Population pharmacokinetics of cyclosporine A based on NONMEM in Chinese allogeneic hematopoietic stem cell transplantation recipients

Population pharmacokinetics of cyclosporine A in hematopoietic stem cell transplant recipients: A systematic review

Cyclosporine A (CsA) is the prevalent immunosuppressive drug for preventing and treating graft-versus-host disease after hematopoietic stem cell transplantation (HSCT) in both children and adults. Population pharmacokinetic studies have identified covariates, owing to their large between-subject variability, facilitating individualized therapy. However, no review has summarized CsA's population pharmacokinetics post-HSCT. This systematic review aims to synthesize population pharmacokinetic studies of CsA therapy in HSCT recipients and explore influencing covariates. Thirteen studies, comprising five involving children, one involving both children and adults and seven involving adults, were included. The median apparent clearance in children surpassed that in adults, influenced notably by hematocrit level and body. While liver function impacted clearance, the effect was insignificant. Co-administration with cytochrome P450 enzyme inhibitors (e.g., fluconazole (Diflucan) or itraconazole) decreased drug clearance, whereas inducers (e.g., rifampicin or rifapentine) increased it. Area under the curve analysis is recommended over trough concentration-based monitoring for HSCT recipients on CsA. In cases of insufficient trough concentration, additional sampling points are recommended for improved area under the curve estimation. Further studies are needed to evaluate the optimal sampling points required for the area under the curve estimation in CsA therapy post-HSCT.

Population pharmacokinetics of cyclosporine A in pediatric patients with thalassemia undergoing allogeneic hematopoietic stem cell transplantation

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Initial dosage optimisation of cyclosporine in Chinese paediatric patients undergoing allogeneic haematopoietic stem cell transplantation based on population pharmacokinetics: a retrospective study

OBJECTIVE

Improved understanding of cyclosporine A (CsA) pharmacokinetics in children undergoing allogeneic haematopoietic stem cell transplantation (allo-HSCT) is crucial for effective prevention of acute graft-versus-host disease and medication safety. The aim of this study was to establish a population pharmacokinetic (Pop-PK) model that could be used for individualised therapy to paediatric patients undergoing allo-HSCT in China.

DESIGN, SETTING AND PARTICIPANTS

A retrospective analysis of 251 paediatric HSCT patients who received CsA intravenously in the early post transplantation period at Women and Children's Medical Center in Guangzhou was conducted.

ANALYSIS MEASURES

The model building dataset from 176 children was used to develop and analyse the CsA Pop-Pk model by using the nonlinear mixed effect model method. The basic information was collected by the electronic medical record system. Genotype was analysed by matrix-assisted time-of-flight mass spectrometry. The stability and predictability of the final model were verified internally, and a validation dataset of 75 children was used for external validation. Monte Carlo simulation is used to adjust and optimise the initial dose of CsA in paediatric allo-HSCT patients.

RESULTS

The typical values for clearance (CL) and volume of distribution ([Formula: see text]) were 14.47 L/hour and 2033.53 L, respectively. The body weight and haematocrit were identified as significant variables for V, while only body weight had an impact on CL. The simulation based on the final model suggests that paediatrics with HSCT required an appropriate intravenous dose of 5 mg/kg/day to reach the therapeutic trough concentration.

CONCLUSIONS

The CsA Pop-PK model established in this study can quantitatively describe the factors influencing pharmacokinetic parameters and precisely predict the intrinsic exposure to CsA in children. In addition, our dosage simulation results can provide evidence for the personalised medications TRIAL REGISTRATION NUMBER: ChiCTR2000040561.

A model based on machine learning for the prediction of cyclosporin A trough concentration in Chinese allo-HSCT patients

BACKGROUND

Cyclosporin A is a calcineurin inhibitor which has a narrow therapeutic window and high interindividual variability. Various population pharmacokinetic models have been reported; however, professional software and technical personnel were needed and the variables of the models were limited. Therefore, the aim of this study was to establish a model based on machine learning to predict CsA trough concentrations in Chinese allo-HSCT patients.

