Dataset Information
Modelling the dose-response relationship: the fair share of pharmacokinetic and pharmacodynamic information.
Ontology highlight
ABSTRACT: Aims
The aim of this paper is to investigate the role of drug concentration samplings in the modelling of the dose-response relationship.Methods
Using an initial PK/PD model, a reference dataset was simulated. PK and PD samples were extracted to create reduced datasets. PK/PD and K-PD models were fitted to theses reduced datasets. Post hoc estimates from both types of models were compared to the initial PK/PD model and performance was assessed.Results
K-PD models were largely biased when the drug has a nonlinear elimination. PK/PD models with 1 PK and 2 PD samples were superior to K-PD models with 3 PD samples. PK/PD models with 1 or 2 PK samples and 3 PD samples proved to be superior to K-PD models with 4 PD samples.Conclusions
K-PD models should not be used when the drug has nonlinear elimination. K-PD models should not replace PK/PD modelling but are an alternative approach if the PD information is large enough.
SUBMITTER: Gonzalez-Sales M
PROVIDER: S-EPMC6396849 | biostudies-literature | 2017 Jun
REPOSITORIES: biostudies-literature
Publications
Modelling the dose-response relationship: the fair share of pharmacokinetic and pharmacodynamic information.
British journal of clinical pharmacology 20170214 6
<h4>Aims</h4>The aim of this paper is to investigate the role of drug concentration samplings in the modelling of the dose-response relationship.<h4>Methods</h4>Using an initial PK/PD model, a reference dataset was simulated. PK and PD samples were extracted to create reduced datasets. PK/PD and K-PD models were fitted to theses reduced datasets. Post hoc estimates from both types of models were compared to the initial PK/PD model and performance was assessed.<h4>Results</h4>K-PD models were lar ...[more]