Population Pharmacokinetic Model Development of Tacrolimus in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplantation

被引:7
作者
Brooks, Jordan T. [1 ]
Keizer, Ron J. [2 ]
Long-Boyle, Janel R. [1 ,3 ]
Kharbanda, Sandhya [3 ]
Dvorak, Christopher C. [3 ]
Friend, Brian D. [4 ]
机构
[1] Univ Calif San Francisco, Sch Pharm, Dept Clin Pharm, San Francisco, CA USA
[2] Insight RX Inc, San Francisco, CA USA
[3] Univ Calif San Francisco, Dept Pediat, San Francisco, CA USA
[4] Baylor Coll Med, Dept Pediat, Ctr Cell & Gene Therapy, Houston, TX 77030 USA
关键词
population pharmacokinetic model; pediatrics; tacrolimus; hematopoietic stem cell transplantation; therapeutic drug monitoring; MARROW TRANSPLANTS; PHARMACOGENETICS; RECIPIENTS;
D O I
10.3389/fphar.2021.750672
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Background: With a notably narrow therapeutic window and wide intra- and interindividual pharmacokinetic (PK) variability, initial weight-based dosing along with routine therapeutic drug monitoring of tacrolimus are employed to optimize its clinical utilization. Both supratherapeutic and subtherapeutic tacrolimus concentrations can result in poor outcomes, thus tacrolimus PK variability is particularly important to consider in the pediatric population given the differences in absorption, distribution, metabolism, and excretion among children of various sizes and at different stages of development. The primary goals of the current study were to develop a population PK (PopPK) model for tacrolimus IV continuous infusion in the pediatric and young adult hematopoietic cell transplant (HCT) population and implement the PopPK model in a clinically available Bayesian forecasting tool.Methods: A retrospective chart review was conducted of 111 pediatric and young adult patients who received IV tacrolimus by continuous infusion early in the post-transplant period during HCT from February 2016 to July 2020 at our institution. PopPK model building was performed in NONMEM. The PopPK model building process included identifying structural and random effects models that best fit the data and then identifying which patient-specific covariates (if any) further improved model fit.Results: A total of 1,648 tacrolimus plasma steady-state trough concentrations were included in the PopPK modeling process. A 2-compartment structural model best fit the data. Allometrically-scaled weight was a covariate that improved estimation of both clearance and volume of distribution. Overall, model predictions only showed moderate bias, with minor under-prediction at lower concentrations and minor over-prediction at higher predicted concentrations. The model was implemented in a Bayesian dosing tool and made available at the point-of-care.Discussion: Novel therapeutic drug monitoring strategies for tacrolimus within the pediatric and young adult HCT population are necessary to reduce toxicity and improve efficacy in clinical practice. The model developed presents clinical utility in optimizing the use of tacrolimus by enabling model-guided, individualized dosing of IV, continuous tacrolimus via a Bayesian forecasting platform.
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页数:8
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