ArticleCPT: pharmacometrics & systems pharmacology2021
Scientific and regulatory evaluation of empirical pharmacometric models: An application of the risk informed credibility assessment framework.
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 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
7 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
- Development of a Physiologically Based Biopharmaceutics Model Report Template: Considerations for Improved Quality in View of Regulatory Submissions.Molecular pharmaceutics · 2025Review
- PBBM Considerations for Base Models, Model Validation, and Application Steps: Workshop Summary Report.Molecular pharmaceutics · 2024Review
- Current practices for QSP model assessment: an IQ consortium survey.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Toward Personalized Salbutamol Therapy: Validating Virtual Patient-Derived Population Pharmacokinetic Model with Real-World Data.Pharmaceutics · 2024Article
- Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.Molecular pharmaceutics · 2024Review
- Scientific and regulatory evaluation of empirical pharmacometric models: An application of the risk informed credibility assessment framework.CPT: pharmacometrics & systems pharmacology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Empirical pharmacometric models are part of practically every regulatory submission for a new drug. The use of the models often exceeds descriptory roles and this change in their context of use increase the requirements on the evidence to support that they are credible. However, when it comes to assessing the trust in a model for a specific application, current tools are skewed to technical aspects and guidance documents often focused on model reporting or the iterative learning loops of model informed drug development (MIDD). There is an unmet need for a holistic tool that provide an end-to-end link from the initial question to the model-informed decision. We suggest the risk-informed credibility framework can be used for this purpose and offers strong support for the pharmacometrics models. We also introduce two tables for explicit description of key attributes of the model evaluation to facilitate and streamline the communication between stakeholders.
Indexed as
Identifiers
What OpenQuestion holds
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.