Dosage optimization of voriconazole in children with haematological malignancies based on population pharmacokinetics.

WHAT IS KNOWN AND OBJECTIVES: Voriconazole has a complex pharmacokinetic profile and exhibits different pharmacokinetic characteristics in adults and children. Nevertheless, few studies have been conducted on the population pharmacokinetics (PPK) of voriconazole in children with haematological malignancies. This study aims to build a PPK model and propose a suitable voriconazole treatment scheme for children with haematological malignancies. METHODS: We retrospectively collected 146 samples from 67 children aged from 1.08 to 17.92 years. The PPK model was established using nonlinear mixed effects modelling (NONMEM). Dosage simulations were conducted on the basis of the final model's covariates. RESULTS AND DISCUSSION: Data were fully characterized by a one-compartment model with first-order absorption and elimination. The weight (WT), CYP2C19 phenotype, and Albumin (ALB) were notable covariates for clearance (CL). The typical values of CL, the volume of distribution (V), and oral bioavailability (F) were 2.29 L/h, 76 L, and 0.902, respectively. The proposed doses for different CYP2C19 genotypes were presented in this ranking: EM (extensive metabolizer) > IM (intermediate metabolizer) > PM (poor metabolizer). Furthermore, higher dosages for light WT patients were recommended while lower ALB levels required lower doses. The probability of achieving the target (PTA) for the recommended doses ranged from 72.2% to 99%. WHAT IS NEW AND CONCLUSION: We successfully built a voriconazole PPK model for children with hematologic malignancies. Dosing regimens were developed for different patients based on the final model, which could enhance the rational use of voriconazole in children with haematological malignancies.

Population pharmacokinetics of voriconazole and initial dosage optimization in patients with talaromycosis.

The high variability and unpredictability of the plasma concentration of voriconazole (VRC) pose a major challenge for clinical administration. The aim of this study was to develop a population pharmacokinetics (PPK) model of VRC and identify the factors influencing VRC PPK in patients with talaromycosis. Medical records and VRC medication history of patients with talaromycosis who were treated with VRC as initial therapy were collected. A total of 233 blood samples from 69 patients were included in the study. A PPK model was developed using the nonlinear mixed-effects models (NONMEM). Monte Carlo simulation was applied to optimize the initial dosage regimens with a therapeutic range of 1.0-5.5 mg/L as the target plasma trough concentration. A one-compartment model with first-order absorption and elimination adequately described the data. The typical voriconazole clearance was 4.34 L/h, the volume of distribution was 97.4 L, the absorption rate constant was set at 1.1 h-1, and the bioavailability was 95.1%. Clearance was found to be significantly associated with C-reactive protein (CRP). CYP2C19 polymorphisms had no effect on voriconazole pharmacokinetic parameters. Monte Carlo simulation based on CRP levels showed that a loading dose of 250 mg/12 h and a maintenance dose of 100 mg/12 h are recommended for patients with CRP ≤ 96 mg/L, whereas a loading dose of 200 mg/12 h and a maintenance dose of 75 mg/12 h are recommended for patients with CRP > 96 mg/L. The average probability of target attainment of the optimal dosage regimen in CRP ≤ 96 mg/L and CRP > 96 mg/L groups were 61.3% and 13.6% higher than with empirical medication, and the proportion of Cmin > 5.5 mg/L decreased by 28.9%. In conclusion, the VRC PPK model for talaromycosis patients shows good robustness and predictive performance, which can provide a reference for the clinical individualization of VRC. Adjusting initial dosage regimens based on CRP may promote the rational use of VRC.

Population pharmacokinetics of mycophenolate mofetil in pediatric patients early after liver transplantation.

