Evidence map›Paper›PMID 42771197›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2026

A mechanism-based model of immune status effects on antibiotic PK/PD targets in bacteremia.

Marinda van de Kreeke, Anh Duc Pham, Michelle Mehciz, Tamara Jordens, Marnix G Uyterlinde, Rob C van Wijk, Linda B S Aulin, Catherijne A J Knibbe, Elke H J Krekels, Laura B Zwep and 1 more

Abstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

11 authors.

Marinda van de Kreeke *Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID http://orcid.org/0000-0001-9904-131X
Anh Duc Pham *Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-0279-1761
Michelle MehcizDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0009-0007-8060-2966
Tamara JordensDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0009-0000-5451-7951
Marnix G UyterlindeDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0009-0009-6766-5174
Rob C van WijkDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID http://orcid.org/0000-0001-7247-1360
Linda B S AulinDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0000-0003-4840-5704
Catherijne A J KnibbeDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-9893-4415
Elke H J KrekelsDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-6006-1567
Laura B ZwepDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-6817-2859
J G Coen van HasseltDivision of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, The Netherlands. coen.vanhasselt@lacdr.leidenuniv.nl.ORCID http://orcid.org/0000-0002-1664-7314

Funding

European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant 861323
6 · The paper itself

Abstract

A key determinant of antibiotic dose selection is the pharmacokinetic/pharmacodynamic (PK/PD) target, typically determined using dose fractionation studies in preclinical infection models. However, such studies often do not consider the host immune response, despite its important role in bacterial infection. We therefore aimed to systematically characterize the potential contributions of the innate immune response on antibiotic PK/PD targets using a novel mathematical mechanism-based model, incorporating interactions between neutrophils, monocytes and bacterial pathogens. We parametrized the model using data from multiple in vitro host-pathogen interaction studies and calibrated using data from previous in vivo infection models. Key parameters included phagocytosis and digestion rates of neutrophils and monocytes, driven by immune cell concentrations and finite ingestion capacities. To describe data from immune competent rodent infection models, maximum phagocytosis rates required a 77% reduction relative to in vitro estimates for both cell types. The calibrated host-pathogen interaction model was then integrated with a pharmacodynamic model accounting for pathogen-drug interactions for four antibiotic modalities. We performed in silico dose fractionation studies for bacteremia thereby evaluating the impact of different types and magnitudes of immune deficiencies, e.g., neutropenia, monocytopenia, on PK/PD targets in humans. The combination of severe neutropenia and monocytopenia required up to 2.2-fold increase in target AUC/MIC for concentration-dependent antibiotics, and up to a 58% increase in T>MIC for time-dependent antibiotics, compared with immune competent individuals. In conclusion, this study provides general insights into the impact of neutrophil and monocyte suppression on PK/PD targets and associated dosage adjustments in case of immune suppression.

Indexed as

Anti-Bacterial AgentsBacteremiaModels, BiologicalAnimalsComputer SimulationDose-Response Relationship, DrugHost-Pathogen InteractionsHumansImmunity, InnateMonocytesNeutrophilsPhagocytosisAnti-Bacterial AgentsAntibiotic dosingMathematical modelingMonocytesNeutrophils

Identifiers

PMID42771197
PMCPMC13597578

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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.