Journal of Pharmacokinetics and Biopharmaceutics

, Volume 5, Issue 5, pp 445-479

First online:

Estimation of population characteristics of pharmacokinetic parameters from routine clinical data

  • Lewis B. SheinerAffiliated withDivision of Clinical Pharmacology, Department of Medicine, and the Department of Laboratory Medicine, University of California
  • , Barr RosenbergAffiliated withSchool of Business Administration, University of California
  • , Vinay V. MaratheAffiliated withSchool of Business Administration, University of California

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


A general data analysis technique estimates average population values of pharmacokinetic parameters and their interindividual variability from clinical pharmacokinetic data gathered during the routine care of patients. Several drug concentration values from each individual, along with dosage information and the values of other routinely assessed variables suffice for purposes of analysis. The Maximum Likelihood principle estimates underlying population values without the necessity for the intermediate estimation of individual parameter values. The approach is quite general, permitting the use of nonlinear statistical models with both fixed and random effects. Complex expressions involving physiological variables can be used to define the pharmacokinetic parameters. Thus, the relationship of physiological factors to parameter values can be assessed. The generality and appropriateness of the analysis technique are demonstrated by analysis of a set of data derived from 141 patients receiving the drug digoxin.

Key words

statistics parameter estimation maximum likelihood population parameters