ArticleCPT: pharmacometrics & systems pharmacology2021
Tutorial for $DESIGN in NONMEM: Clinical trial evaluation and optimization.
Article in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- 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
- Accelerating Pediatric Oncology Drug Development: Advances in Clinical Pharmacology, Trial Design, Non-Clinical Evidence, and Regulatory Science.Journal of clinical pharmacology · 2026Review
- Advancing Precision Dosing of 5-FU: Population PK Model Development, Limited Sampling Strategies, and Fit-for-Use Application.Clinical pharmacokinetics · 2026Article
- Optimizing Clinical Study Designs for CAR-T Cell Therapy: Development of an Efficient Sampling Strategy Through Optimal Experimental Design.CPT: pharmacometrics & systems pharmacology · 2026Article
- Design Optimization for Developing Population Pharmacokinetic Models in Critically Ill Children: Application to Teicoplanin, Piperacillin and Meropenem.Clinical pharmacokinetics · 2026Article
- A Pharmacometric Workflow for Resolving Model Instability in Model Use-Reuse Settings.CPT: pharmacometrics & systems pharmacology · 2025Article
- Comparing randomized trial designs to estimate treatment effect in rare diseases with longitudinal models: a simulation study showcased by Autosomal Recessive Cerebellar Ataxias using the SARA score.BMC medical research methodology · 2025Article
- Interoccasion variability in population pharmacokinetic models: identifiability, influence, interdependencies and derived study design recommendations.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice.British journal of clinical pharmacology · 2025Review
- Empagliflozin in paediatric heart failure: model-based optimisation of a pharmacokinetic bridging study.Frontiers in medicine · 2025Article
- Model-informed drug discovery and development approaches to inform clinical trial design and regulatory decisions: A primer for the MENA region.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024Review
- Navigating the landscape of parameter identifiability methods: A workflow recommendation for model development.CPT: pharmacometrics & systems pharmacology · 2024Article
- Two new user-friendly methods to assess pharmacometric parameter identifiability on categorical and continuous scales.CPT: pharmacometrics & systems pharmacology · 2024Article
- Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases.Journal of pharmacokinetics and pharmacodynamics · 2023Review
- Tutorial for $DESIGN in NONMEM: Clinical trial evaluation and optimization.CPT: pharmacometrics & systems pharmacology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This NONMEM tutorial shows how to evaluate and optimize clinical trial designs, using algorithms developed in design software, such as PopED and PFIM 4.0. Parameter precision and model parameter estimability is obtained by assessing the Fisher Information Matrix (FIM), providing expected model parameter uncertainty. Model parameter identifiability may be uncovered by very large standard errors or inability to invert an FIM. Because evaluation of FIM is more efficient than clinical trial simulation, more designs can be investigated, and the design of a clinical trial can be optimized. This tutorial provides simple and complex pharmacokinetic/pharmacodynamic examples on obtaining optimal sample times, doses, or best division of subjects among design groups. Robust design techniques accounting for likely variability among subjects are also shown. A design evaluator and optimizer within NONMEM allows any control stream first developed for trial design exploration to be subsequently used for estimation of parameters of simulated or clinical data, without transferring the model to another software. Conversely, a model developed in NONMEM could be used for design optimization. In addition, the $DESIGN feature can be used on any model file and dataset combination to retrospectively evaluate the model parameter uncertainty one would expect given that the model generated the data, particularly if outliers of the actual data prevent a reasonable assessment of the variance-covariance. The NONMEM trial design feature is suitable for standard continuous data, whereas more elaborate trial designs or with noncontinuous data-types can still be accomplished in optimal design dedicated software like PopED and PFIM.
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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.