Objective: To investigate the factors influencing the pharmacokinetics of mycophenolate mofetil (MMF) in pediatric patients after liver transplantation, and to establish a population pharmacokinetics model, which can provide a reference for clinical dosage adjustment. Methods: A prospective study in a single center was performed on pediatric patients who were administrated with mycophenolate mofetil dispersible tablets (MMFdt) for at least 4 days after liver transplantation continuously. Blood samples were collected in ethylene diamine tetraacetic acid anticoagulant tubes before dosing and 0.5, 1, 2, 4, 8, and 12 h after the morning intake of MMFdt. The concentrations of mycophenolic acid (MPA) in plasma were assayed with a validated reverse-phase high-performance liquid chromatography method. UGT1A8 518C > G, UGT1A9 -275T > A, UGT1A9 -2152C > T, UGT2B7 211G > T, SLC O 1B1 521T > C polymorphism were determined by Sanger sequencing. Nonlinear mixed effects modeling was used to establish the population pharmacokinetics (PPK) model. The predictability and stability of the model were internally evaluated by the goodness of fit plots, visual prediction check, normalized prediction errors, and bootstraps. Results: A two-compartment model with first-order absorption and first-order elimination was established with 115 MPA concentrations from 20 pediatric patients. The final model were: CL/F (L/h) = 14.8×(WT/7.5)0.75×(DOSE/11.16)0.452×е0.06, Ka (h-1) = 2.02×(WT/7.5)-0.25, Vc/F (L) = 6.01×(WT/7.5), Vp/F (L) = 269 (fixed), Q/F (L/h) = 15.4×(WT/7.5)0.75×е1.39. Where CL/F was the apparent clearance rate, Ka was the absorption rate constant, Vc/F was the apparent distribution volume of the central compartment, Vp/F was the apparent distribution volume of the peripheral compartment, Q/F was the atrioventricular clearance rate, WT was the body weight of the subject, and DOSE was the MMFdt administered dose. The model indicated there was large inter-individual variability in CL/F and Q/F after multiple dosing of MMFdt. Internal evaluation results showed that the final model had good stability and prediction performance. Conclusion: A stable and predictive population pharmacokinetic model of MMFdt in pediatric patients after the early stage of liver transplantation was established. The pediatric patient's weight and the dose of MMFdt can be a reference to adjust the MMFdt dose.

Influential Factors and Efficacy Analysis of Tacrolimus Concentration After Allogeneic Hematopoietic Stem Cell Transplantation in Children with ß-Thalassemia Major.

PURPOSE: To analyze factors influencing tacrolimus (TAC) trough concentration (C0) in ß-thalassemia major (ß-TM) pediatric patients after allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and to investigate the effects of genotype polymorphism and drug-drug interactions on TAC trough concentration in children with ß-TM. Furthermore, to analyze the correlation between TAC C0 and efficacy and adverse reactions. PATIENTS AND METHODS: Prospectively collection of demographic information and details of combined treatment of patients with ß-TM receiving HSCT, and genotypes of CYP3A4, CYP3A5, and ABCB1 (rs1045642, rs1128503, rs2032582) were obtained for each patient. Univariate analysis and multiple linear regression analysis were used to investigate influencing factors on TAC C0. The impact of different genotypes and the co-administration of azole antifungal drugs on ß-TM patients receiving TAC were evaluated, together with the correlation between acute graft-versus-host disease (aGVHD), infection, and liver injury of TAC C0. RESULTS: A total of 46 patients with 587 concentration data were included. The multiple linear regression results showed that the patient's sex, weight, postoperative time, hemoglobin, platelet count, serum cystatin C, and combined voriconazole were independent influencing factors of the infusion trough concentration/daily dose, C0/Div. Age, body surface area, postoperative time, co-administration of voriconazole, and CYP3A4*18B are independent influencing factors of C0/Dpo. Group comparisons showed that voriconazole can affect TAC C0 administered intravenously (IV) and orally in ß-TM pediatric patients, while patient genotype can affect TAC C0 during oral administration. TAC C0 does not correlate with aGVHD or liver injury, but infection may be associated with TAC C0. CONCLUSION: The concentration of TAC should be closely monitored when co-administered with voriconazole. It is worth considering that the influence of genotype on the trough concentration of oral TAC and individualized drug administration warrant investigation. Finally, this study indicated that C0 is not suitable as an indicator of the efficacy of TAC.

