A Population Pharmacokinetics Model of Busulfan in Pediatric Patients with Thalas-semia Major.

Perampanel is a promising epilepsy treatment with an innovative mechanism of action. This study was performed to investigate the factors affecting perampanel clearance in a population pharmacokinetic (PPK) model of Chinese pediatric and adult patients with epilepsy. A total of 135 perampanel plasma concentrations from 125 patients with epilepsy were analyzed using the PPK model with nonlinear mixed-effects modeling. One-compartment and proportional residual models best described the pharmacokinetics of perampanel. Covariate effects on the model parameters were assessed using forward and backward elimination. Goodness-of-fit, bootstrapping, visual predictive checks, and normalized prediction distribution errors were used to evaluate the model. Monte Carlo simulations were conducted to assess the impact of covariate combinations on perampanel plasma concentrations at different dosages. In the final PPK model, body weight (BW), concomitant carbamazepine (CBZ), oxcarbazepine (OXC), and C-reactive protein (CRP) levels significantly influenced perampanel clearance. The interindividual clearance was calculated as follows: 0.84 × (BW/70) 0.53 × e CBZ × e OXC × e CRP (CBZ = 0.98, when comedicated with carbamazepine; OXC = 0.43, when comedicated with oxcarbazepine; CRP = -0.69, when CRP >15 mg/L, otherwise = 0). The estimates (relative standard error) for clearance and apparent volume of distribution of the final model were 0.84 L/h (8.75%) and 64.35 L (19.78%), respectively. The model maintained its stability and effectiveness with moderate predictability. BW and CBZ, OXC, and CRP levels may influence perampanel clearance in both pediatric and adult patients with epilepsy according to a population pharmacokinetic model that included real-world data.

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.

Population pharmacokinetics of vancomycin in Chinese patients with augmented renal clearance

Oxcarbazepine (OXC) is an antiepileptic drug whose efficacy is largely attributed to its monohydroxy derivative metabolite (MHD). Nevertheless, there exists significant inter-individual variability in both the pharmacokinetics and therapeutic response of this drug. The objective of this study is to explore the impact of patients' characteristics and genetic variants on MHD clearance in a population pharmacokinetic (PPK) model of Chinese pediatric patients with epilepsy. The PPK model was developed using a nonlinear mixed effects modeling method based on 231 MHD plasma concentrations obtained from 185 children with epilepsy. The one-compartment model and combined residual model were established to describe the pharmacokinetics of MHD. Forward addition and backward elimination were employed to evaluate the impact of covariates on the model parameters. The model was evaluated using goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. In the two final PPK models, age, estimated glomerular filtration rate (eGFR), and a combined genotype of six variants (rs1045642, rs2032582, rs7668282, rs2396185, rs2304016, rs1128503) were found to significantly reduce inter-individual variability for MHD clearance. The inter-individual clearance equals to 1.38 × (Age/4.74)0.29 × (eGFR/128.66)0.25 × eθABCB-UGT-SCN-INSR for genetic variants included model and 1.30 × (Age/4.74)0.30 × (eGFR/128.66)0.23 for model without genetic variants. The precision of all parameters was deemed acceptable, and the model exhibited good predictability while remaining stable and effective. Conclusion: Age, eGFR, and genotype may play a significant role in MHD clearance in children with epilepsy. The developed PPK models hold potential utility in facilitating oxcarbazepine dose adjustment in pediatric patients. What is Known: • The adjustment of the oxcarbazepine regimen remains difficult due to the considerable inter- and intra-individual variability of oxcarbazepine pharmacokinetics. • Body weight and co-administration with enzyme-inducing antiepileptic drugs emerge as the most influential factors contributing to the pharmacokinetics of MHD. What is New: • A positive correlation was observed between eGFR and the clearance of MHD in pediatric patients with epilepsy. • We explored the influence of genetic polymorphisms on MHD clearance and identified a combined genotype (ABCB-UGT-SCN-INSR) that exhibited a significant association with MHD concentration.

To establish the population pharmacokinetics (PPK) model of cyclosporine A(CsA) in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation (HSCT), aiming at providing a reference for clinical dose individualization of CsA. Children with thalassemia who underwent allogeneic HSCT were enrolled retrospectively. The PPK structural model and the random variable model of CsA were established on NONMEN. And goodness of fit plots (GOFs), visual predictive check (VPC), and bootstrap and normalized prediction distribution errors (NPDE) were used to evaluate the final model. A one-compartment model with first-order absorption was employed to fit the base model. A total of 74 pediatric patients and 600 observations of whole blood concentration were included. The final model included weight (WT) in clearance (CL), alongside post-operative day (POD), fluconazole (FLUC), voriconazole (VORI), posaconazole (POSA), and red blood cell count (RBC) significantly. All the model evaluations were passed. In the PPK model based on the pediatric cohort on CsA with thalassemia undergoing allogeneic HSCT, WT, POD, FLUC, VORI, POSA, and RBC were found to be the significant factors influencing CL of CsA. The reliability and robustness of the final model were excellent. It is expected that the PPK model can assist in individualizing dosing strategy clinically.

