综述

成人肝移植术后他克莫司个体化治疗的研究进展

  • 蒋艳 ,
  • 王国徽 ,
  • 宋沧桑 ,
  • 张函舒 ,
  • 李兴德
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  • 1.昆明医科大学附属甘美医院药学部 (云南 昆明 650224 )
    2.昆明医科大学研究生院 (云南 昆明 650500 )

收稿日期: 2025-07-21

  修回日期: 2025-09-16

  录用日期: 2025-09-17

  网络出版日期: 2026-04-13

基金资助

云南省科技厅科技计划(昆医联合专项)(202301AY070001-112);昆明市卫生科技人才培养项目(编号:2022-SW(带头)-32;2023-SW(领军)-04;云南省卫生健康委员会医学领军人才培养项目(L-2018012);昆明市临床药学重点专科建设项目

Research advances in personalized tacrolimus therapy for adult liver transplant recipients

  • Yan JIANG ,
  • Guohui WANG ,
  • Cangsang SONG ,
  • Hanshu ZHANG ,
  • Xingde LI
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  • 1.Department of Pharmacy,Ganmei Hospital Affiliated to Kunming Medical University,Kunming 650224,Yunnan,China
    2.Graduate School of Kunming Medical University,Kunming 650500,Yunnan,China

Received date: 2025-07-21

  Revised date: 2025-09-16

  Accepted date: 2025-09-17

  Online published: 2026-04-13

摘要

他克莫司(TAC)是肝移植(LT)术后的核心免疫抑制药物,但其治疗窗狭窄,且药代动力学存在显著的个体间及个体内变异,导致血药浓度易偏离目标范围,精准给药难度大。近年来,随着治疗药物监测(TDM)的广泛应用,基于TAC血药浓度的个体化治疗策略研究取得了重要进展。本文系统综述成人肝移植受者TAC个体化给药的最新研究,重点探讨了药物基因组学、群体药代动力学(PPK)和机器学习(ML)等方法在临床中的应用价值与发展现状,并对比分析不同建模策略的优势与局限。研究表明,基于模型的精准给药(MIPD)工具不仅可显著提升血药浓度预测准确性,还能生成个体化给药方案,有助于优化肝移植患者的治疗效果与改善长期预后。

本文引用格式

蒋艳 , 王国徽 , 宋沧桑 , 张函舒 , 李兴德 . 成人肝移植术后他克莫司个体化治疗的研究进展[J]. 实用医学杂志, 2026 , 42(7) : 1294 -1300 . DOI: 10.3969/j.issn.1006-5725.2026.07.024

Abstract

Tacrolimus(TAC) serves as a cornerstone immunosuppressive therapy following liver transplantation(LT). However, its narrow therapeutic window, combined with significant inter- and intra-individual pharmacokinetic variability, often leads to blood concentrations deviating from target range, posing a major challenge for precision dosing. In recent years, with the widespread adoption of therapeutic drug monitoring(TDM), research on individualized dosing strategies based on TAC blood concentrations has achieved substantial progress. This article provides a systematic review of the latest advances in personalized TAC dosing for adult LT recipients, with a focus on the clinical application value and current status of pharmacogenomics, population pharmacokinetics(PPK), and machine learning(ML). It further compares and summarizes the strengths and limitations of different modeling strategies. Studies demonstrate that model-informed precision dosing(MIPD) tools can not only significantly enhance the accuracy of blood concentration predictions but also generate patient-tailored dosing regimens, thereby contributing to the optimization of therapeutic outcomes and long-term prognosis in LT patients.

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