Systematic external evaluation of reported population pharmacokinetic models of vancomycin in Chinese children and adolescents.

WHAT IS KNOWN AND OBJECTIVES: Various population pharmacokinetic (PopPK) models for vancomycin in children and adolescents have been constructed to optimize the therapeutic regimen of vancomycin. However, little is known about their predictive performance when extrapolated to different clinical centres. Therefore, the aim of this study was to externally validate the predictability of vancomycin PopPK model when extrapolated to different clinical centres and verify its applicability in an independent data set. METHODS: The published models were screened from the literature and evaluated using an external data set of a total of 451 blood concentrations of vancomycin measured in 220 Chinese paediatric patients. Prediction- and simulation-based diagnostics and Bayesian forecasting were performed to evaluate the predictive performance of the models. RESULTS: Ten published PopPK models were assessed. Prediction-based diagnostics showed that none of the investigated models met all the standards (median prediction error (MDPE) ≤ ±20%, median absolute prediction error (MAPE) ≤30%, PE% within ±20% (F20 ) ≥35% and PE% within ±30% (F30 ) ≥50%), indicating unsatisfactory predictability. In simulation-based diagnostics, both the visual predictive checks (VPC) and the normalized prediction distribution error (NPDE) indicated misspecification in all models. Bayesian forecasting results showed that the accuracy and precision of individual predictions could be significantly improved with one or two prior observations, but frequent monitoring might not be necessary in the clinic, since Bayesian forecasting identified that greater number of samples did not significantly improve the predictability. Model 3 established by Moffett et al showed better predictability than other models. WHAT IS NEW AND CONCLUSION: The 10 published models performed unsatisfactorily in prediction- and simulation-based diagnostics; none of the published models was suitable for designing the initial dosing regimens of vancomycin. Pharmacokinetic characteristics and covariates, such as weight, renal function, age and underlying disease should be taken into account when extrapolating the vancomycin model. Bayesian forecasting combined with therapeutic drug monitoring based on model 3 can be used to adjust vancomycin dosing regimens.

Initial Dosage Optimization of Tacrolimus in Pediatric Patients With Thalassemia Major Undergoing Hematopoietic Stem Cell Transplantation Based on Population Pharmacokinetics.

BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is an effective treatment for hematological disorders. Tacrolimus is widely used after HSCT, but it has highly interindividual variable pharmacokinetics. Population pharmacokinetics (PPK) researches of tacrolimus in children with ß-thalassemia major (ß-TM) undergoing HSCT are insufficient. OBJECTIVE: To establish a PPK model of tacrolimus in children with ß-TM and optimize initial dosing regimen for achieving target concentration of 5 to 15 ng/mL. METHODS: Data on patients aged <18 years were retrospectively collected from January 2017 to December 2018. PPK analysis and Monte Carlo simulations were performed using nonlinear mixed-effects modeling. RESULTS: A data set of 55 patients with 332 concentrations was included. A 2-compartment model could best describe the pharmacokinetics of tacrolimus. The body surface area and gender were significant covariates in the final model. The typical value of clearance, the distribution volume of the central room, the distribution volume of the peripheral room, and the intercompartmental clearance were 5.05L/h, 4.33L, 155L, and 6.22L/h, respectively. The optimal initial dosing regimen of 0.03, 0.04, 0.05, 0.06, and 0.10 mg/kg were appropriate for female children with a weight (WT) of 50 to 10 kg. The regimen of 0.04, 0.05, 0.06, 0.07, and 0.12 mg/kg is suitable for male children with a WT of 50 to 10 kg. The probability of target attainment (PTA) of each regimen reached 91%. CONCLUSION AND RELEVANCE: A stable PPK model of tacrolimus was established. The proposed dosage regimen reached a good PTA, which could provide a reference for tacrolimus therapy.