearly, and a concentration-time profile from one dose can be rescaled to predict another. It is assessed by fitting a power model to exposure against dose and asking whether the slope sits close to one. Departures arise wherever something saturates: a transporter, a plasma protein binding site, a metabolising enzyme, or the receptor itself.

Most peptides are dose-proportional across their therapeutic range because the processes clearing them, non-specific proteolysis and glomerular filtration, operate nowhere near capacity. Where peptides do go non-linear it is usually through target-mediated disposition, in which binding to the receptor is itself a meaningful elimination route. That route saturates first, so clearance falls as dose rises and exposure climbs faster than proportionally, a pattern shared with therapeutic antibodies.

The practical value is predictive. If exposure is proportional, a dose adjustment has a calculable effect and exposure in an untested subgroup can be inferred rather than measured. If it is not, every step has to be characterised, and the direction of the non-linearity determines whether a dose increase is a modest change or a disproportionate one.

Two errors follow the term around. The first is extrapolating proportionality beyond the doses actually studied, which is precisely where saturation appears. The second is treating proportional exposure as proportional effect. Response follows a saturating concentration-effect curve, so doubling exposure near the top of that curve buys very little extra effect while reliably delivering the concentration-dependent adverse effects, which is the arithmetic that more is better claims ignore.