ArticleClinical pharmacokinetics2021
Thoroughly Validated Bayesian Estimator and Limited Sampling Strategy for Dose Individualization of Ganciclovir and Valganciclovir in Pediatric Transplant Recipients.
Article in Clinical pharmacokinetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Pharmacokinetic/Pharmacodynamic Modelling and Monte Carlo Simulations to Predict Cytomegalovirus Viral Load in Pediatric Transplant Recipients Treated with (val)Ganciclovir.Clinical pharmacokinetics · 2025Article
- Application of machine-learning models to predict the ganciclovir and valganciclovir exposure in children using a limited sampling strategy.Antimicrobial agents and chemotherapy · 2024Article
- Limited Sampling Strategies to Predict Ganciclovir Exposure after Valganciclovir Administration and to Reduce Monitoring Constraints in Renal Transplant Children.Antimicrobial agents and chemotherapy · 2023Article
- A Hybrid Algorithm Combining Population Pharmacokinetic and Machine Learning for Isavuconazole Exposure Prediction.Pharmaceutical research · 2023Article
- Population Pharmacokinetics of Ganciclovir in Allogeneic Hematopoietic Stem Cell Transplant Patients.Antimicrobial agents and chemotherapy · 2023Observational
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveGiven 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.
methodsSolid 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.
resultsIn the development dataset, the mean bias/standard deviation/root mean square error for the 1 h/2 h/3 h and 1 h/3 h 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 1 h/2 h/6 h and 1 h/6 h 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.
conclusionsThree plasma samples collected at 1 h/2 h/3 h and 1 h/2 h/6 h 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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