METHODS

A total of 7874 cases of CsA therapeutic drug monitoring data from 2069 allo-HSCT patients were retrospectively included. Sequential forward selection was used to select variable subsets, and eight different algorithms were applied to establish the prediction model.

RESULTS

XGBoost exhibited the highest prediction ability. Except for the variables that were identified by previous studies, some rarely reported variables were found, such as norethindrone, WBC, PAB, and hCRP. The prediction accuracy within ±30% of the actual trough concentration was above 0.80, and the predictive ability of the models was demonstrated to be effective in external validation.

CONCLUSION

In this study, models based on machine learning technology were established to predict CsA levels 3-4 days in advance during the early inpatient phase after HSCT. A new perspective for CsA clinical application is provided.

Effect of posaconazole on the concentration of intravenous and oral cyclosporine in patients undergoing hematopoietic stem cell transplantation

PURPOSE

This study aimed to investigate the interactions between posaconazole (POS) and intravenously/orally administered cyclosporine A (CsA) in allogeneic hematopoietic stem cell transplant (HSCT) recipients.

METHODS

We included 118 allogeneic HSCT patients who received CsA and POS simultaneously between January 2017 and June 2020 in this study. The ratio of CsA blood concentration (ng/mL) to dosage (mg/day) (C/D) before and after POS initiation was compared.

RESULTS

After the initiation of POS, the level of CsA increased 1 to 2 times in 66% (78/118) of patients compared to those without POS. However, the CsA C/D ratio increased by more than threefold in 6% (7/118) of patients after POS initiation, with an increase of more than fourfold in two patients. The median C/D ratio of CsA increased from 0.89 to 1.23 (P < 0.001) and 0.78 to 1.22 (P < 0.001) after POS initiation when CsA was administered intravenously and orally, respectively. In patients who received POS at the time of transition from intravenous to oral CsA, the value increased from 1.01 to 1.38 (P = 0.001). The route of administration had no significant effect on the change in the CsA C/D ratio (P = 0.615). Additionally, we observed the time required for the C/D ratio to reach a plateau after POS initiation was similar on days 13, 8, and 15 under various scenarios.

CONCLUSION

POS treatment increased blood CsA levels. A large variability was found in the fold-change in the CsA C/D ratio. Therefore, CsA doses should be adjusted by closely monitoring the blood levels of CsA after POS initiation.

Population Pharmacokinetics of Cyclosporine in Chinese Pediatric Patients With Acquired Aplastic Anemia

Cyclosporine (CsA) is a component of the first-line treatment for acquired aplastic anemia (acquired AA) in pediatric patients. This study aimed to develop a population pharmacokinetic (PK) model of CsA in Chinese pediatric patients with acquired AA to inform individual dosage regimens. A total of 681 CsA whole blood concentrations and laboratory data of 157 pediatric patients with acquired AA were retrospectively collected from two hospitals in Shanghai. A nonlinear mixed-effect model approach was used to build the population PK model. Potential covariate effects of age, body weight, and biochemical measurements (renal and liver functions) on CsA PK disposition were evaluated. Model fit was assessed using the basic goodness of fit and a visual predictive check. The CsA concentration data were accurately described using a two-compartment disposition model with first-order absorption and elimination. Body weight value was implemented as a fixed allometric function on all clearance and volume of distribution parameters. Total bilirubin level was identified as a significant covariate on apparent clearance (CL/F), with a 1.07% reduction per 1 nmol/L rise in total bilirubin level. The final estimates for CL/F and central volume (Vc/F) were 29.1 L/h and 325 L, respectively, for a typical 28 kg child. Other covariates (e.g., gender, age, albumin, hemoglobin, hematocrit, serum creatinine, and concomitant medication) did not significantly affect the PK properties of CsA. This population PK model, along with a maximum a posteriori Bayesian approach, could estimate individual PK parameters in pediatric patients with acquired AA to conduct individual CsA therapy.

