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Optimization of busulfan dosing regimen in pediatric patients using population pharmacokinetic model incorporating GST polymorphisms
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  • Jin-jie Yuan,
  • Ning Sun,
  • Xin-ying Feng,
  • Huan He,
  • Guang-hua Zhu,
  • Li-Bo Zhao
Jin-jie Yuan

Corresponding Author:[email protected]

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Xin-ying Feng
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Huan He
Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 10045, China
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Guang-hua Zhu
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Li-Bo Zhao
Peking University
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Abstract

Aim: The aim of this study was to develop a population pharmacokinetic (PPK) model in Chinese children for intravenous busulfan, and to develop a novel busulfan dosing regimen to support better area under the concentration-time curve (AUC) targeting. Methods: We collected busulfan concentration-time samples from 69 children who received intravenous busulfan prior to allogeneic hematopoietic stem cell transplantation (allo-HSCT). A population pharmacokinetic model for busulfan was developed by nonlinear mixed effect modelling and was validated by an external dataset (n=14). A novel busulfan dosing regimen was developed through simulation on 1000 patients. Limited Sampling Strategy (LSS) was established by the Bayesian forecasting. Absolute Prediction Error (APE), Mean Absolute Prediction Error (MAPE) and relative Root Mean Squared Error (rRMSE) were calculated to evaluate predictive accuracy. Results: A one-compartment model with first-order elimination best described the data. GSTA1 genotypes, BSA and AST were found to be significant covariates of Bu clearance, and BSA had remarkable impact of the volume. Moreover, recommended dose regimens for children with different GSTA1 genotypes and BSA were developed with a perfect AUC targeting. A two-point LSS, two hours and four hours after dosing, behaved well with acceptable prediction precision. Conclusion: This study developed a PPK model for busulfan that firstly incorporated GSTA1 genotypes in an Asian pediatric population. We recommend a BSA-based dosing for personalizing busulfan therapy in pediatric population. Additionally, an optimal LSS (C2h and C4h) provides convenience for therapeutic drug monitoring (TDM) in the future.