Evidence map›Paper›PMID 34185905›Full record

ArticleJournal of clinical pharmacology2021

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children.

Ibrahim Ince, André Dallmann, Sebastian Frechen, Katrin Coboeken, Christoph Niederalt, Thomas Wendl, Michael Block, Michaela Meyer, Thomas Eissing, Rolf Burghaus and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of clinical pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
7.0field-weighted citation impact, top 3% of its field
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

15 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Ibrahim IncePharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
André DallmannPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Sebastian FrechenPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Katrin CoboekenPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Christoph NiederaltPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Thomas WendlPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Michael BlockPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Michaela MeyerPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Thomas EissingPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Rolf BurghausPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Jörg LippertPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Stefan WillmannPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Jan-Frederik SchlenderPharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer, AG, Germany.
Bayer (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

Indexed as

Models, BiologicalPharmacokineticsAdolescentChildChild, PreschoolClinical Trials as TopicComputer SimulationHumansInfantInfant, NewbornPediatricsPharmaceutical PreparationsPharmaceutical Preparationsclinical trials (CTR)dose predictionPBPKpediatrics (PED)physiology (PHY)

Identifiers

PMID34185905
PMCPMC8361729
OpenAlexW3173974889

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.