Develops a model to predict fludarabine exposure in pediatric HSCT, indicating personalized dosing could improve outcomes.
Fludarabine (Flu), administered as a prodrug Flu monophosphate, is a lymphodepleting agent used prior to hematopoietic stem cell transplantation (HSCT) which exhibits substantial pharmacokinetics (PK) variability, contributing to suboptimal outcomes. This study developed and validated a physiologically based pharmacokinetic (PBPK) model using literature‐based data and a middle‐out approach for Flu and its two main metabolites in adults and children, and evaluated its performance to predict individual Flu exposures in 28 pediatric HSCT patients using a virtual twin (VT) approach using PK‐Sim software. Different informed models with individual demographic and biological characteristics were assessed by comparing predicted and observed plasma exposures (AUC 0➔24h ) via fold error metrics and regression analyses. The PBPK model accurately reproduced observed Flu and metabolites concentrations in both adults and children. In the VT cohort, informing the model with plasma protein scaling factor and nuclear GFR improved drug exposure predictions in total (mean fold error (MFE) = 0.91) and unbound (MFE = 0.88) compartments with minimal bias in both Deming and Bland–Altman analyses. This model provided superior agreement between observed and predicted exposures, achieving improved agreement across statistical and regression approaches compared to the model with estimated GFR. PBPK‐based VT modeling enables accurate, individualized prediction of Flu PK in pediatric HSCT patients. These results support the implementation of model‐informed precision dosing to achieve personalized pediatric dosing of Flu in HSCT.
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Mseddi et al. (2026) studied this question.
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