Population Pharmacokinetics and Pharmacodynamics with Enterohepatic Recirculation of Co-Medication of Rosuvastatin and Ezetimibe.

IF 4.7 2区 医学 Q1 CHEMISTRY, MEDICINAL
Drug Design, Development and Therapy Pub Date : 2025-06-04 eCollection Date: 2025-01-01 DOI:10.2147/DDDT.S522863
Hyungmi An, Dongseong Shin
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引用次数: 0

Abstract

Objective: Combination therapy with rosuvastatin and ezetimibe is generally administered to patients with high cardiovascular risk. The objective of this study was to develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the interaction between rosuvastatin and ezetimibe that incorporates enterohepatic recirculation (EHC).

Methods: Concentration-time data were obtained from a two-part, open-label, multiple-dose crossover, drug interaction study. In total, 50 healthy male subjects received both monotherapy and co-therapy (Part A: rosuvastatin and co-therapy; Part B: ezetimibe and co-therapy). Rosuvastatin (20 mg) or ezetimibe (10 mg) were administered once daily for 7 days as monotherapy or co-therapy. Plasma concentrations were measured for PK analysis until 72 h post-dose at steady state. The changes in low-density lipoprotein cholesterol (LDL-C) levels from baseline to steady state at 24 h after the last administration were measured. A population PK/PD model incorporating EHC was developed using Monolix 2024R1. Covariate effects were explored, and the final model was evaluated through goodness-of-fit diagnostics and visual predictive checks. Model-based simulations were conducted to compare the LDL-C lowering effects of monotherapy and co-therapy.

Results: A population PK/PD model was established using a two-compartment model for rosuvastatin and a four-compartment model for ezetimibe incorporating EHC via intermittent gallbladder emptying. No significant PK interaction was observed. An indirect response PD model reflected the independent LDL-C lowering effects of both drugs. Simulations showed LDL-C reductions of -51.0% (rosuvastatin), -25.3% (ezetimibe), and -60.7% (co-therapy), supporting the additive efficacy of co-therapy. EHC increased the exposure of total ezetimibe with limited LDL-C lowering effects.

Conclusion: The overall PK interaction between rosuvastatin and total ezetimibe was not significant. The developed PK/PD model incorporating EHC successfully described the independent LDL-C lowering effects. These findings support the additive benefit of co-therapy of rosuvastatin and ezetimibe and may guide future research toward personalized lipid-lowering strategies.

瑞舒伐他汀与依折替米贝合用的人群药代动力学及肠肝再循环的药效学。
目的:瑞舒伐他汀与依折替米贝联合治疗一般用于心血管高危患者。本研究的目的是建立瑞舒伐他汀和依折替米布结合肠肝再循环(EHC)相互作用的群体药代动力学/药效学(PK/PD)模型。方法:浓度-时间数据来自两部分、开放标签、多剂量交叉、药物相互作用研究。总共有50名健康男性受试者接受了单药和联合治疗(A部分:瑞舒伐他汀和联合治疗;B部分:依折麦布和联合治疗)。瑞舒伐他汀(20mg)或依zetimibe (10mg)作为单药或联合治疗,每天1次,连续7天。在稳定状态下测量血浆浓度以进行PK分析,直至给药后72小时。测量末次给药后24 h低密度脂蛋白胆固醇(LDL-C)水平从基线到稳定状态的变化。利用Monolix 2024R1建立了包含EHC的种群PK/PD模型。探索协变量效应,并通过拟合优度诊断和视觉预测检查评估最终模型。进行基于模型的模拟,比较单一治疗和联合治疗的LDL-C降低效果。结果:采用瑞舒伐他汀组2室模型和依折替米贝组4室模型,通过间歇性胆囊排空建立了人群PK/PD模型。未观察到显著的PK相互作用。间接反应PD模型反映了两种药物的独立LDL-C降低作用。模拟显示LDL-C降低-51.0%(瑞舒伐他汀),-25.3%(依泽替米布)和-60.7%(联合治疗),支持联合治疗的附加疗效。EHC增加了总依折麦布的暴露,但降低LDL-C的效果有限。结论:瑞舒伐他汀与总依折替米贝的总体PK相互作用不显著。建立的结合EHC的PK/PD模型成功地描述了独立的LDL-C降低作用。这些发现支持瑞舒伐他汀和依折替米贝联合治疗的附加益处,并可能指导未来个性化降脂策略的研究。
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来源期刊
Drug Design, Development and Therapy
Drug Design, Development and Therapy CHEMISTRY, MEDICINAL-PHARMACOLOGY & PHARMACY
CiteScore
9.00
自引率
0.00%
发文量
382
审稿时长
>12 weeks
期刊介绍: Drug Design, Development and Therapy is an international, peer-reviewed, open access journal that spans the spectrum of drug design, discovery and development through to clinical applications. The journal is characterized by the rapid reporting of high-quality original research, reviews, expert opinions, commentary and clinical studies in all therapeutic areas. Specific topics covered by the journal include: Drug target identification and validation Phenotypic screening and target deconvolution Biochemical analyses of drug targets and their pathways New methods or relevant applications in molecular/drug design and computer-aided drug discovery* Design, synthesis, and biological evaluation of novel biologically active compounds (including diagnostics or chemical probes) Structural or molecular biological studies elucidating molecular recognition processes Fragment-based drug discovery Pharmaceutical/red biotechnology Isolation, structural characterization, (bio)synthesis, bioengineering and pharmacological evaluation of natural products** Distribution, pharmacokinetics and metabolic transformations of drugs or biologically active compounds in drug development Drug delivery and formulation (design and characterization of dosage forms, release mechanisms and in vivo testing) Preclinical development studies Translational animal models Mechanisms of action and signalling pathways Toxicology Gene therapy, cell therapy and immunotherapy Personalized medicine and pharmacogenomics Clinical drug evaluation Patient safety and sustained use of medicines.
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