Estimation of population characteristics of pharmacokinetic parameters from routine clinical data
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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.
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- Estimation of population characteristics of pharmacokinetic parameters from routine clinical data
Journal of Pharmacokinetics and Biopharmaceutics
Volume 5, Issue 5 , pp 445-479
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers-Plenum Publishers
- Additional Links
- parameter estimation
- maximum likelihood
- population parameters
- Industry Sectors
- Author Affiliations
- 1. Division of Clinical Pharmacology, Department of Medicine, and the Department of Laboratory Medicine, University of California, 94143, San Francisco, California
- 2. School of Business Administration, University of California, 94720, Berkeley, California