Determining the Optimal Dosing of Methyldopa in Pregnancy-Induced Hypertension Using PBPK-PD Modeling.

IF 4.6 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Clinical Pharmacokinetics Pub Date : 2025-08-01 Epub Date: 2025-06-14 DOI:10.1007/s40262-025-01523-2
Xinyang Liu, Wei Wang, Jinying Zhu, Jingsi Chen, Xiaoyi Wang, Dunjin Chen, Defang Ouyang
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引用次数: 0

Abstract

Background: Pregnancy-induced hypertension is a significant risk factor for adverse maternal and fetal outcomes, with methyldopa being a commonly prescribed antihypertensive for its safety profile. However, the physiological changes during pregnancy may alter the pharmacokinetics (PK) and pharmacodynamics (PD) of methyldopa, complicating the establishment of optimal dosing regimens.

Objective: This study aims to develop and validate a pregnancy-specific physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) model for methyldopa to optimize dosing strategies and support individualized treatment plans for managing pregnancy-induced hypertension effectively.

Methods: The PBPK-PD model for methyldopa was developed using PK-Sim, MoBi, and MATLAB software, incorporating pregnancy-specific physiological parameters from the literature. The development process involved: (a) constructing and validating a PBPK model for non-pregnant individuals based on intravenous and oral administration, including renal clearance, serum clearance, and enzyme clearance; (b) extending the model to a pregnant PBPK model and validating it for oral administration; (c) constructing a PK/PD model using the maximum effect model; and (d) integrating the PBPK and PK/PD models to form a unified PBPK-PD model. This model was then used to simulate mean arterial pressure (MAP) responses across different stages of pregnancy. Finally, the optimal dosing regimen was calculated.

Results: The model verification results show a good fit, indicating that the parameters are appropriate. The pregnancy model indicated no significant change in phenol sulfotransferase (PST) activity during pregnancy. The physiologically based pharmacokinetic-pharmacodynamic simulations across different stages of pregnancy show fluctuations in both PK and PD; however, these variations are not particularly significant. Ultimately, the results indicate that 500 mg is the optimal dosing regimen for patients with MAP ≤ 130 mmHg. For MAP > 130 mmHg, additional antihypertensive medications are recommended. Due to its delayed onset, methyldopa should be combined with other antihypertensives during the first 48 hours.

Conclusion: The PBPK-PD model developed in this study provides a valuable tool for optimizing methyldopa therapy, supporting personalized treatment strategies, and improving blood pressure management and maternal and fetal health outcomes in pregnancy-induced hypertension.

利用PBPK-PD模型确定甲基多巴在妊娠高血压中的最佳剂量。
背景:妊娠性高血压是孕产妇和胎儿不良结局的重要危险因素,甲基多巴因其安全性而成为常用的抗高血压药物。然而,怀孕期间的生理变化可能会改变甲基多巴的药代动力学(PK)和药效学(PD),使最佳给药方案的建立复杂化。目的:本研究旨在建立和验证甲基多巴妊娠特异性生理药代动力学(PBPK-PD)模型,以优化给药策略,并支持有效管理妊娠高血压的个体化治疗方案。方法:采用PK-Sim、MoBi和MATLAB软件,结合文献中妊娠特异性生理参数,建立甲基多巴PBPK-PD模型。开发过程包括:(a)构建和验证基于静脉和口服给药的非怀孕个体PBPK模型,包括肾脏清除率、血清清除率和酶清除率;(b)将该模型扩展到妊娠PBPK模型,并验证其口服给药;(c)利用最大效应模型构建PK/PD模型;(d)整合PBPK和PK/PD模型,形成统一的PBPK-PD模型。然后使用该模型模拟怀孕不同阶段的平均动脉压(MAP)反应。最后计算出最佳给药方案。结果:模型验证结果拟合良好,说明参数合理。妊娠模型显示苯酚磺基转移酶(PST)活性在妊娠期间无明显变化。基于生理的药代动力学-药效学模拟在不同的妊娠阶段显示PK和PD的波动;然而,这些变化并不是特别显著。最终,结果表明500 mg是MAP≤130 mmHg患者的最佳给药方案。对于MAP值为130 mmHg的患者,建议服用额外的抗高血压药物。由于甲基多巴起效较晚,应在最初48小时内与其他抗高血压药物联合使用。结论:本研究建立的PBPK-PD模型为优化甲基多巴治疗、支持个性化治疗策略、改善妊娠高血压患者的血压管理和母婴健康结局提供了有价值的工具。
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
8.80
自引率
4.40%
发文量
86
审稿时长
6-12 weeks
期刊介绍: Clinical Pharmacokinetics promotes the continuing development of clinical pharmacokinetics and pharmacodynamics for the improvement of drug therapy, and for furthering postgraduate education in clinical pharmacology and therapeutics. Pharmacokinetics, the study of drug disposition in the body, is an integral part of drug development and rational use. Knowledge and application of pharmacokinetic principles leads to accelerated drug development, cost effective drug use and a reduced frequency of adverse effects and drug interactions.
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