ArticleBritish journal of clinical pharmacology2017
Modelling the dose-response relationship: the fair share of pharmacokinetic and pharmacodynamic information.
Article in British journal of clinical pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- From Trait-Structured Within-Host Dynamics to SIR Models: A Multiscale Framework With Re-Exposure.Bulletin of mathematical biology · 2026Article
- Pharmacokinetic/Pharmacodynamic Modeling of the Acute Heart Rate Effects of Delta-9 Tetrahydrocannabinol and Its Major Metabolites After Intravenous Injection in Healthy Volunteers.European journal of drug metabolism and pharmacokinetics · 2025Article
- Model-based interspecies interpretation of botulinum neurotoxin type A on muscle-contraction inhibition.Biopharmaceutics & drug disposition · 2024Article
- Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice.Frontiers in pharmacology · 2021Article
- Kinetic-pharmacodynamic model for drugs with non-linear elimination: Parameterisation matters.British journal of clinical pharmacology · 2020Article
- Correction.British journal of clinical pharmacology · 2018Article
- Modelling the dose-response relationship: the fair share of pharmacokinetic and pharmacodynamic information.British journal of clinical pharmacology · 2017Article
Corrections and comments
- Erratum issuedCorrection.2018
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThe aim of this paper is to investigate the role of drug concentration samplings in the modelling of the dose-response relationship.
methodsUsing 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.
resultsK-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.
conclusionsK-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.
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