Confidence and Prediction Intervals for Pharmacometric Models. (25th March 2018)

• Record Type: Journal Article
• Authors: Kümmel, Anne; Bonate, Peter L.; Dingemanse, Jasper; Krause, Andreas
• Is Part Of: CPT: pharmacometrics & systems pharmacology. Volume 7:Number 6(2018)
• Page Start: 360
• Page End: 373
• Publication Date: 2018-03-25
• Subjects: Pharmacokinetics -- Periodicals; Pharmacology -- Periodicals; Pharmacokinetics; Periodicals; 615.05
• DOI: 10.1002/psp4.12286
• Languages: English
• ISSNs: 2163-8306

Abstract

Abstract : Supporting decision making in drug development is a key purpose of pharmacometric models. Pharmacokinetic models predict exposures under alternative posologies or in different populations. Pharmacodynamic models predict drug effects based on exposure to drug, disease, or other patient characteristics. Estimation uncertainty is commonly reported for model parameters; however, prediction uncertainty is the key quantity for clinical decision making. This tutorial reviews confidence and prediction intervals with associated calculation methods, encouraging pharmacometricians to report these routinely.