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

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.

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.

Correlation between Cyclosporine Blood Levels and Area under Blood Concentration Time Curve in Iraqi Bone Marrow Transplant Patients Treated with Neoral® Oral Solution

Cyclosporine is a potent immunosuppressive drug. It has a narrow therapeutic index, and therefore the measurement of cyclosporine’s blood concentration is essential to obtain optimal therapy. Measurement of the area under the blood concentration-time curve (AUC) is reflective of total drug exposure. However, for organ transplant patients, the measurement of AUC involves many problems and difficulties. Thus, it is more clinically acceptable to use a single blood sample as a surrogate index of total drug exposure. Fifty-four adults bone marrow transplant Iraqi patients were given cyclosporine every 12 h as prophylaxis using Neoral® oral solution. Steady-state blood concentrations were monitored for each patient at zero time and then at 1, 2, 3, 4, 6, 8, 10, and at 12 h post-dosing. Cyclosporine blood levels were determined by using AXSYM automated immuno-analyzer which is a fluorescence polarization immunoassay (FPIA). The present investigation demonstrated the best correlation between C2 and the corresponding AUC0–4h and AUC0–12h compared to other concentrations. After two months of cyclosporine therapy, no unexpected biochemical changes and adverse effects were registered. It is concluded from this study that a single blood sample obtained at 2 h post-dosing (C2) and possibly at 3 h post dosing (C3) are ideal surrogate indexes for reflecting total drug exposure, and therefore may be used in clinical practice for predicting therapeutic and toxic effects of cyclosporine.

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.

Immunosuppression for in vivo research: state-of-the-art protocols and experimental approaches

Almost every experimental treatment strategy using non-autologous cell, tissue or organ transplantation is tested in small and large animal models before clinical translation. Because these strategies require immunosuppression in most cases, immunosuppressive protocols are a key element in transplantation experiments. However, standard immunosuppressive protocols are often applied without detailed knowledge regarding their efficacy within the particular experimental setting and in the chosen model species. Optimization of such protocols is pertinent to the translation of experimental results to human patients and thus warrants further investigation. This review summarizes current knowledge regarding immunosuppressive drug classes as well as their dosages and application regimens with consideration of species-specific drug metabolization and side effects. It also summarizes contemporary knowledge of novel immunomodulatory strategies, such as the use of mesenchymal stem cells or antibodies. Thus, this review is intended to serve as a state-of-the-art compendium for researchers to refine applied experimental immunosuppression and immunomodulation strategies to enhance the predictive value of preclinical transplantation studies.

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.