Analysis of the variable factors affecting changes in the blood concentration of cyclosporine before and after transfusion of red blood cell concentrate

Background

The blood concentration of cyclosporine (CyA) is frequently elevated following the transfusion of red blood cell concentrate (RCC) to patients after allogeneic hematopoietic stem cell transplantation (HSCT). The aim of this retrospective study was to identify the variable factors affecting changes in the blood concentration of CyA before and after transfusion of RCC.

Methods

We enrolled 105 patients (age, 5–66 years) who received both CyA and transfusion after HSCT. The ratio of the measurement after transfusion to the measurement before transfusion was calculated for the hematocrit and blood concentration/dose ratio of CyA (termed the HCT ratio and the CyA ratio, respectively).

Results

The blood concentration/dose ratio of CyA was increased after transfusion compared with before transfusion (P < 0.001). The HCT ratio was significantly correlated with the CyA ratio (P = 0.23, P < 0.001). The HCT ratio, concomitant medication that could elevate CyA concentration after RCC transfusion, and difference in the alkaline phosphatase level between before and after transfusion (ΔALP) were explanatory variables associated with the variation in the CyA ratio. There was no correlation between the CyA concentration after transfusion and the change in the estimated glomerular filtration rate.

Conclusions

A change in the blood concentration/dose ratio of CyA was found to be associated with a change in the HCT, concomitant medication that could elevate CyA concentration after RCC transfusion, and ALP levels. If the HCT level rises significantly after RCC transfusion, clinicians and pharmacists should pay attention to changes in the blood CyA concentration.

Population pharmacokinetics of ciclosporin in allogeneic hematopoietic stem cell transplant recipients: C-reactive protein as a novel covariate for clearance

WHAT IS KNOWN AND OBJECTIVES

Ciclosporin (CsA), a potent immunosuppressive agent used to prevent graft-versus-host disease in allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients, is characterized by large inter-individual variability and a narrow therapeutic range. The aim of this study was to develop a population pharmacokinetic model for CsA in Chinese allo-HSCT recipients and to identify covariates influencing CsA pharmacokinetics.

METHODS

A total of 758 retrospective drug monitoring data points were collected after intravenous infusion or oral administration of CsA from 59 patients. Population pharmacokinetic analysis was performed using nonlinear mixed effects modelling expressed by differential equations. Monte Carlo simulation was applied to optimize dosage regimens. The final model was validated using bootstrap and normalized prediction distribution errors.

RESULTS AND DISCUSSION

The results showed that the daily CsA dose, haematocrit, total bile acid, C-reactive protein (CRP) and co-administration of triazole antifungal agent were identified as significant covariates for clearance (CL) of CsA. The typical value of CL was 19.8 L/h with an inter-individual variability of 13.1%. The volume of distribution was 1340 L. Bioavailability was 67.2% with an inter-individual variability of 8.5%. Dosing simulation based on the developed model indicated that patients with high CRP concentration required a higher daily dose to attain the therapeutic trough concentration. The influence of CRP ultimately on the therapy outcome of CsA is not clear, which needs further study.

WHAT IS NEW AND CONCLUSION

CRP concentration was identified as a novel marker associated with CsA pharmacokinetics, which should be considered when determining the appropriate dosage of CsA in allo-HSCT recipients.

The first study in pediatric: Population pharmacokinetics of sirolimus and its application in Chinese children with immune cytopenia

