Precision Dosing of Tacrolimus in Liver Transplantation: Integrating Donor-Recipient CYP3A5 Pharmacogenomics and Drug Interactions.

IF 2.8 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Virunya Komenkul, Prawat Chantharit, Piyawat Komolmit, Bunthoon Nonthasoot, Athaya Vorasittha, Anapat Sanpavat, Sirinporn Suksawatamnuay, Chandramouli Radhakrishnan, Thitima Wattanavijitkul
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Abstract

Tacrolimus dosing in liver transplantation is complicated by a narrow therapeutic index and high CYP3A5 genetic variability. While saturable Michaelis-Menten kinetics can explain nonlinearities, identifying saturable parameters from routine clinical data remains challenging. This study aimed to determine the optimal structural model and develop a precision dosing algorithm. A population pharmacokinetic analysis was conducted in 114 patients, yielding 1989 observations. CYP3A5 genotypes were determined for both recipients and donors. Using Phoenix NLME, we rigorously compared linear versus Michaelis-Menten elimination structures. Stepwise covariate modeling was conducted to quantify the impact of genetic, physiological, and pharmacological factors, followed by Monte Carlo simulations to optimize dosing. A conventional two-compartment model adequately described the data without requiring a Michaelis-Menten structure. The combined CYP3A5 genotype exhibited a distinct stepwise reduction in apparent clearance from the homozygous expressor to the non-expressor group. Fluconazole emerged as a major inhibitor, reducing clearance by 33%, whereas prednisolone showed modest induction. Hemoglobin displayed a significant inverse relationship with clearance. Crucially, incorporating the daily dose as a covariate on clearance effectively captured the apparent nonlinear disposition. Simulations confirmed that fluconazole-treated patients require substantially lower doses (1.5-3.0 mg every 12 h) compared with fluconazole-free patients (2.5-7.0 mg every 12 h). A dose-dependent two-compartment model offers a basis for model-informed dose selection, addressing reported nonlinearities through physiological covariates. We provide a model-informed dosing algorithm that accounts for combined recipient/donor genetics and drug interactions, which may improve target attainment in liver transplant populations.

他克莫司在肝移植中的精确剂量:整合供受体CYP3A5药物基因组学和药物相互作用。
他克莫司在肝移植中的应用存在治疗指数窄和CYP3A5遗传变异性高的问题。虽然饱和Michaelis-Menten动力学可以解释非线性,但从常规临床数据中确定饱和参数仍然具有挑战性。本研究旨在确定最优的结构模型,并开发精确的加药算法。对114例患者进行了群体药代动力学分析,得出1989项观察结果。测定受体和供体的CYP3A5基因型。使用Phoenix NLME,我们严格比较了线性和Michaelis-Menten消去结构。采用逐步协变量建模来量化遗传、生理和药理学因素的影响,然后通过蒙特卡罗模拟来优化给药。传统的双室模型不需要Michaelis-Menten结构就能充分描述数据。联合CYP3A5基因型表现出明显的逐步减少的表观清除率,从纯合表达到非表达组。氟康唑是主要的抑制剂,可使清除率降低33%,而强的松龙则表现出适度的诱导作用。血红蛋白与清除率呈显著负相关。至关重要的是,将日剂量作为清除率的协变量有效地捕获了明显的非线性配置。模拟证实,与不使用氟康唑的患者(每12小时2.5-7.0 mg)相比,使用氟康唑治疗的患者需要的剂量(每12小时1.5-3.0 mg)要低得多。剂量相关的两室模型为模型知情剂量选择提供了基础,解决了通过生理协变量报告的非线性问题。我们提供了一个模型知情的给药算法,该算法考虑了受体/供体遗传学和药物相互作用,这可能会提高肝移植人群的目标实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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