Evidence map›Paper›PMID 42897405›Full record

ArticleThe AAPS journal2026

Predictive Performance of pyDarwin-Selected Versus Expert-Developed Paediatric Tobramycin Population Pharmacokinetic Models for Model-Informed Precision Dosing.

Jinglei Wang, Kiera Harwood, Wenyu Yang, Alice Lei, Tony Lai, Keith Nieforth, Stephen Duffull, Mark Sale, Amanda Gwee, Xiao Zhu

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Jinglei Wang *Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmaceutical Sciences, Fudan University, Shanghai, 201203, China.ORCID http://orcid.org/0009-0002-7803-8765
Kiera Harwood *Department of Paediatrics, The University of Melbourne, Melbourne, Australia.ORCID http://orcid.org/0009-0006-9507-2497
Wenyu Yang *Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmaceutical Sciences, Fudan University, Shanghai, 201203, China.ORCID http://orcid.org/0000-0002-9057-4520
Alice LeiAntimicrobial Group, Murdoch Children's Research Institute, Melbourne, Australia.ORCID http://orcid.org/0009-0004-2404-4830
Tony LaiPharmacy Department, The Children's Hospital at Westmead, Sydney, Australia.ORCID http://orcid.org/0000-0001-9761-0072
Keith NieforthCertara, Radnor, Pennsylvania, USA.ORCID http://orcid.org/0009-0005-2170-4853
Stephen DuffullCertara, Radnor, Pennsylvania, USA.ORCID http://orcid.org/0000-0002-6545-9408
Mark SaleCertara, Radnor, Pennsylvania, USA.ORCID http://orcid.org/0000-0002-6239-2359
Amanda Gwee *Department of Paediatrics, The University of Melbourne, Melbourne, Australia.ORCID http://orcid.org/0000-0003-4016-8986
Xiao Zhu *Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmaceutical Sciences, Fudan University, Shanghai, 201203, China. xiaozhu@fudan.edu.cn.ORCID http://orcid.org/0000-0003-3295-619X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PyDarwin is an open-source Python package integrating machine learning with NONMEM for automated model selection; however, its utility in model-informed precision dosing (MIPD) remains unvalidated. This study aims to evaluate pyDarwin for population pharmacokinetics (PopPK) model development in MIPD compared with expert-developed models, using paediatric tobramycin as a representative case. The model-building dataset included 450 plasma concentrations from 63 children with cystic fibrosis (CF). One group manually developed a model using stepwise covariate selection, while another applied pyDarwin within a predefined 27-dimensional model space, using a fitness function that incorporated a penalty based on 24-h area under the curve (AUC

Indexed as

Anti-Bacterial AgentsModels, BiologicalTobramycinAdolescentArea Under CurveBayes TheoremChildChild, PreschoolCystic FibrosisDrug MonitoringFemaleHumansInfantMalePrecision MedicinePredictive Learning ModelsAnti-Bacterial AgentsTobramycinmodel-Informed Precision Dosing (MIPD)paediatricspopulation Pharmacokinetics (PopPK)pyDarwintobramycin

Identifiers

PMID42897405

What OpenQuestion holds

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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.