The narrow therapeutic index and large inter-individual variability in sirolimus pharmacokinetics (PK) make therapeutic drug monitoring (TDM) necessary. Factors responsible for PK variability are not well understood, and published PK studies do not include pediatric patients with immune cytopenia. The objective of this study was to characterize the PK of sirolimus in pediatric patients with immune cytopenia and to develop a population PK model in Chinese children and evaluate its utility for dose individualization. A total of 27 children with either acquired or congenital immune cytopenia aged 8.16 ± 3.60 years (range: 1-15 years) were included. TDM data for sirolimus were collected. The population PK model of sirolimus was described using the nonlinear mixed-effects modeling (Phoenix NLME 1.3 software) approach. Covariate analysis was applied to select candidate factors associated with PK parameters. The final model was validated using bootstrap (1000 runs) and visual predictive check (VPC) method. A one-compartment model with first-order absorption and elimination was developed. The outcome parameters were as follows: apparent clearance (CL/F) 5.63 L/h, apparent distribution volume (V/F) 144.16 L. Inter-individual variabilities for CL/F and V/F were 3.53% and 7.27%, respectively. The intra-individual variability of proportional error model was 22.45%. The covariate test found that body weight and total bilirubin were strongly associated with clearance; however, we did not find the relevance between the covariate and volume of distribution of sirolimus. Personalized dosage regimens were provided based on Bayesian method. The oral dose should be adjusted according to weight and total bilirubin. This is the first study to describe a population PK model of sirolimusin pediatric patients with immune cytopenia. Population pharmacokinetic (PPK) model-based dose individualization of sirolimus and the design of future clinical studies in children will be facilitated by the developed model in this study.

Multicenter-Based Population Pharmacokinetic Analysis of Ciclosporin in Hematopoietic Stem Cell Transplantation Patients

PURPOSE

To explore the contribution of physiological characteristics to variability in ciclosporin pharmacokinetics in hematopoietic stem cell transplantation patients.

METHODS

Clinical data from 563 patients were collected from centers in three regions. Ciclosporin concentrations were measured using immunoassays. The patients' demographics, hematological and biological indicators, coadministered drugs, region, and disease diagnosis were recorded from medical records. Data analysis was performed using NONMEM based on a one-compartment model to describe the pharmacokinetics of ciclosporin. The reliability and stability of the final model were evaluated using bootstrap resampling, goodness-of-fit plots, and prediction-corrected visual predictive checks.

RESULTS

The population estimate of the clearance (CL) was 30.4 L/h, the volume of distribution (V) was 874.0 L and the bioavailability (F) was 81.1%. The between-subject variability in these parameters was 26.3, 68.0, and 110.8%, respectively. Coadministration of fluconazole, itraconazole, or voriconazole decreased CL by 17.6%, 28.4%, and 29.2%, respectively. Females' CL increased by approximately 12.0%. In addition, CL and V decreased with hematocrit, total protein, and uric acid increase, and CL also decreased with age and aspartate aminotransferase increase. However, CL increased with creatinine clearance increase.

CONCLUSIONS

A multicenter-based population pharmacokinetic model of ciclosporin was established. The pharmacokinetics of ciclosporin exhibited discrepancies among different regions.

Population pharmacokinetics of cyclosporine in Chinese children receiving hematopoietic stem cell transplantation

Cyclosporine (CsA) is characterized by a narrow therapeutic window and high interindividual pharmacokinetic variability, particularly in juvenile patients. The aims of this study were to build a population pharmacokinetic model of CsA in Chinese children with hematopathy who received allogeneic hematopoietic stem cell transplantation (allo-HSCT) and to identify covariates affecting CsA pharmacokinetics. A total of 86 Chinese children aged 8.4 ± 3.8 years (range 1.1–16.8 years) who received allo-HSCT were enrolled. Whole blood samples were collected before allo-HSCT. Genotyping was performed using an Agena MassARRAY system. A total of 1010 trough plasma concentration values of CsA and clinical data were collected. The population pharmacokinetic model of CsA was constructed using nonlinear mixed-effects modeling (NONMEM) software. The stability and performance of the final model were validated using bootstrapping and normalized prediction distribution errors. We showed that a one-compartment model with first-order elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL) and volume of distribution (V) were 42.3 L/h and 3100 L, respectively. Body weight, postoperative days, CYP3A4*1 G genotype, estimated glomerular filtration rate and coadministration of triazole antifungal drugs were identified as significant covariates for CL. Weight and postoperative days were significant covariates for the V of CsA. Our model can be adopted to optimize the CsA dosing regimen for Chinese children with hematopathy receiving allo-HSCT.

