Physiologically Based Pharmacokinetic Modeling to Assess Ritonavir-Digoxin Interactions and Recommendations for Co-Administration Regimens.

IF 3.5 3区 医学 Q2 CHEMISTRY, MULTIDISCIPLINARY Pharmaceutical Research Pub Date : 2024-11-18 DOI:10.1007/s11095-024-03789-w
Youjun Chen, Wenxin Shao, Xingwen Wang, Kuo Geng, Wenhui Wang, Yiming Li, Zhiwei Liu, Haitang Xie
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Abstract

Background: Digoxin is a commonly used cardiac glycoside drug in clinical practice, primarily transported by P-glycoprotein (P-gp) and susceptible to the influence of P-gp inhibitors/inducers. Concurrent administration of ritonavir and digoxin may significantly increase the plasma concentration of digoxin. Due to the narrow therapeutic window of digoxin, combined use may lead to severe toxic effects.

Purpose: Utilize a Physiology-Based Pharmacokinetic (PBPK) model to simulate and predict the impact of the interaction between ritonavir and digoxin on the pharmacokinetics (PK) of digoxin, and provide recommendations for the combined medication regimen.

Methods: Using PK-Sim®, develop individual PBPK models for ritonavir and digoxin. Simulate the exposure in a drug-drug interaction (DDI) scenario by implementing ritonavir's inhibition of P-glycoprotein (P-gp) on digoxin. Evaluate the performance of the models by comparing the predicted and observed plasma concentration-time curves and predicted versus observed PK parameter values. Finally, adjust the dosing regimen for the combined therapy based on the changes in exposure.

Results: According to the model simulations, the steady-state exposure of digoxin increased by 86.5% and 90.2% for oral administration, and 80.2% and 90.2% for intravenous administration, respectively, when 0.25 mg or 0.5 mg of digoxin was administered concurrently with ritonavir. By reducing the dose of digoxin by 45% or doubling the oral administration interval, similar steady-state concentrations can be achieved compared to when the drugs are not co-administered.

Conclusions: In clinical practice, the influence of drug interactions on the plasma concentration changes of digoxin within the body should be considered to ensure the safety and effectiveness of treatment.

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基于生理学的药代动力学模型评估利托那韦-地高辛的相互作用并提出联合给药方案建议
背景:地高辛是临床上常用的强心苷类药物,主要通过P-糖蛋白(P-gp)转运,易受P-gp抑制剂/诱导剂的影响。同时服用利托那韦和地高辛可能会显著增加地高辛的血浆浓度。目的:利用基于生理学的药代动力学(PBPK)模型模拟和预测利托那韦和地高辛之间的相互作用对地高辛药代动力学(PK)的影响,并为联合用药方案提供建议:方法:使用 PK-Sim®,为利托那韦和地高辛建立单独的 PBPK 模型。通过实施利托那韦对地高辛的 P-糖蛋白(P-gp)抑制,模拟药物-药物相互作用(DDI)情况下的暴露量。通过比较预测和观察到的血浆浓度-时间曲线以及预测和观察到的 PK 参数值,评估模型的性能。最后,根据暴露量的变化调整联合疗法的给药方案:根据模型模拟结果,在口服地高辛 0.25 毫克或 0.5 毫克地高辛的同时服用利托那韦,地高辛的稳态暴露量分别增加了 86.5% 和 90.2%,静脉注射地高辛的稳态暴露量分别增加了 80.2% 和 90.2%。通过将地高辛的剂量减少45%或将口服给药间隔时间延长一倍,可以达到与不同时给药时相似的稳态浓度:在临床实践中,应考虑药物相互作用对地高辛体内血浆浓度变化的影响,以确保治疗的安全性和有效性。
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来源期刊
Pharmaceutical Research
Pharmaceutical Research 医学-化学综合
CiteScore
6.60
自引率
5.40%
发文量
276
审稿时长
3.4 months
期刊介绍: Pharmaceutical Research, an official journal of the American Association of Pharmaceutical Scientists, is committed to publishing novel research that is mechanism-based, hypothesis-driven and addresses significant issues in drug discovery, development and regulation. Current areas of interest include, but are not limited to: -(pre)formulation engineering and processing- computational biopharmaceutics- drug delivery and targeting- molecular biopharmaceutics and drug disposition (including cellular and molecular pharmacology)- pharmacokinetics, pharmacodynamics and pharmacogenetics. Research may involve nonclinical and clinical studies, and utilize both in vitro and in vivo approaches. Studies on small drug molecules, pharmaceutical solid materials (including biomaterials, polymers and nanoparticles) biotechnology products (including genes, peptides, proteins and vaccines), and genetically engineered cells are welcome.
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Physiologically Based Pharmacokinetic Modeling to Assess Ritonavir-Digoxin Interactions and Recommendations for Co-Administration Regimens. Pharmacological Innovations in Space: Challenges and Future Perspectives. Regulatory Role of eIF2αK4 in Amino Acid Transporter Expression in Mouse Brain Capillary Endothelial Cells. Chemical Distribution Uniformity Assessment of "Intra-Tablet" by Hyperspectral Raman Imaging Analysis. The Current State of Biotransformation Science - Industry Survey of In Vitro and In Vivo Practices, Clinical Translation, and Future Trends.
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