ArticlePharmaceutical research2011
A new exact test for the evaluation of population pharmacokinetic and/or pharmacodynamic models using random projections.
Article in Pharmaceutical research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Optimization of Cefotaxime Treatment in Intensive Care Patients: Impact of Inter- and Intra-patient Variability on Pharmacokinetics and Target Attainment.Clinical pharmacokinetics · 2026Article
- The CetuxIMAX study: a population pharmacokinetic approach to modelling the pharmacokinetics and pharmacodynamics relationships of Cetuximab in patients with head and neck cancer.Cancer chemotherapy and pharmacology · 2026Article
- Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics.CPT: pharmacometrics & systems pharmacology · 2017Article
- Enhanced Method for Diagnosing Pharmacometric Models: Random Sampling from Conditional Distributions.Pharmaceutical research · 2016Article
- Extension of NPDE for evaluation of nonlinear mixed effect models in presence of data below the quantification limit with applications to HIV dynamic model.Journal of pharmacokinetics and pharmacodynamics · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
purposeWithin-subject dependency of observations has a strong impact on the evaluation of population pharmacokinetic (PK) and/or pharmacodynamic (PD) models. To our knowledge, none of the current model evaluation tools correctly address this issue. We present a new method with a global test and easy diagnostic plot which relies on the use of a random projection technique that allows the analysis of dependent data.
methodsFor each subject, the vector of standardised residuals is calculated and projected onto many random directions drawn uniformly from the unit sphere. Our test compares the empirical distribution of projections with their distribution under the model. Simulation studies assess the level of the test and compare its performance with common metrics including normalised prediction distribution errors and different types of weighted residuals. An application to real data is performed.
resultsIn contrast to other evaluated methods, our test shows adequate level for all models and designs investigated, which confirms its good theoretical properties. The weakness of other methods is demonstrated and discussed.
conclusionsThis new test appears promising and could be used in combination with other tools to drive model evaluation in population PK/PD analyses.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.