Evidence map›Paper›PMID 37004650›Full record

ArticleClinical pharmacokinetics2023

External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps.

Mehdi El Hassani, Amélie Marsot

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical pharmacokinetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  10. The Visual Predictive Check and Real-World Data.Clinical pharmacology and therapeutics · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Mehdi El HassaniFaculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada. mehdi.el.hassani@umontreal.ca.ORCID http://orcid.org/0000-0003-4314-5368
Amélie MarsotFaculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predicting drug exposures using population pharmacokinetic models through Bayesian forecasting software can improve individual pharmacokinetic/pharmacodynamic target attainment. However, selecting the most adapted model to be used is challenging due to the lack of guidance on how to design and interpret external evaluation studies. The confusion around the choice of statistical metrics and acceptability criteria emphasises the need for further research to fill this methodological gap as there is an urgent need for the development of standards and guidelines for external evaluation studies. Herein we discuss the scientific challenges faced by pharmacometric researchers and opportunities for future research with a focus on antibiotics.

Indexed as

Anti-Bacterial AgentsSoftwareBayes TheoremForecastingHumansModels, BiologicalAnti-Bacterial Agents

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.