Abstract
Background: Voriconazole pharmacokinetics (PK) are known to be affected by genetic polymorphisms of drug-metabolizing enzymes such as CYP2C19; however, such information is limited for the pediatric population. The primary aim of this study is to establish a voriconazole PK model incorporating CYP2C19 phenotypes in Japanese children with malignancy or inborn errors of immunity. Methods: CYP2C19 genotypes were assessed by whole-genome genotyping and defined as follows: *17/*17: ultrarapid metabolizer (URM), *1/*17: rapid metabolizer (RM), *1/*1:normal metabolizer (NM), *1/*2, *1/*3, *2/*17:intermediate metabolizer (IM), and *2/*2, *2/*3, *3/*3: poor metabolizer (PM). Population PK analysis was performed. The voriconazole serum concentration profile was described by a two-compartment model with first-order absorption, mixed linear and nonlinear (Michaelis-Menten) elimination. Results: Voriconazole concentration data were available from 60 patients with a median age of 5.3 years. The phenotypes predicted from CYP2C19 genotypes were RM in 1 (2 %), NM in 21 (35 %) patients, IM in 27 (45 %) patients, and PM in 11 (18 %) patients. Underlying diseases included 38 (63%) patients with hematological malignancy and 18 (30 %) patients with inborn errors of immunity. Among the CYP2C19 phenotypes, PM was predicted to show complete inhibition (the degree of Vmax inhibition [Vmax, inh] = 100 %; Vmax = 0). The estimated parameters of Vmax,inh were +0.8 higher in patients with gamma-glutamyl transpeptidase (γ-GTP) Grade 2 or higher and +2.7 higher when C-reactive protein (CRP) levels were 2.0 mg/dL or higher. Conclusion: CYP2C19 genetic polymorphisms, γ-GTP, and CRP affect Vmax,inh of voriconazole in children with malignancy or inborn errors of immunity.
| Original language | English |
|---|---|
| Pages (from-to) | 1280-1288 |
| Number of pages | 9 |
| Journal | Journal of Infection and Chemotherapy |
| Volume | 30 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 12-2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Microbiology (medical)
- Pharmacology (medical)
- Infectious Diseases
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