Pharmacokinetic tools for the dose adjustment of ciclosporin in haematopoietic stem cell transplant patients

AIMS

Ciclosporin A (CsA) is used in the prophylaxis and treatment of acute and chronic graft vs. host disease after haematopoietic stem cell (HSCT) transplantation. Our objective was to build and compare three independent Bayesian estimators of CsA area under the curve (AUC) using a limited sampling strategy (LSS), to assist in dose adjustment.

METHODS

The Bayesian estimators were developed using in parallel: two independent parametric modelling approaches (nonmem® and iterative two stage (ITS) Bayesian modelling) and the non-parametric adaptive grid method (Pmetrics®). Seventy-two full pharmacokinetic profiles (at pre-dose and 0.33, 0.66, 1, 2, 3, 4, 6, 8 and 12h after dosing) collected from 40 HSCT patients given CsA were used to build the pharmacokinetic models, while 15 other profiles (n = 7) were kept for validation. For each Bayesian estimator, AUCs estimated using the full profiles were compared with AUCs estimated using three samples.

RESULTS

The pharmacokinetic profiles were well fitted using a two compartment model with first order elimination, combined with a gamma function for the absorption phase with ITS and Pmetrics or an Erlang distribution with nonmem. The derived Bayesian estimators based on a C0-C1 h-C4 h sampling schedule (best LSS) accurately estimated CsA AUC(0,12 h) in the validation group (n = 15; nonmem: bias (mean ± SD)/RMSE 2.05% ± 13.31%/13.02%; ITS: 4.61% ± 10.56%/11.20%; Pmetrics: 0.30% ± 10.12%/10.47%). The dose chosen confronting the three results led to a pertinent dose proposal.

CONCLUSIONS

The developed Bayesian estimators were all able to predict ciclosporin AUC(0,12 h) in HSCT patients using only three blood with minimal bias and may be combined to increase the reliability of CsA dose adjustment in routine.

Population pharmacokinetics of cyclosporine in hematopoietic stem cell transplant patients: consideration of genetic polymorphisms

BACKGROUND

Cyclosporine (CsA), which is used for graft-versus-host disease prophylaxis in allogeneic hematopoietic stem cell transplant (allo-HSCT), has a narrow therapeutic range and large interindividual and intraindividual pharmacokinetic variability. Nevertheless, population pharmacokinetic (PopPK) studies of CsA in allo-HSCT are scarce.

OBJECTIVE

The goal of our study was to build a PopPK model of CsA in allo-HSCT in consideration of demographic, clinical, and genetic polymorphisms data.

METHODS

A total of 34 adult allo-HSCT patients who received CsA were enrolled prospectively. Demographic, clinical, and CYP3A5 *1/*3, CYP2C19 *1/*2/*3, ABCB1 3435C>T, 1236C>T, 2677G>T/A, ABCC2 -24C>T, 1249G>A, VDR Bsml, Apal polymorphisms data were collected. A PopPK modeling was conducted with NONMEM program.

RESULTS

A 1-compartment model with a 2-transit absorption compartment model was developed. After the stepwise covariate model building process, weight was incorporated into clearance (CL) as a power function model with the exponent value of 0.419. The final typical estimate of CL was 21.2 L/h; volume of distribution was 430 L; logit-transformed bioavailability was 1.49 (bioavailability: 81%); and transit compartment rate was 2.87/h. None of the genetic polymorphisms in CYP3A5, CYP2C19, ABCB1, ABCC2, and VDR were significant covariates in the pharmacokinetics of CsA.

CONCLUSIONS

In our study, it was observed that weight had a significant effect on CL. Genetic polymorphisms did not affect CsA pharmacokinetics. Prospective studies with a larger number of participants is needed to validate the results of this study.

Population pharmacokinetics and individualized dosage prediction of cyclosporine in allogeneic hematopoietic stem cell transplant patients

BACKGROUND

Cyclosporine (CsA), a potent immunosuppressive agent used to prevent rejection, is characterized by large individual variability. The purpose of this study was to explore the pharmacokinetic characteristics of CsA and establish a CsA population pharmacokinetic model that could be used for personalized therapy in allogeneic hematopoietic stem cell transplant (allo-HSCT) patients.

