Evidence map›Paper›PMID 34337764›Full record

ArticleBritish journal of clinical pharmacology2022

Physiologically based pharmacokinetic modelling in pregnancy: Model reproducibility and external validation.

Larissa L Silva, Rebecca M Silvola, David M Haas, Sara K Quinney

Open access · bronzeAbstract read
In one paragraph

Article in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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  3. Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models.International journal of molecular sciences · 2025
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  6. Article
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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

4 authors at 1 institution in 1 country.

Larissa L SilvaDivision of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0002-6165-6893
Rebecca M SilvolaDivision of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0003-0493-0603
David M HaasDivision of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0002-8379-0743
Sara K QuinneyDivision of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0002-6554-0695
Indiana University School of Medicine

Funding

Tumor Microenvironment and Metastasis ProgramP30CA082709 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI David W Clapp · 1999 to 2026
$59.3M
The Indiana University-Ohio State University Maternal and Pediatric Precision in Therapeutics Data, Model, Knowledge, and Research Coordination Center (IU-OSU MPRINT DMKRCC)P30HD106451 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI Lang Li, Sara K Quinney · 2021 to 2026
$24.1M
Indiana University Comprehensive Training in Clinical PharmacologyT32GM008425 · NIGMS · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI Zeruesenay Desta, Michael Thomas Eadon · 1992 to 2026
$7.7M
Pharmacokinetics and modeling of betamethasone therapy in threatened preterm birthR01HD088014 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI HAAS, DAVID M. · 2016 to 2020
$2.6M
Pharmacogenetics of antenatal corticosteroids to improve neonatal outcomesK23HD055305 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI HAAS, DAVID M. · 2008 to 2011
$539k
NCI NIH HHS P30 CA082709NICHD NIH HHS K23 HD055305NICHD NIH HHS P30 HD106451NICHD NIH HHS R01 HD088014NIGMS NIH HHS T32 GM008425
6 · The paper itself

Abstract

aimsPhysiologically based pharmacokinetic (PBPK) models have been previously developed for betamethasone and buprenorphine for pregnant women. The goal of this work was to replicate and reassess these models using data from recently completed studies.

methodsBetamethasone and buprenorphine PBPK models were developed in Simcyp V19 based on prior publications using V17 and V15. Ability to replicate models was verified by comparing predictions in V19 to those previously published. Once replication was verified, models were reassessed by comparing predictions to observed data from additional studies in pregnant women. Model performance was based upon visual inspection of concentration vs. time profiles, and comparison of pharmacokinetic parameters. Models were deemed reproducible if parameter estimates were within 10% of previously reported values. External validations were considered acceptable if the predicted area under the concentration-time curve (AUC) and peak plasma concentration fell within 2-fold of the observed.

resultsThe betamethasone model was successfully replicated using Simcyp V19, with ratios of reported (V17) to reproduced (V19) peak plasma concentration of 0.98-1.04 and AUC of 0.95-1.07. The model-predicted AUC ratios ranged from 0.98-1.79 compared to external data. The previously published buprenorphine PBPK model was not reproducible, as we predicted intravenous clearance of 70% that reported previously (both in Simcyp V15).

conclusionWhile high interstudy variability was observed in the newly available clinical data, the PBPK model sufficiently predicted changes in betamethasone exposure across gestation. Model reproducibility and reassessment with external data are important for the advancement of the discipline. PBPK modelling publications should contain sufficient detail and clarity to enable reproducibility.

Indexed as

BuprenorphineModels, BiologicalArea Under CurveBetamethasoneComputer SimulationFemaleHumansPregnancyReproducibility of ResultsBetamethasoneBuprenorphineobstetricspharmacometricsphysiologically based pharmacokinetic modellingresearch ethics

Identifiers

PMID34337764
PMCPMC10293961
OpenAlexW3193274045

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.