Voriconazole exposure is influenced by inflammation: A population pharmacokinetic model

D Abraham van den Born; Anne-Grete Märtson; Anette Veringa; Nieko C Punt; Tjip S van der Werf; Jan-Willem C Alffenaar; Marieke G G Sturkenboom; Daan J Touw

doi:10.1016/j.ijantimicag.2023.106750

Voriconazole exposure is influenced by inflammation: A population pharmacokinetic model

Int J Antimicrob Agents. 2023 Apr;61(4):106750. doi: 10.1016/j.ijantimicag.2023.106750. Epub 2023 Feb 8.

Authors

D Abraham van den Born¹, Anne-Grete Märtson¹, Anette Veringa¹, Nieko C Punt², Tjip S van der Werf³, Jan-Willem C Alffenaar⁴, Marieke G G Sturkenboom¹, Daan J Touw⁵

Affiliations

¹ University of Groningen, University Medical Centre Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands.
² University of Groningen, University Medical Centre Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands; Medimatics, Maastricht, The Netherlands.
³ Department of Internal Medicine and Department of Pulmonary Diseases and Tuberculosis Groningen, University of Groningen, University Medical Centre Groningen, The Netherlands.
⁴ University of Groningen, University Medical Centre Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands; Sydney Institute for Infectious Diseases, University of Sydney, Sydney, Australia; Faculty of Medicine and Health, Sydney Pharmacy School, University of Sydney, Sydney, Australia; Westmead Hospital, Sydney, Australia.
⁵ University of Groningen, University Medical Centre Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands; Department of Pharmaceutical Analysis, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands. Electronic address: d.j.touw@umcg.nl.

PMID: 36758777
DOI: 10.1016/j.ijantimicag.2023.106750

Abstract

Background: Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM.

Objectives: To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care.

Patients and methods: Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots.

Results: In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (V_max). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean V_max was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates.

Conclusions: This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately.

Keywords: CRP; Inflammation; Pharmacokinetic modelling; Voriconazole.

MeSH terms

Antifungal Agents* / pharmacokinetics
Antifungal Agents* / therapeutic use
C-Reactive Protein
Humans
Inflammation / drug therapy
Invasive Fungal Infections* / drug therapy
Voriconazole / pharmacokinetics
Voriconazole / therapeutic use

Substances

Voriconazole
Antifungal Agents
C-Reactive Protein