ArticleJournal of pharmacokinetics and pharmacodynamics2017
Deterministic identifiability of population pharmacokinetic and pharmacokinetic-pharmacodynamic models.
Article in Journal of pharmacokinetics and pharmacodynamics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Structural identifiability for mathematical pharmacology: models of myelosuppression.Journal of pharmacokinetics and pharmacodynamics · 2018Pooled it
- The 95% CDIRAs, a Credible Interval Based Method to Capture Uncertainty in Population Modeling: Pharmacokinetics Versus Sum of Exponentials Case Study.CPT: pharmacometrics & systems pharmacology · 2026Article
- A Pharmacometric Workflow for Resolving Model Instability in Model Use-Reuse Settings.CPT: pharmacometrics & systems pharmacology · 2025Article
- Mechanistic inference of the metabolic rates underlyingJournal of pharmacokinetics and pharmacodynamics · 2023Article
- Model-Informed Optimization of a Pediatric Clinical Pharmacokinetic Trial of a New Spironolactone Liquid Formulation.Pharmaceutics · 2021Article
- Saddle-Reset for Robust Parameter Estimation and Identifiability Analysis of Nonlinear Mixed Effects Models.The AAPS journal · 2020Article
- Automated Scale Reduction of Nonlinear QSP Models With an Illustrative Application to a Bone Biology System.CPT: pharmacometrics & systems pharmacology · 2018Article
- Evaluation of performance of distributed delay model for chemotherapy-induced myelosuppression.Journal of pharmacokinetics and pharmacodynamics · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifiability is an important component of pharmacokinetic-pharmacodynamic (PKPD) model development. Structural identifiability is concerned with the uniqueness of the model parameters for a set of perfect input-output data and deterministic identifiability with the precision of parameter estimation given imperfect input-output data. We introduce two subcategories of deterministic identifiability, external and internal, and consider factors that distinguish between these forms. We define external deterministic identifiability as a function of externally controllable variables, i.e., the design, and internal deterministic identifiability as a function of the model and its parameter values. The concepts are explored using three common PK and PKPD models, and verified for their precision for the selected set of parameter values under optimal design.
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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.