Bayesian approach for the estimation of cyclosporine area under the curve using limited sampling strategies in pediatric hematopoietic stem cell transplantation

Personalized Tuberculosis Treatment Through Model-Informed Dosing of Rifampicin

BACKGROUND AND OBJECTIVE

This study proposes a model-informed approach for therapeutic drug monitoring (TDM) of rifampicin to improve tuberculosis (TB) treatment.

METHODS

Two datasets from pulmonary TB patients were used: a pharmacokinetic study (34 patients, 373 samples), and TDM data (96 patients, 391 samples) collected at Radboud University Medical Center, The Netherlands. Nine suitable population pharmacokinetic models of rifampicin were identified in the literature and evaluated on the datasets. A model developed by Svensson et al. was found to be the most suitable based on graphical goodness of fit, residual diagnostics, and predictive performance. Prediction of individual area under the concentration-time curve from time zero to 24 h (AUC₂₄) and maximum concentration (C_max) employing various sampling strategies was compared with a previously established linear regression TDM strategy, using sampling at 2, 4, and 6 h, in terms of bias and precision (mean error [ME] and root mean square error [RMSE]).

RESULTS

A sampling strategy using 2- and 4-h blood collection was selected to be the most suitable. The bias and precision of the two strategies were comparable, except that the linear regression strategy was more biased in prediction of the AUC₂₄ than the model-informed approach (ME of 9.9% and 1.5%, respectively). A comparison of resulting dose advice, using predictions on a simulated dataset, showed no significant difference in sensitivity or specificity between the two methods. The model was successfully implemented in the InsightRX precision dosing platform.

CONCLUSION

Blood sampling at 2 and 4 h, combined with model-based prediction, can be used instead of the currently used linear regression strategy, shortening the sampling by 2 h and one sampling point without performance loss while simultaneously offering flexibility in sampling times.

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.

Development of a Limited Sampling Strategy for the Estimation of Exposure to High-Dose Etoposide After Intravenous Infusion in Pediatric Patients

BACKGROUND

Etoposide (VP-16), a podophyllotoxin derivative, is used in conditioning regimens before allogeneic hematopoietic stem cell transplantation in children with acute lymphoblastic leukemia. The aim of this study was to develop a limited sampling strategy (LSS) suitable for the prediction of exposure to VP-16 defined as area under time-concentration curve (AUC).

METHODS

The study included 28 pediatric patients with acute lymphoblastic leukemia, who were administered a 4-hour infusion of 60 mg/kg VP-16. VP-16 concentrations were determined in samples collected 4-124 hours after the beginning of infusion. On obtaining the pharmacokinetic (PK) profiles, a population PK model was developed in NONMEM (ICON Development Solutions, Hanover, MD) with first-order conditional estimation with interaction algorithm. LSSs were chosen by means of a multivariate regression analysis and cross-validated with a leave-one-out approach. Predictive performance of LSSs was assessed by calculating relative prediction error (PE), mean PE, mean absolute PE, and root mean squared PE for model-predicted and observed AUC.

RESULTS

VP-16 PKs was best described by a 2-compartment first-order model, and a large variability in the PK parameters was observed. A 3-sample strategy allowed the estimation of VP-16 with highest accuracy and precision (mean relative PE = 0.18%, 95% confidence interval, 1.73%-2.09%; mean absolute relative PE = 3.47%, 95% confidence interval, 2.28%-4.66%; root mean squared PE = 4.43%). The final equation was AUC = 6.85 × C6 h + 3.88 × C12 h + 46.11 × C28 h + 282.0 (adjusted R = 0.9540).

CONCLUSIONS

In conclusion, developed LSS allows accurate and precise estimation of VP-16 AUC and might be useful for therapeutic drug monitoring.