There are several reports describing population pharmacokinetic (popPK) models of busulfan (BU). However, limited information is available in Chinese hematopoietic stem cell transplantation (HSCT) patients. The present study aimed to establish a popPK model of intravenous BU in Chinese HSCT patients for individualized drug therapy. The popPK model of BU was developed from a total of 284 concentration-time points from 53 patients. The effects of demographic and biochemical covariates were investigated by nonlinear mixed effect model (NONMEM) software. Plots, visual predictive check (VPC), bootstrap and normalized prediction distribution error (NPDE) were performed to determine the stability and the reliability of the final model. A one-compartment model with first-order elimination process was confirmed as the final structural model for BU. For a typical patient whose body surface area (BSA) is 1.7m2 , the population typical values of CL and Vd were 11.86L/h, and 48.2L, respectively. The result suggested BSA showed significant influence on CL and Vd (P<.001). Plots revealed the final model was performing a goodness fit. The steady rate verified by bootstrap was 100%, relative deviation was less than 4.00%, estimated value of final model was in the 95% confidence interval (CI). The VPC results showed the observed values were almost all positioned within the 5th and 95th CIs. The mean and variance of the NPDE were 0.0363 (Wilcoxon signed-rank test, 0.298) and 0.877 (Fisher variance test, 0.134; SW test of normality, 0.108), respectively. The global adjusted P value was 0.305, which indicated that the prediction of the BU popPK model was adequate. A physician-friendly Microsoft Excel-base tool was implemented using the final popPK model for designing individualized dosing regimens.

Population pharmacokinetics of valproic acid in epileptic children: Effects of clinical and genetic factors

1. Several tacrolimus population pharmacokinetic (PPK) models in hematopoietic stem cell transplantation (HSCT) patients have been set up to recommend an optimal dosage schedule. However, the PPK model of Chinese pediatric HSCT patients has not been reported. The study is to investigate whether published PPK models of HSCT patients can be used to simulate Chinese pediatric HSCT patients and establish the tacrolimus PPK model of Chinese pediatric HSCT patients.2. Published PPK models were collected from the literature and assessed using Chinese pediatric HSCT patients via the individual prediction error method. The establishment of tacrolimus PPK model in Chinese pediatric HSCT patients was characterized with nonlinear mixed-effects modeling (NONMEM).3. Three published HSCT PPK models were identified, two of which could be applied to our external dataset. However, these models were dissatisfactory in terms of individual prediction error and, hence, inadequate for extrapolation. Finally, a new tacrolimus PPK model in Chinese pediatric HSCT patients was established. Based on the simulation results of our model, new initial dosage suggestions were recommended. In conclusion, the tacrolimus PPK model in Chinese pediatric HSCT patients was presented and the model could be used to predict individualized dosing regimens in children with HSCT.

Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy. The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies. In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW⁄11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW⁄11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW⁄11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate. The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

CPX-351 Population Pharmacokinetics in Pediatric and Adult Patients with Acute Myeloid Leukemia (AML)

Objective: The aim of this study was to establish a population pharmacokinetic (PPK) model of valproic acid (VPA) in pediatric patients with epilepsy in southern China, and provide guidance for individualized medication of VPA therapy.Methods: A total of 376 VPA steady-state trough concentrations were collected from 103 epileptic pediatric patients. The PPK parameter values for VPA were calculated by using the nonlinear mixed-effects modeling (NONMEM) method, and a one-compartment model with first-order absorption and elimination processes was applied. Covariates included demographic information, concomitant medications and selected gene polymorphisms. Goodness-of-fit (GOF), bootstrap analysis, and visual predictive check (VPC) were used for model evaluation. In addition, we used Monte Carlo simulations to propose dose recommendations for different subgroup patients.Results: A significant effect of the patient age and ABCB1 genotypes was observed on the VPA oral clearance (CL/F) in the final PPK model. Compared with patients with the ABCB1 rs3789243 AA genotype, CL/F in patients with GG and AG genotypes was increased by 8% and reduced by 4.7%, respectively. The GOF plots indicated the satisfactory predictive performance of the final model, and the evaluation by bootstrap and VPC showed that a stable model had been developed. A table of individualized dosing regimens involving age and ABCB1 genotype was constructed based on the final PPK model.Conclusion: This study quantitatively investigated the effects of patient age and ABCB1 rs3789243 variants on the pharmacokinetic variability of VPA. The PPK models could be beneficial to individual dose optimization in epileptic children on VPA therapy.

