Pharmacokinetics

Pharmacokinetics: Concept Architecture

Orientation and learning roadmap

This page follows a drug dose through absorption, distribution, metabolism, and elimination, then connects concentration-time measures to a worked calculation. It closes by explaining population variation, exposure-response evidence, and the limited but useful role of pharmacokinetic inputs in health economic modelling.

Follow the drug through the body

After administration, a drug may enter systemic circulation, distribute among tissues, undergo metabolic transformation, and leave the body through renal or other pathways. The route, formulation, organ function, interacting medicines, and patient characteristics can change the concentration-time profile.

Absorption describes entry from an extravascular dose; an intravenous bolus reaches systemic circulation directly. Distribution describes movement between blood and tissues, metabolism changes chemical form, and excretion removes drug or metabolites. These processes are often grouped as ADME, but a measured plasma concentration is a useful marker rather than a complete description of concentration at every site of action.

Quantities used to describe exposure

Pharmacokinetic (PK) analysis specifies the measured substance, biological matrix, dose and timing, sampling schedule, and model assumptions. Common summary quantities describe different aspects of a concentration-time curve and should retain their units.

The elimination half-life is the time for concentration to halve during a specified terminal phase under the relevant model. Exposure metrics do not by themselves specify therapeutic benefit or harm; those outcomes require pharmacodynamic or exposure-response evidence. For oral dosing, bioavailability and absorption kinetics affect how dose relates to systemic exposure.

Worked example: a one-compartment intravenous dose

Suppose a hypothetical 100 mg intravenous bolus is instantly mixed in a single compartment with apparent volume $V=20$ L and linear clearance $CL=2$ L/h. The example assumes first-order elimination, time-constant parameters, and no additional dose; it is not a clinical dosing recommendation.

$$\begin{aligned} C_0&=\frac{D}{V}=\frac{100\ \mathrm{mg}}{20\ \mathrm L}=5\ \mathrm{mg/L},\\ k&=\frac{CL}{V}=0.10\ \mathrm{h}^{-1},\\ C(t)&=C_0e^{-kt},\\ t_{1/2}&=\frac{\ln2}{k}\approx6.93\ \mathrm h. \end{aligned}$$

After 10 hours, the model predicts $C(10)=5e^{-1}\approx1.84$ mg/L. For this intravenous linear model integrated to infinite time, $\mathrm{AUC}_{0\to\infty}=D/CL=50$ mg·h/L. Oral dosing would introduce bioavailability and absorption assumptions, while multi-compartment or nonlinear elimination would require a different concentration-time expression.

Population variation and model checks

Population PK models estimate typical parameters and between-person variation from concentration observations while accounting for dosing histories and sampling times. Covariates such as renal function, body size, age, and interacting treatments may help explain variation if supported by data and a suitable model.

Model assessment should compare predicted and observed concentrations, examine residual patterns and exposure ranges, and evaluate performance in patient groups relevant to the intended use. Sparse sampling, assay error, adherence uncertainty, and model misspecification can affect estimates. Extrapolating to a different route, dose, formulation, or organ-function group requires additional evidence rather than a change of units alone.

From exposure to clinical and economic outcomes

Pharmacodynamics concerns what a drug does to the body, while PK concerns the body's influence on drug exposure over time. An exposure-response relationship can connect concentration or AUC to efficacy, adverse events, and dose selection, but the relationship must be estimated and assessed for confounding and clinically relevant ranges.

In a health economic model, different doses or patient subgroups may change drug acquisition, monitoring, event rates, adherence, and quality-adjusted life-years (QALYs). A PK model may inform those pathways when linked to validated clinical evidence, yet AUC alone cannot be converted into a QALY gain or a cost-effectiveness conclusion. Dosing changes may also have implementation and safety consequences that are outside a simple one-compartment equation.

Interpretation and common errors

Clearance and half-life are related but not interchangeable: half-life also depends on distribution volume under the simple first-order model. The same AUC may conceal different peak concentrations, so exposure summaries should match the biological and clinical question.

The formula $D/CL$ for AUC applies to an intravenous dose with linear systemic kinetics and the stated integration interval, not to every oral product or saturable pathway. A measured terminal half-life can reflect distribution as well as elimination when a multi-compartment profile is compressed into one number. Regulatory bioequivalence criteria address specified PK comparisons and should not be mistaken for an unrestricted claim of identical clinical outcomes in every population.

Sources and further learning

The regulatory sources below show how population PK and exposure-response analyses are used and reported. Their scope differs by purpose, so a drug-specific study should also use the relevant product and clinical evidence.

• US Food and Drug Administration (2022), Population Pharmacokinetics: Guidance for Industry. This addresses population variability, covariates, and model evaluation.
• US Food and Drug Administration, Exposure-Response Relationships: Study Design, Data Analysis, and Regulatory Applications. This connects drug exposure to efficacy and safety questions.
• International Council for Harmonisation, ICH M13A, Bioequivalence for Immediate-Release Solid Oral Dosage Forms. This identifies AUC and peak concentration as distinct comparison measures within its defined scope.