In population pharmacokinetics, what is the difference between fixed effects and random effects?

• A. Fixed effects are typical population parameter estimates; random effects capture inter-individual variability around those estimates.
• B. Fixed effects capture inter-individual variability.
• C. Random effects are used to estimate system noise.
• D. Fixed effects vary across individuals; random effects are constant.

Answer: (A)

In population pharmacokinetics, you separate what is common to the whole population from what varies between individuals. The fixed effects define the typical, population-average values of PK parameters—things like the usual clearance and volume of distribution. They set the baseline shape and scale that applies to the “average” person in the dataset. The random effects quantify how each individual deviates from that average. Each person has an eta term that represents their departure from the typical value, capturing inter-individual variability. These deviations are usually assumed to be normally distributed with mean zero and a estimable variance, so the individual parameter is essentially the fixed effect value adjusted by the person’s random effect (often modeled multiplicatively as parameter_i = TVP × exp(eta_i), depending on the parameterization). This framework lets you describe both the common pharmacokinetic behavior and the variability across individuals, while another component (the residual error) accounts for within-subject noise and measurement error. Thus, the described distinction—fixed effects as typical population parameter estimates and random effects as capturing inter-individual variability around those estimates—is the correct interpretation.