Application of a Physiologically Based Pharmacokinetic Model to Characterize Time-dependent Metabolism of Voriconazole in Children and Support Dose Optimization

Pharmacogenomics and adverse effects of anti-infective drugs in children

Children, as a special group, have their own peculiarities in terms of individualized medication use compared to adults. Adverse drug reactions have been an important issue that needs to be addressed in the hope of safe medication use in children, and the occurrence of adverse drug reactions is partly due to genetic factors. Anti-infective drugs are widely used in children, and they have always been an important cause of the occurrence of adverse reactions in children. Pharmacogenomic technologies are becoming increasingly sophisticated, and there are now many guidelines describing the pharmacogenomics of anti-infective drugs. However, data from paediatric-based studies are scarce. This review provides a systematic review of the pharmacogenomics of anti-infective drugs recommended for gene-guided use in CPIC guidelines by exploring the relationship between pharmacogenetic frequencies and the incidence of adverse reactions, which will help inform future studies of individualized medication use in children.

Physiologically-Based Pharmacokinetic Modeling for Drug Dosing in Pediatric Patients: A Tutorial for a Pragmatic Approach in Clinical Care

It is well-accepted that off-label drug dosing recommendations for pediatric patients should be based on the best available evidence. However, the available traditional evidence is often low. To bridge this gap, physiologically-based pharmacokinetic (PBPK) modeling is a scientifically well-founded tool that can be used to enable model-informed dosing (MID) recommendations in children in clinical practice. In this tutorial, we provide a pragmatic, PBPK-based pediatric modeling workflow. For this approach to be successfully implemented in pediatric clinical practice, a thorough understanding of the model assumptions and limitations is required. More importantly, careful evaluation of an MID approach within the context of overall benefits and the potential risks is crucial. The tutorial is aimed to help modelers, researchers, and clinicians, to effectively use PBPK simulations to support pediatric drug dosing.

Voriconazole plasma concentrations and dosing in paediatric patients below 24 months of age

Voriconazole (VCZ) is an important first-line option for management of invasive fungal diseases and approved in paediatric patients ≥24 months at distinct dosing schedules that consider different developmental stages. Information on dosing and exposures in children <24 months of age is scarce. Here we report our experience in children <24 months who received VCZ due to the lack of alternative treatment options. This retrospective analysis includes 50 distinct treatment episodes in 17 immunocompromised children aged between 3 and <24 months, who received VCZ between 2004 and 2022 as prophylaxis (14 patients; 47 episodes) or as empirical treatment (3 patients; 3 episodes) by mouth (46 episodes) or intravenously (4 episodes) based on contraindications, intolerance or lack of alternative options. Trough concentrations were measured as clinically indicated, and tolerability was assessed based on hepatic function parameters and discontinuations due to adverse events (AEs). VCZ was administered for a median duration of 10 days (range: 1-138). Intravenous doses ranged from 4.9 to 7.0 mg/kg (median: 6.5) twice daily, and oral doses from 3.8 to 29 mg/kg (median: 9.5) twice daily, respectively. The median trough concentration was 0.63 mg/L (range: 0.01-16.2; 38 samples). Only 34.2% of samples were in the recommended target range of 1-6 mg/L; 57.9% had lower and 7.9% higher trough concentrations. Hepatic function parameters analysed at baseline, during treatment and at end of treatment did not show significant changes during VCZ treatment. There was no correlation between dose and exposure or hepatic function parameters. In three episodes, VCZ was discontinued due to an AE (6%; three patients). In conclusion, this retrospective analysis reveals no signal for increased toxicity in paediatric patients <24 months of age. Empirical dosing resulted in mostly subtherapeutic exposures which emphasises the need for more systematic study of the pharmacokinetics of VCZ in this age group.

Optimization of Voriconazole Dosing Regimens Against Aspergillus Species and Candida Species in Pediatric Patients After Hematopoietic Cell Transplantation: A Theoretical Study Based on Pharmacokinetic/Pharmacodynamic Analysis

This study aimed to optimize the dosing regimens of voriconazole (VRC) for pediatric patients after hematopoietic cell transplantation with different cytochrome P450 (CYP) 2C19 phenotypes and body weights, based on pharmacokinetic (PK)/pharmacodynamic (PD) analysis. The PK parameters of VRC were derived from previous literature. Combined with key factors affecting VRC, patients were categorized into 9 subgroups based on different CYP2C19 phenotypes (poor metabolizer/intermediate metabolizer, normal metabolizer, and rapid metabolizer/ultrarapid metabolizer) and typical body weights (15, 40, and 65 kg). Monte Carlo simulation was used to investigate dosing regimens for different groups. The area under the 24-hour free drug concentration-time curve to the minimum inhibitory concentration (MIC) > 25 was used as the target value for effective treatment. The probability of target achievement and the cumulative fraction of response were determined on the basis of the assumed MICs and MICs distribution frequency of Aspergillus species and Candida species. When the MIC was ≤1 mg/L, 4 mg/kg every 12 hours was sufficient for optimal effects in groups 1-3 and groups 5 and 6; however, 6 mg/kg every 12 hours was required for group 4, and 8 mg/kg every 12 hours was required for groups 7-9. In empirical treatment, lower (2-6 mg/kg every 12 hours) and higher (6-12 mg/kg every 12 hours) dosing regimens were recommended for Candida spp. and Aspergillus spp., respectively. Our findings will assist in selecting appropriate dosing regimens of VRC for pediatric patients after hematopoietic cell transplantation with different CYP2C19 phenotypes and body weights. Clinically, it is better to continuously adjust the dosing on the basis of the therapeutic drug monitoring.

Use of Modeling and Simulation to Predict the Influence of Triazole Antifungal Agents on the Pharmacokinetics of Crizotinib

Crizotinib is used for the treatment of c-ros oncogene 1-positive advanced non-small-cell lung cancer. Triazole antifungal agents are widely used for invasive fungal infections in clinical practice. To predict the potential influence of different triazoles (voriconazole, fluconazole, and itraconazole) on the pharmacokinetics of crizotinib by modeling and simulation the physiologically based pharmacokinetic models were established and validated in virtual cancer subjects through Simcyp software based on the essential physicochemical properties and pharmacokinetic data collected. The validated physiologically based pharmacokinetic models were applied to predict the drug-drug interactions between crizotinib and different triazoles (voriconazole, fluconazole, or itraconazole) in patients with cancer. Crizotinib and triazole antifungal agents were administered orally. The predicted plasma concentration vs time profiles of crizotinib, voriconazole, fluconazole, and itraconazole showed good agreement with observed, respectively. The geometric mean area under the plasma concentration-time curve (AUC) of crizotinib was increased by 84%, 58%, and 79% when coadministered with voriconazole, fluconazole, or itraconazole at multiple doses, respectively. The drug-drug interaction results showed increased pharmacokinetic exposure (maximum plasma concentration and area under the plasma concentration-time curve) of crizotinib when coadministrated with different triazoles (voriconazole > itraconazole > fluconazole). Among the 3 triazoles, voriconazole exhibited the most significant influence on the pharmacokinetic exposure of crizotinib. In clinic, adverse drug reactions and toxicity related to crizotinib should be carefully monitored, and therapeutic drug monitoring for crizotinib is recommended to guide dosing and optimize treatment when coadministered with voriconazole, fluconazole, or itraconazole.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.