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Confidence and Prediction Intervals for Pharmacometric Models.


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.

SUBMITTER: Kummel A 

PROVIDER: S-EPMC6027739 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Confidence and Prediction Intervals for Pharmacometric Models.

Kümmel Anne A   Bonate Peter L PL   Dingemanse Jasper J   Krause Andreas A  

CPT: pharmacometrics & systems pharmacology 20180325 6


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 i  ...[more]

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