Evidence map›Paper›PMID 42834847›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

Application of an Open-Source Modular Framework for Pharmacokinetic, Pharmacodynamic, and Safety Simulations to Anti-Tuberculosis Drugs.

Marco Siccardi, Nina Nauwelaerts, Raphaëlle Lesage, Diane Lefaudeux, Vanessa Baier, Venetia Karamitsou, Cleo Demeester, Miao-Chan Huang, Alexander Kulesza, Stephan Schaller

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 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.

Marco SiccardiESQlabs GmbH, Saterland, Germany.
Nina NauwelaertsESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0001-5301-6813
Raphaëlle LesageESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0003-1041-2407
Diane LefaudeuxESQlabs GmbH, Saterland, Germany.
Vanessa BaierESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0002-7001-6804
Venetia KaramitsouESQlabs GmbH, Saterland, Germany.
Cleo DemeesterESQlabs GmbH, Saterland, Germany.
Miao-Chan HuangESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0002-8645-039X
Alexander KuleszaESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0002-8812-8548
Stephan SchallerESQlabs GmbH, Saterland, Germany.ORCID https://orcid.org/0000-0003-1046-7651

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) treatment requires long-term multidrug regimens where dosing, efficacy, and safety optimization remain challenging. This tutorial establishes an integrated, open-source, modular framework connecting high-throughput PBPK (HT-PBPK) simulations, mechanistic PBPK models, pharmacodynamic endpoints, and safety predictions for anti-TB drugs. Using the Open Systems Pharmacology Suite and ESQhtpbpk (R package), physicochemical parameters were obtained from literature, with QSAR-predicted values supplementing missing experimental data to generate generic PBPK models. Mechanistic models were parameterized for moxidectin, isoniazid, moxifloxacin, bedaquiline, and rifampicin. A quantitative TB disease model of host-pathogen dynamics and PK-PD interactions was integrated to assess efficacy. A cardiac electrophysiology model incorporating ion channel inhibition data was coupled with PBPK predictions for moxifloxacin and bedaquiline. The HT-PBPK framework automated virtual studies across compounds and dosing regimens. Mechanistic models reproduced systemic and local disposition within two-fold of the observed data. The TB disease model predicted treatment response across exposure scenarios. The cardiac module captured the dose-QTc relationship for moxifloxacin and identified metabolite-driven QTc prolongation with bedaquiline, consistent with clinical observations. This open-source, modular framework spans compound screening, mechanistic PK, efficacy, and cardiotoxicity, providing a reproducible tool to support TB drug development, guide dose selection, and inform regulatory decisions.

Indexed as

Antitubercular AgentsModels, BiologicalTuberculosisComputer SimulationDiarylquinolinesHumansMoxifloxacinQuantitative Structure-Activity RelationshipAntitubercular AgentsbedaquilineDiarylquinolinesMoxifloxacin

Identifiers

PMID42834847
PMCPMC13639711

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.