Abstract

Given a high pharmacokinetic inter-individual variability and a low exposure target achievement, ganciclovir (GCV) therapeutic drug monitoring is sometimes used in children. We aimed to develop and validate Bayesian estimators based on limited sampling strategies for the estimation of GCV area under the concentration-time curve from 0 to 24 h in pediatric transplant recipients treated with valganciclovir (VGCV) or GCV. Solid organ transplant or stem-cell transplant recipients who received GCV or VGCV and had available GCV concentrations per standard of care were retrospectively included in this study for pharmacokinetic modeling and development of Bayesian estimators using the iterative two-stage Bayesian method. Validation datasets included additional child recipients of a solid organ transplant or stem-cell transplant, and child recipients of a kidney or liver transplant enrolled in a previous study. Various combinations of three or two sampling times, applicable in clinical practice, were assessed based on the relative mean bias, standard deviation, and the root mean square error in a development dataset and three independent validation datasets. In the development dataset, the mean bias/standard deviation/root mean square error for the 1h/2h/3h and 1h/3h limited sampling strategies were - 1.4%/9.3%/9.1% and - 3.5%/12.2%/12.3%, respectively for GCV, while for VGCV, the mean bias/standard deviation/root mean square error for the 1h/2h/6h and 1h/6h limited sampling strategies were 0.7%/13.5%/13.3% and - 0.1%/12.1%/11.8%, respectively. In the independent validation datasets, seven (13%) and five (14%) children would have had misclassifications of their exposure using these Bayesian estimators and limited sampling strategies for VGCV and GCV, respectively. Three plasma samples collected at 1h/2h/3h and 1h/2h/6h post-dose for GCV and VGCV respectively, are sufficient to accurately determine GCV area under the concentration-time curve from 0 to 24 h for pharmacokinetic-enhanced therapeutic drug monitoring.

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