Pharmacokinetic/Pharmacodynamic Analysis of Voriconazole Against Candida spp. and Aspergillus spp. in Allogeneic Stem Cell Transplant Recipients

Nanotechnology-Based Approaches for Voriconazole Delivery Applied to Invasive Fungal Infections

Invasive fungal infections increase mortality and morbidity rates worldwide. The treatment of these infections is still limited due to the low bioavailability and toxicity, requiring therapeutic monitoring, especially in the most severe cases. Voriconazole is an azole widely used to treat invasive aspergillosis, other hyaline molds, many dematiaceous molds, Candida spp., including those resistant to fluconazole, and for infections caused by endemic mycoses, in addition to those that occur in the central nervous system. However, despite its broad activity, using voriconazole has limitations related to its non-linear pharmacokinetics, leading to supratherapeutic doses and increased toxicity according to individual polymorphisms during its metabolism. In this sense, nanotechnology-based drug delivery systems have successfully improved the physicochemical and biological aspects of different classes of drugs, including antifungals. In this review, we highlighted recent work that has applied nanotechnology to deliver voriconazole. These systems allowed increased permeation and deposition of voriconazole in target tissues from a controlled and sustained release in different routes of administration such as ocular, pulmonary, oral, topical, and parenteral. Thus, nanotechnology application aiming to delivery voriconazole becomes a more effective and safer therapeutic alternative in the treatment of fungal infections.

Systematic Evaluation of Voriconazole Pharmacokinetic Models without Pharmacogenetic Information for Bayesian Forecasting in Critically Ill Patients

Voriconazole (VRC) is used as first line antifungal agent against invasive aspergillosis. Model-based approaches might optimize VRC therapy. This study aimed to investigate the predictive performance of pharmacokinetic models of VRC without pharmacogenetic information for their suitability for model-informed precision dosing. Seven PopPK models were selected from a systematic literature review. A total of 66 measured VRC plasma concentrations from 33 critically ill patients was employed for analysis. The second measurement per patient was used to calculate relative Bias (rBias), mean error (ME), relative root mean squared error (rRMSE) and mean absolute error (MAE) (i) only based on patient characteristics and dosing history (a priori) and (ii) integrating the first measured concentration to predict the second concentration (Bayesian forecasting). The a priori rBias/ME and rRMSE/MAE varied substantially between the models, ranging from −15.4 to 124.6%/−0.70 to 8.01 mg/L and from 89.3 to 139.1%/1.45 to 8.11 mg/L, respectively. The integration of the first TDM sample improved the predictive performance of all models, with the model by Chen (85.0%) showing the best predictive performance (rRMSE: 85.0%; rBias: 4.0%). Our study revealed a certain degree of imprecision for all investigated models, so their sole use is not recommendable. Models with a higher performance would be necessary for clinical use.

Postantifungal Effect of Antifungal Drugs against Candida: What Do We Know and How Can We Apply This Knowledge in the Clinical Setting?

The study of the pharmacological properties of an antifungal agent integrates the drug pharmacokinetics, the fungal growth inhibition, the fungicidal effect and the postantifungal activity, laying the basis to guide optimal dosing regimen selection. The current manuscript reviews concepts regarding the postantifungal effect (PAFE) of the main classes of drugs used to treat Candida infections or candidiasis. The existence of PAFE and its magnitude are highly dependent on both the fungal species and the class of the antifungal agent. Therefore, the aim of this article was to compile the information described in the literature concerning the PAFE of polyenes, azoles and echinocandins against the Candida species of medical interest. In addition, the mechanisms involved in these phenomena, methods of study, and finally, the clinical applicability of these studies relating to the design of dosing regimens were reviewed and discussed. Additionally, different factors that could determine the variability in the PAFE were described. Most PAFE studies were conducted in vitro, and a scarcity of PAFE studies in animal models was observed. It can be stated that the echinocandins cause the most prolonged PAFE, followed by polyenes and azoles. In the case of the triazoles, it is worth noting the inconsistency found between in vitro and in vivo studies.

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

Background: Voriconazole is a potent antifungal drug with complex pharmacokinetics caused by time-dependent inhibition and polymorphisms of metabolizing enzymes. It also exhibits different pharmacokinetic characteristics between adults and children. An understanding of these alterations in pharmacokinetics is essential for pediatric dose optimization.

Objective: To determine voriconazole plasma exposure in the pediatric population and further investigate optimal dosage regimens.

Methods: An adult and pediatric physiologically based pharmacokinetic (PBPK) model of voriconazole, integrating auto-inhibition of cytochrome P450 3A4 (CYP3A4) and CYP2C19 gene polymorphisms, was developed. The model was evaluated with visual predictive checks and quantitative measures of the predicted/observed ratio of the area under the plasma concentration-time curve (AUC) and maximum concentration (C_max). The validated pediatric PBPK model was used in simulations to optimize pediatric dosage regimens. The probability of reaching a ratio of free drug (unbound drug concentration) AUC during a 24-h period to minimum inhibitory concentration greater than or equal to 25 (fAUC_24h/MIC ≥ 25) was assessed as the pharmacokinetic/pharmacodynamic index.

Results: The developed PBPK model well represented voriconazole's pharmacokinetic characteristics in adults; 78% of predicted/observed AUC ratios and 85% of C_max ratios were within the 1.25-fold range. The model maintained satisfactory prediction performance for intravenous administration in pediatric populations after incorporating developmental changes in anatomy/physiology and metabolic enzymes, with all predicted AUC values within 2-fold and 73% of the predicted C_max within 1.25-fold of the observed values. The simulation results of the PBPK model suggested that different dosage regimens should be administered to children according to their age, CYP2C19 genotype, and infectious fungal genera.

Conclusion: The PBPK model integrating CYP3A4 auto-inhibition and CYP2C19 gene polymorphisms successfully predicted voriconazole pharmacokinetics during intravenous administration in children and could further be used to optimize dose strategies. The infectious fungal genera should be considered in clinical settings, and further research with large sample sizes is required to confirm the current findings.