4CPS-184 Determination of voriconazole metaboliser phenotype in the absence of genetic testing

<h3>Background and Importance</h3> Pharmacokinetic monitoring of voriconazole is useful for optimising its treatment due to the significant inter- and intra-individual variability it exhibits. It is metabolised mainly by CYP2C19, an enzyme with a considerable genetic polymorphism leading to variability in metabolism among the population. Its genotyping in many cases is expensive and inaccessible, so it would be interesting to develop alternative methods to determine the patient’s metaboliser phenotype. <h3>Aim and Objectives</h3> To determine the metaboliser phenotype according to plasma concentrations (Cp) of voriconazole using a population pharmacokinetic model. <h3>Material and Methods</h3> Observational, descriptive, retrospective study of patients treated with intravenous and oral voriconazole in a second-level hospital from January 2016 to June 2024. Clinical data were collected through the electronic medical record: medical history number, weight, posology, route and rate of administration, Cp and concomitant treatments with prednisone, methylprednisolone, dexamethasone, carbamazepine, phenytoin, ritonavir and St. John’s wort. We applied the Dolton pharmacokinetic model to each patient using the NONMEM program to estimate Cp of voriconazole based on two assumptions: CYP2C19=1 for patients with one or more loss-of-function alleles (poor metaboliser). CYP2C19=0 for patients not meeting the previous criteria (normal/rapid metaboliser). We obtained: observed Cp (Cpo), predicted Cp for CYP2C19=1 (CppCYP2C19=1) and predicted Cp for CYP2C19=0 (CppCYP2C19=0). We deduce metaboliser phenotype according to: Cpo value closest to CppCYP2C19=1 → Poor metaboliser. Cpo value closest to CppCYP2C19=0 → Normal/rapid metaboliser. Values very different or very similar to each other → Not possible to determine the metaboliser phenotype. <h3>Results</h3> A total of 85 Cp of voriconazole were analysed from 47 patients. Regarding metaboliser phenotype, 63.9% (30 patients) were normal/rapid metabolisers, 6.4% (three patients) were poor metabolisers and 29.7% (14 patients) could not be determined. <h3>Conclusion and Relevance</h3> The metaboliser phenotype could be estimated in the majority of patients (70.3%). Therefore, the application of the Dolton pharmacokinetic model to the Cp of voriconazole obtained could be a useful tool, in the absence of genetic studies, to determine the metaboliser phenotype of our patient. <h3>References and/or Acknowledgements</h3> <h3>Conflict of Interest</h3> No conflict of interest

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Published
2025-03-01
DOI
https://doi.org/10.1136/ejhpharm-2025-eahp.247
Primary Topic
Antifungal resistance and susceptibility
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article
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article

4CPS-184 Determination of voriconazole metaboliser phenotype in the absence of genetic testing

Maria-Renee Ortiz, P Pastor Vara, Mariano Giménez, H Gavilan Gigosos et al.
Antifungal resistance and susceptibility
article

4CPS-184 Determination of voriconazole metaboliser phenotype in the absence of genetic testing

Maria-Renee Ortiz, P Pastor Vara, Mariano Giménez, H Gavilan Gigosos, Sara Corrales Krohnert, César A. Ramírez, Abraham Garcia, Antonio Millán, I Orozco Cifuentes
article en

Abstract

<h3>Background and Importance</h3> Pharmacokinetic monitoring of voriconazole is useful for optimising its treatment due to the significant inter- and intra-individual variability it exhibits. It is metabolised mainly by CYP2C19, an enzyme with a considerable genetic polymorphism leading to variability in metabolism among the population. Its genotyping in many cases is expensive and inaccessible, so it would be interesting to develop alternative methods to determine the patient’s metaboliser phenotype. <h3>Aim and Objectives</h3> To determine the metaboliser phenotype according to plasma concentrations (Cp) of voriconazole using a population pharmacokinetic model. <h3>Material and Methods</h3> Observational, descriptive, retrospective study of patients treated with intravenous and oral voriconazole in a second-level hospital from January 2016 to June 2024. Clinical data were collected through the electronic medical record: medical history number, weight, posology, route and rate of administration, Cp and concomitant treatments with prednisone, methylprednisolone, dexamethasone, carbamazepine, phenytoin, ritonavir and St. John’s wort. We applied the Dolton pharmacokinetic model to each patient using the NONMEM program to estimate Cp of voriconazole based on two assumptions: CYP2C19=1 for patients with one or more loss-of-function alleles (poor metaboliser). CYP2C19=0 for patients not meeting the previous criteria (normal/rapid metaboliser). We obtained: observed Cp (Cpo), predicted Cp for CYP2C19=1 (CppCYP2C19=1) and predicted Cp for CYP2C19=0 (CppCYP2C19=0). We deduce metaboliser phenotype according to: Cpo value closest to CppCYP2C19=1 → Poor metaboliser. Cpo value closest to CppCYP2C19=0 → Normal/rapid metaboliser. Values very different or very similar to each other → Not possible to determine the metaboliser phenotype. <h3>Results</h3> A total of 85 Cp of voriconazole were analysed from 47 patients. Regarding metaboliser phenotype, 63.9% (30 patients) were normal/rapid metabolisers, 6.4% (three patients) were poor metabolisers and 29.7% (14 patients) could not be determined. <h3>Conclusion and Relevance</h3> The metaboliser phenotype could be estimated in the majority of patients (70.3%). Therefore, the application of the Dolton pharmacokinetic model to the Cp of voriconazole obtained could be a useful tool, in the absence of genetic studies, to determine the metaboliser phenotype of our patient. <h3>References and/or Acknowledgements</h3> <h3>Conflict of Interest</h3> No conflict of interest

Hospital Clínico San Carlos (ES), Hospital Universitario de Guadalajara (ES), Hospital Universitario Severo Ochoa (ES)
Zero hunger
Openalex Percentile: Top 93%
Antifungal resistance and susceptibility
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