Evidence map›Paper›PMID 39476315›Full record

ArticleClinical pharmacokinetics2024

Understanding Voriconazole Metabolism: A Middle-Out Physiologically-Based Pharmacokinetic Modelling Framework Integrating In Vitro and Clinical Insights.

Ayatallah Saleh, Josefine Schulz, Jan-Frederik Schlender, Linda B S Aulin, Amrei-Pauline Konrad, Franziska Kluwe, Gerd Mikus, Wilhelm Huisinga, Charlotte Kloft, Robin Michelet

Abstract read
In one paragraph

Article in Clinical pharmacokinetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ayatallah SalehDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0000-0002-8161-9854
Josefine SchulzDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0000-0002-0968-5873
Jan-Frederik SchlenderNovartis, Biomedical Research, Basel, Switzerland.
Linda B S AulinDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0000-0003-4840-5704
Amrei-Pauline KonradDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0009-0001-2692-7061
Franziska KluweDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0000-0002-5985-9683
Gerd MikusDepartment of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.ORCID 0000-0003-1783-133X
Wilhelm HuisingaInstitute of Mathematics, University of Potsdam, Potsdam, Germany.ORCID 0000-0002-5249-3914
Charlotte Kloft *Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany. charlotte.kloft@fu-berlin.de.ORCID 0000-0001-9344-8514
Robin Michelet *Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany. robin.michelet@fu-berlin.de.ORCID 0000-0002-5485-607X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveVoriconazole (VRC), a broad-spectrum antifungal drug, exhibits nonlinear pharmacokinetics (PK) due to saturable metabolic processes, autoinhibition and metabolite-mediated inhibition on their own formation. VRC PK is also characterised by high inter- and intraindividual variability, primarily associated with cytochrome P450 (CYP) 2C19 genetic polymorphism. Additionally, recent in vitro findings indicate that VRC main metabolites, voriconazole N-oxide (NO) and hydroxyvoriconazole (OHVRC), inhibit CYP enzymes responsible for VRC metabolism, adding to its PK variability. This variability poses a significant risk of therapeutic failure or adverse events, which are major challenges in VRC therapy. Understanding the underlying processes and sources of these variabilities is essential for safe and effective therapy. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) modelling framework that elucidates the complex metabolism of VRC and the impact of its metabolites, NO and OHVRC, on the PK of the parent, leveraging both in vitro and in vivo clinical data in a middle-out approach.

methodsA coupled parent-metabolite PBPK model for VRC, NO and OHVRC was developed in a stepwise manner using PK-Sim

resultsUsing a combined bottom-up and middle-out approach, incorporating data from multiple clinical studies and existing literature, the model accurately predicted plasma concentration-time profiles across various intravenous dosing regimens in healthy adults, of different CYP2C19 genotype-predicted phenotypes. All (100%) of the predicted area under the concentration-time curve (AUC) and 94% of maximum concentration (C

conclusionThis comprehensive parent-metabolite PBPK model of VRC quantitatively elucidated the complex metabolism of the drug and emphasised the substantial impact of the primary metabolites on VRC PK. The comprehensive approach combining bottom-up and middle-out modelling, thereby accounting for VRC autoinhibition, metabolite-mediated inhibition, and the impact of CYP2C19 genetic polymorphisms, enhances our understanding of VRC PK. Moreover, the model can be pivotal in designing further in vitro experiments, ultimately allowing for extrapolation to paediatric populations, enhance treatment individualisation and improve clinical outcomes.

Indexed as

Antifungal AgentsCytochrome P-450 CYP2C19Models, BiologicalVoriconazoleAdultCytochrome P-450 CYP3AHumansMaleAntifungal AgentsCYP2C19 protein, humanCytochrome P-450 CYP2C19Cytochrome P-450 CYP3AVoriconazole

Identifiers

PMID39476315
PMCPMC11573852

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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.