METHODS

Clinical data were obtained from 117 allo-HSCT patients. The data analysis was performed using NONMEM software. A first-order conditional estimation with interaction (FOCE-I) method within NONMEM was used to estimate the parameters. The covariates, including demographics, hematological indices, biochemical levels, concurrent drugs, and genetic polymorphisms of CYP3A4, CYP3A5, and ABCB1, were evaluated quantitatively. The stability of the final model was validated by a nonparametric bootstrap procedure.

RESULTS

A total of 1,571 observed concentrations were collected. A 1-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL), volume of distribution (V), and bioavailability were 29.6 L/hr, 605 L, and 0.619, respectively. The interindividual variability of these parameters was 20.4, 66.1, and 30.4%, respectively. The residual error was 31.4% and 23.7 ng/mL. The duration of CsA therapy, hematocrit, antifungal agent administration, triglycerides, and weight were identified as the main covariates that influenced CL, and hematocrit had a significant effect on V. The internal validation showed that the final model was stable and accurate.

CONCLUSIONS

This study established a population pharmacokinetic model of CsA in allo-HSCT patients that could provide the foundation for personalized use of CsA in the clinic.

Population pharmacokinetics of ciclosporin in Chinese children with aplastic anemia: effects of weight, renal function and stanozolol administration

AIM

To develop a population pharmacokinetic model for the immunosuppressant ciclosporin in Chinese children with aplastic anemia and to identify covariates influencing ciclosporin pharmacokinetics.

METHODS

A total of 102 children with either acquired or congenital aplastic anemia aged 8.8±3.6 years (range 0.9-17.6 years) were included. Therapeutic drug monitoring (TDM) data for ciclosporin were collected. The population pharmacokinetic model of ciclosporin was described using the nonlinear mixed-effects modeling (NONMEM) VI software. The final model was validated using bootstrap and normalized prediction distribution errors.

RESULTS

A one-compartment model with first-order absorption and elimination was developed. The estimated CL/F was 15.1, which was lower than those of children receiving stem cell or kidney transplant reported in the West (16.9-29.3). The weight normalized CL/F was 0.45 (range: 0.27-0.70) Lh(-1)·kg(-1). The covariate analysis identified body weight, serum creatinine and concomitant administration of the anabolic steroid stanozolol as individual factors influencing the CL/F of ciclosporin.

CONCLUSION

Our model could be used to optimize the ciclosporin dosing regimen in Chinese children with aplastic anemia.

Population pharmacokinetics of cyclosporine in transplant recipients

A number of classical pharmacokinetic studies have been conducted in transplant patients. However, they suffer from some limitations, for example, (1) the study design was limited to intense blood sampling in small groups of patients during a certain posttransplant period, (2) patient factors were evaluated one at a time to identify their association with the pharmacokinetic parameters, and (3) mean pharmacokinetic parameters often cannot be precisely estimated due to large intraindividual variability. Population pharmacokinetics provides a potential means of addressing these limitations and is a powerful tool to evaluate the magnitude and consistency of drug exposure. Population pharmacokinetic studies of cyclosporine focused solely on developing limited sampling strategies and Bayesian estimators to estimate drug exposure, have been summarized before, and are, therefore, not a subject of this review. The major focus of this review is to describe factors (demographic factors, hepatic and gastrointestinal functions, drug-drug interactions, genetic polymorphisms of drug metabolizing enzymes and transporters) that have been identified to contribute to the large portion of observed variability in the pharmacokinetics of cyclosporine in transplant patients. This review summarizes and interprets the conclusions as well as the nonlinear mixed-effects modeling methodologies used in such studies. A highly diversified collection of structural models, variability models, and covariate submodels have been evaluated and validated using internal or external validation methods. This review also highlights areas where additional research is warranted to improve the models since a portion of model variability still remains unexplained.