College of Pharmacy and Integrated Research Institute of Pharmaceutical Sciences, The Catholic University of Korea, Bucheon, 14662, Republic of Korea.
Arch Pharm Res. 2017 Dec;40(12):1356-1379. doi: 10.1007/s12272-017-0976-0. Epub 2017 Oct 27.
The occurrence of drug-drug interactions (DDIs) can significantly affect the safety of a patient, and thus assessing DDI risk is important. Recently, physiologically based pharmacokinetic (PBPK) modeling has been increasingly used to predict DDI potential. Here, we present a PBPK modeling concept and strategy. We also surveyed PBPK-related articles about the prediction of DDI potential in humans published up to October 10, 2017. We identified 107 articles, including 105 drugs that fit our criteria, with a gradual increase in the number of articles per year. Studies on antineoplastic and immunomodulatory drugs (26.7%) contributed the most to published PBPK models, followed by cardiovascular (20.0%) and anti-infective (17.1%) drugs. Models for specific products such as herbal products, therapeutic protein drugs, and antibody-drug conjugates were also described. Most PBPK models were used to simulate cytochrome P450 (CYP)-mediated DDIs (74 drugs, of which 85.1% were CYP3A4-mediated), whereas some focused on transporter-mediated DDIs (15 drugs) or a combination of CYP and transporter-mediated DDIs (16 drugs). Full PBPK, first-order absorption modules and Simcyp software were predominantly used for modeling. Recently, DDI predictions associated with genetic polymorphisms, special populations, or both have increased. The 107 published articles reasonably predicted the DDI potentials, but further studies of physiological properties and harmonization of in vitro experimental designs are required to extend the application scope, and improvement of DDI predictions using PBPK modeling will be possible in the future.
药物-药物相互作用（DDI）的发生会显著影响患者的安全性，因此评估DDI 风险很重要。最近，基于生理学的药代动力学（PBPK）建模已越来越多地用于预测 DDI 潜力。在这里，我们提出了一个 PBPK 建模概念和策略。我们还调查了截至 2017 年 10 月 10 日发表的关于预测人类 DDI 潜力的 PBPK 相关文章。我们确定了 107 篇文章，包括 105 种符合我们标准的药物，每年发表的文章数量逐渐增加。抗肿瘤和免疫调节药物（26.7%）的研究对发表的 PBPK 模型贡献最大，其次是心血管（20.0%）和抗感染（17.1%）药物。还描述了针对特定产品的模型，如草药产品、治疗性蛋白药物和抗体-药物偶联物。大多数 PBPK 模型用于模拟细胞色素 P450（CYP）介导的 DDI（74 种药物，其中 85.1%为 CYP3A4 介导），而有些则侧重于转运体介导的 DDI（15 种药物）或 CYP 和转运体介导的 DDI 的组合（16 种药物）。全 PBPK、一阶吸收模块和 Simcyp 软件主要用于建模。最近，与遗传多态性、特殊人群或两者相关的 DDI 预测有所增加。107 篇已发表的文章合理地预测了 DDI 潜力，但需要进一步研究生理特性和体外实验设计的协调，以扩大应用范围，未来使用 PBPK 建模改善 DDI 预测将成为可能。
