Setting Confidence Intervals for Drug Concentrations from Pharmacokinetic Parameters

Abstract

OBJECTIVE:

To describe and illustrate a convenient method of forecasting drug concentrations with confidence intervals (CIs) using the means and standard deviations of relevant pharmacokinetic parameters (e.g., clearance and volume of distribution).

DESIGN:

Using summary statistics from previously published reports, a Monte Carlo technique employing a SAS random number generator creates an arbitrarily large “sample” of each pharmacokinetic parameter. A related “sample” of drug concentrations is provided by inserting the parameters into the appropriate model. A point estimate of the mean drug concentration with a CI is calculated using standard statistical methods. Both the one- and two-compartment body models are illustrated using previous investigations of gentamicin and lidocaine, respectively.

RESULTS:

One-compartment simulations describe CIs for gentamicin concentrations that vary widely depending on the source of the clearance and volume of distribution parameters. Lidocaine CIs using a two-compartment analysis indicate a range of concentrations quite different from the expected mean.

CONCLUSIONS:

CIs provide a perspective of drug therapy that is considerably more informative than a simple point estimate of the mean concentration.