Prediction of Pharmacokinetic Drug-Drug Interactions Involving Anlotinib as a Victim by Using Physiologically Based Pharmacokinetic Modeling.

IF 4.7 2区医学 Q1 CHEMISTRY, MEDICINAL

Drug Design, Development and Therapy Pub Date : 2024-10-15 eCollection Date: 2024-01-01 DOI:10.2147/DDDT.S480402

Fengjiao Bu, Yong-Soon Cho, Qingfeng He, Xiaowen Wang, Saurav Howlader, Dong-Hyun Kim, Mingshe Zhu, Jae Gook Shin, Xiaoqiang Xiang

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引用次数: 0

Abstract

Background: Anlotinib was approved as a third line therapy for advanced non-small cell lung cancer in China. However, the impact of concurrent administration of various clinical drugs on the drug-drug interaction (DDI) potential of anlotinib remains undetermined. As such, this study aims to evaluate the DDI of anlotinib as a victim by establishing a physiologically based pharmacokinetic (PBPK) model.

Methods: The PBPK model of anlotinib as a victim drug was constructed and validated in the Simcyp^® incorporating parameters derived from in vitro studies, pre-clinical investigations, and clinical research encompassing patients with cancer. Subsequently, plasma exposure of anlotinib in cancer patients was predicted for single- and multi-dose co-administration with typical perpetrators mentioned in Food and Drug Administration (FDA) industrial guidance.

Results: Based on predictions, the CYP3A potent inhibitor ketoconazole demonstrated the most significant DDI with anlotinib, regardless of whether anlotinib is administered as a single dose or multiple doses. Ketoconazole increased the area under the concentration-time curve (AUC) and maximum concentration (C_max) of single-dose anlotinib to 1.41-fold and 1.08-fold, respectively. In contrast, rifampicin, a potent inducer of CYP3A enzymes, exhibited a relatively higher level of DDI, with AUC_R and C_maxR values of 0.44 and 0.79, respectively.

Conclusion: Based on the PBPK modeling, there is a low risk of DDI between anlotinib and potent CYP3A/1A2 inhibitors, but caution and enhanced monitoring for adverse reactions are advised. To mitigate the risk of anti-tumor treatment failure, it is recommended to avoid concurrent use of strong CYP3A inducers. In conclusion, our study enhances understanding of anlotinib's interaction with medications, aiding scientists, prescribers, and drug labels in gauging the expected impact of CYP3A/1A2 modulators on anlotinib's pharmacokinetics.

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利用基于生理学的药代动力学模型预测安罗替尼作为受害者参与的药代动力学药物间相互作用

背景安罗替尼在中国被批准作为晚期非小细胞肺癌的三线治疗药物。然而，同时服用多种临床药物对安洛替尼的药物相互作用（DDI）潜力的影响仍未确定。因此，本研究旨在通过建立基于生理学的药代动力学（PBPK）模型，评估作为受害者的安罗替尼的DDI：方法：结合体外研究、临床前研究和包括癌症患者在内的临床研究得出的参数，在Simcyp®中构建并验证了作为受害者药物的安罗替尼的PBPK模型。随后，预测了癌症患者在单剂量和多剂量与食品药品管理局（FDA）工业指南中提到的典型加害药联合用药时的安罗替尼血浆暴露量：根据预测，CYP3A强效抑制剂酮康唑与安罗替尼的DDI最为显著，无论安罗替尼是单剂量给药还是多剂量给药。酮康唑使单剂安罗替尼的浓度曲线下面积（AUC）和最大浓度（Cmax）分别增加了1.41倍和1.08倍。相比之下，CYP3A酶的强效诱导剂利福平的DDI水平相对较高，AUCR和CmaxR值分别为0.44和0.79：根据PBPK模型，安罗替尼与强效CYP3A/1A2抑制剂之间的DDI风险较低，但建议谨慎用药并加强不良反应监测。为降低抗肿瘤治疗失败的风险，建议避免同时使用强效CYP3A诱导剂。总之，我们的研究加深了人们对安洛替尼与药物相互作用的了解，有助于科学家、处方者和药品标签衡量CYP3A/1A2调节剂对安洛替尼药代动力学的预期影响。

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

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.