Pharmacokinetic Modeling of Voriconazole To Develop an Alternative Dosing Regimen in Children

Gastine, Silke; Lehrnbecher, Thomas; Müller, Carsten; Farowski, Fedja; Bader, Peter; Ullmann-Moskovits, Judith; Cornely, Oliver A.; Groll, Andreas H.; Hempel, Georg

doi:10.1128/aac.01194-17

Cited by 32 publications

(59 citation statements)

References 45 publications

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“…medication and costs . However, in clinical practice, observed or estimated bioavailability was reported as substantially lower (83% in adult patients with haematological malignancies and solid organ transplantation; 63% in adults with haematological malignancies and other diseases; and 59.4% in children). In our models, we found that the bioavailability of voriconazole in our patients was approximately 50%.…”

Section: Discussionmentioning

confidence: 98%

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A pharmacokinetic model for voriconazole in a highly diversified population of children and adolescents with cancer

Carlesse

Araújo

Marques

et al. 2019

Mycoses

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Summary Background The wide pharmacokinetic variability of voriconazole leads to uncertainty regarding adequate exposure. Objectives To create a pharmacokinetic model that could help to explain the variability. Methods Retrospective review of paediatric patients with cancer. Models were built using Pmetrics. Results We analysed 158 trough measurements in 55 patients; in 41.8%, the serum levels were between 1 and 6 mg/L on initial measurement. After the measurements, dosage adjustments were made in 42 (76.3%) patients, and the percentage of adequate levels rose to 54.5%. Fourteen deaths (25.4%) were attributed to invasive fungal diseases. The mean serum levels were higher in deceased patients (mean ± SD: 3.1 ± 3.2 mg/L vs 2.5 ± 3.6 mg/L in survivors; P = 0.018), but the median doses per kg were higher in survivors. Drug exposure was also higher in deceased patients (mean ± SD of AUC: 19.2 ± 8.1 vs 9.5 ± 19.1 in survivors; P = 0.005). No correlation was found between serum concentrations <1 mg/L and death attributable to fungal disease. Bioavailability was estimated in 50%. The maximum velocity of clearance was reduced in deceased patients. Conclusions Extremely ill patients can be poor metabolizers of voriconazole. Therapeutic monitoring promotes only a limited improvement in drug management.

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Section: Discussionmentioning

confidence: 98%

“…20 and 59.4% in children21 ). In our models, we found that the bioavailability of voriconazole in our patients was approximately 50%.…”

mentioning

confidence: 95%

A pharmacokinetic model for voriconazole in a highly diversified population of children and adolescents with cancer

Carlesse

Araújo

Marques

et al. 2019

Mycoses

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“…The PK of azoles, such as voriconazole, is complex. Many PK models and simulations have been performed to determine variability, dosing schedule, and to study the drug interactions …”

Section: Admementioning

confidence: 98%

“…Gastine et al. also used PopPK and simulations to evaluate target voriconazole dose and interval using a nonlinear model with allometric scaling …”

Section: Admementioning

confidence: 99%

“…Many PK models and simulations have been performed to determine variability, dosing schedule, and to study the drug interactions. [64][65][66][67][68][69] Example 8: Drug interaction and genetic polymorphism: Etoposide is a substrate of P-gp, CYP3A4, and CYP3A5. Glucocorticoids, such as dexamethasone and prednisolone, can inhibit or induce CYP3A and P-gp.…”

Section: Metabolismmentioning

confidence: 99%

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Pharmacokinetics and population pharmacokinetics in pediatric oncology

Sassen

Zwaan

Sluis

et al. 2019

Pediatric Blood & Cancer

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Pharmacokinetic research has become increasingly important in pediatric oncology as it can have direct clinical implications and is a crucial component in individualized medicine. Population pharmacokinetics has become a popular method especially in children, due to the potential for sparse sampling, flexible sampling times, computing of heterogeneous data, and identification of variability sources. However, population pharmacokinetic reports can be complex and difficult to interpret. The aim of this article is to provide a basic explanation of population pharmacokinetics, using clinical examples from the field of pediatric oncology, to facilitate the translation of pharmacokinetic research into the daily clinic.

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Predictive Value of C‐Reactive Protein and Albumin for Temporal Within‐Individual Pharmacokinetic Variability of Voriconazole in Pediatric Patients Undergoing Hematopoietic Cell Transplantation

Takahashi

Jaber

Smith

et al. 2022

The Journal of Clinical Pharma

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Voriconazole is a widely used antifungal agent in immunocompromised patients, but its utility is limited by its variable exposure and narrow therapeutic index. Population pharmacokinetic (PK) models have been used to characterize voriconazole PK and derive individualized dosing regimens. However, determinants of temporal within-patient variability of voriconazole PK were not well established. We aimed to characterize temporal variability of voriconazole PK within individuals and identify predictive clinical factors. This study was conducted as a part of a single-institution, phase I study of intravenous voriconazole in children undergoing hematopoietic cell transplantation (NCT02227797). We analyzed voriconazole PK study data collected at week 1 and again at week 2 after the start of voriconazole therapy in 59 pediatric patients undergoing HCT (age <21 years). Population PK analysis using nonlinear mixed effect modeling was performed to analyze temporal within-individual variability of voriconazole PK by incorporating a between-occasion variability term in the model. A 2-compartment linear elimination model incorporating body weight and cytochrome P450 2C19 phenotype described the data. The ratio of individual voriconazole clearance between weeks 1 and 2 ranged from 0.11 to 3.3 (−9.1 to +3.3-fold change). Incorporation of covariate effects by serum C-reactive protein and albumin levels decreased between-occasion variability of clearance as compared to the model without them (coefficient of variation, 41.2% and 59.5%, respectively) and improved the model fit (P < .05). As significant covariates on voriconazole PK, C-reactive protein and albumin concentrations may potentially serve as useful biomarkers as part of therapeutic drug monitoring.

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Pharmacokinetic Modeling of Voriconazole To Develop an Alternative Dosing Regimen in Children

Cited by 32 publications

References 45 publications

A pharmacokinetic model for voriconazole in a highly diversified population of children and adolescents with cancer

A pharmacokinetic model for voriconazole in a highly diversified population of children and adolescents with cancer

Pharmacokinetics and population pharmacokinetics in pediatric oncology

Predictive Value of C‐Reactive Protein and Albumin for Temporal Within‐Individual Pharmacokinetic Variability of Voriconazole in Pediatric Patients Undergoing Hematopoietic Cell Transplantation

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