Evidence map›Paper›PMID 37765316›Full record

ArticlePharmaceutics2023

Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling.

Pieter-Jan De Sutter, Phebe Rossignol, Lien Breëns, Elke Gasthuys, An Vermeulen

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

5 citing papers in PubMed, 8 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

5 authors at 1 institution in 1 country.

Pieter-Jan De SutterDepartment of Bioanalysis, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-3858-8017
Phebe RossignolDepartment of Bioanalysis, Ghent University, 9000 Ghent, Belgium.
Lien BreënsDepartment of Bioanalysis, Ghent University, 9000 Ghent, Belgium.
Elke GasthuysDepartment of Bioanalysis, Ghent University, 9000 Ghent, Belgium.
An VermeulenDepartment of Bioanalysis, Ghent University, 9000 Ghent, Belgium.
Ghent University · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The volume of distribution at steady state (Vss) in neonates is still often estimated through isometric scaling from adult values, disregarding developmental changes beyond body weight. This study aimed to compare the accuracy of two physiologically based pharmacokinetic (PBPK) Vss prediction methods in neonates (Poulin & Theil with Berezhkovskiy correction (P&T+) and Rodgers & Rowland (R&R)) with isometrical scaling. PBPK models were developed for 24 drugs using in-vitro and in-silico data. Simulations were done in Simcyp (V22) using predefined populations. Clinical data from 86 studies in neonates (including preterms) were used for comparison, and accuracy was assessed using (absolute) average fold errors ((A)AFEs). Isometric scaling resulted in underestimated Vss values in neonates (AFE: 0.61), and both PBPK methods reduced the magnitude of underprediction (AFE: 0.82-0.83). The P&T+ method demonstrated superior overall accuracy compared to isometric scaling (AAFE of 1.68 and 1.77, respectively), while the R&R method exhibited lower overall accuracy (AAFE: 2.03). Drug characteristics (LogP and ionization type) and inclusion of preterm neonates did not significantly impact the magnitude of error associated with isometric scaling or PBPK modeling. These results highlight both the limitations and the applicability of PBPK methods for the prediction of Vss in the absence of clinical data.

Indexed as

allometric scalingdevelopmental pharmacologyneonatespharmacokineticsphysiologically based pharmacokinetics (PBPK)volume of distribution

Identifiers

PMID37765316
PMCPMC10536587
OpenAlexW4386895096

What OpenQuestion holds

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Registered trials

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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.