Vancomycin is a primary antibiotic for the treatment of severe infections in children with malignant hematological disease. However, precise dosing of vancomycin is difficult in children because of high interindividual variability and limited data of pharmacokinetic profiles. The present study aims to develop a population pharmacokinetic (PPK) model for vancomycin in Chinese pediatric patients with hematological malignancies. This was a retrospective pharmacokinetic study. The setting for this study was a tertiary-care children's hospital. This study included 92 pediatric patients with hematological malignancies who received vancomycin and experienced therapeutic drug monitoring from February 2017 to December 2018. A PPK model was generated with a nonlinear mixed effects model. In addition, required doses to achieve target therapeutic concentrations were simulated based on the final model. A one-compartment model with first-order elimination fit the concentration data best. Actual body weight (BW) and glomerular filtration rate (GFR) were the significant influential factors on the clearance (CL) of vancomycin. The final PPK model for CL was CL (L/h)=4.18 , K= , and the volume of distribution was 22.3L. The model proved to be robust and reliable. Reference dosing regimens were proposed based on the final model. A PPK model of vancomycin was established for Chinese pediatric patients with hematological malignancies using a nonlinear mixed effects model, which provided a reference for the clinical application of vancomycin.

Objective: The primary objective of this study revolves around the development of a population pharmacokinetic (PPK) model for vancomycin in neonatal subjects, with the objective of providing a theoretical basis for judicious therapeutic interventions.Methods: In this study, a retrospective collection encompassed 75 neonatal patients, contributing to a total of 89 vancomycin blood concentration monitoring datasets. The establishment of the PPK model is carried out utilizing the nonlinear mixed effects model methodology. The PPK model was constructed employing a one‐compartment model with proportional residual error, and the influence of covariates on pharmacokinetic parameters was systematically assessed through forward stepwise addition and backward elimination methods. The stability and predictive accuracy of the final model were assessed using goodness‐of‐fit plots, nonparametric bootstrap validation, visual predictive checks, and normalized prediction distribution errors. Furthermore, Monte Carlo simulations were employed to predict vancomycin concentrations in neonatal patients with typical characteristics.Results: The final PPK model yielded population‐typical values of 0.24 L/h for vancomycin clearance (CL). Noteworthy contributors to vancomycin CL were identified as body weight, gestational age, creatinine clearance rate (CLcr), and sex. Internal validation results of the model indicate that it possesses stability, efficacy, and demonstrates a favorable predictive capacity. Monte Carlo simulations indicate that for a male neonatal patient characterized by a gestational age of 37 weeks, a body weight of 2.5 kg, and a CLcr of 60 mL/min, the recommended dosing regimen is 25.5 to 41.5 mg every 8 h.Conclusion: This investigation has successfully formulated a PPK model for vancomycin in neonatal patients, offering the capacity to estimate individual CL. The dosing regimen for neonates should take into account factors such as body weight, gestational age, CLcr, and sex.

A Population Pharmacokinetic Model for Concizumab Based on Phase 1 and Phase 2 Trial Data

Busulfan, a bifunctional alkylating agent, has been used as a conditioning regimen prior to allogeneic hematopoietic stem cell transplantation (HSCT). The aim of this study was to derive a novel once-daily intravenous (IV) busulfan dosing nomogram for pediatric patients undergoing HSCT using a population pharmacokinetic (PK) model. A population PK analysis was performed using 2183 busulfan concentrations in 137 pediatric patients (age: 0.6-22.2 years), who received IV busulfan once-daily for 4 days before undergoing HSCT. Based on the final population PK model, an optimal once-daily IV busulfan dosing nomogram was derived. The percentage of simulated patients achieving the daily target area under the concentration-time curve (AUC) by the new nomogram was compared with that by other busulfan dosing regimens including the FDA regimen, the EMA regimen, and the empirical once-daily regimen without therapeutic drug monitoring (TDM). A one-compartment open linear PK model incorporating patient's body surface area, age, dosing day, and aspartate aminotransferase as a significant covariate adequately described the concentration-time profiles of busulfan. An optimal dosing nomogram based on the PK model performed significantly better than the other dosing regimens, resulting in >60% of patients achieving the target AUC while the percentage of patients exceeding the toxic AUC level was kept <25% during the entire treatment period. A novel once-daily busulfan dosing nomogram for pediatric patients undergoing HSCT is useful for clinicians, particularly in a setting where TDM service is not readily available or to optimize the dose on day 1.