GastroPlus 在预测药物相互作用DDI 的应用文章 （2011 —2020 ）
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凡默谷技术部精取了2011-2020年10月在预测药物相互作用DDI的应用文章28篇。
其中编号1-6的文章是2019年8月-2020年10月新增的文章。
希望对您的业务或专业学习有所帮助。内容如下：
1. 通过体外研究、静态和生理药代动力学PBPK模型，评估埃沙西林酮Esaxerenone作为作促变药导致的药物相互作用DDI风险
Drug-Drug Interaction Risk Assessment of Esaxerenone as a Perpetrator by In Vitro Studies and Static and Physiologically Based Pharmacokinetic Models.
Makiko Yamada, Tomoko Ishizuka, Shin-ichi Inoue, Veronika Rozehnal, Thomas Fischer, Daisuke Sugiyama. Drug Metabolism and Disposition. September 2020, 48 (9) 769-777. IF=3.231
2. 构建和验证主要由葡萄糖醛酸代谢清除的4种药物的生理药代动力学PBPK模型：劳拉西泮, 奥沙西泮, 纳洛酮, 齐多夫定
Construction and Verification of Physiologically Based Pharmacokinetic Models for Four Drugs Majorly Cleared by Glucuronidation: Oxazepam, Naloxone, and Zidovudine.
Docci L, Umehara K, Krähenbühl S, Fowler S, Parrott N. AAPS J. 2020 Oct 8;22(6):128. IF= 3.737
3. 采用生理药代动力学PBPK模型预测具有pH依赖的弱碱性药物的药物相互作用DDI
Application of Physiologically-Based Pharmacokinetic Modeling to Predict Gastric pH-Dependent Drug–Drug Interactions for Weak Base Drugs.
Zhongqi Dong, Jia Li, Fang Wu, Ping Zhao, Sue‐Chih Lee, Lillian Zhang, Paul Seo, Lei Zhang. CPT: Pharmacometrics & Systems Pharmacology, Volume9, Issue8. August 2020. CiteScore=5.2
4. 采用生理药代动力学模型，考察肠道CYP3A弱调节剂对药物相互作用风险的关键影响
Critical impact of drug-drug interactions via intestinal CYP3A in the risk assessment of weak perpetrators using physiologically based pharmacokinetic models.
Yamada M, Inoue SI, Sugiyama D, Nishiya Y, Ishizuka T, Watanabe A, Watanabe K, Yamashita S, Watanabe N. Drug Metab Dispos. 48:288–296, April 2020. IF=3.231
5. 使用基于生理的生物药剂学PBBM模型预测具有pH依赖的碱性药物的药物相互作用DDI
Prediction of pH-Dependent Drug-Drug Interactions for Basic Drugs Using Physiologically Based Biopharmaceutics Modeling: Industry Case Studies.
Mitra A, Parrott N, Miller N, Lloyd R, Tistaert C, Heimbach T, Ji Y, Kesisoglou F. J Pharm Sci. Volume 109, Issue 3, March 2020, Pages 1380-1394. IF=3.616
6. 采用生理药代动力学PBPK模型考察羟考酮的药物相互作用DDI
Physiologically based pharmacokinetic modelling of oxycodone drug-drug interactions.
Rytkonen J, Ranta VP, Kokki M, Rinne V, Heikkinen AT. Biopharm Drug Dispos. Volume41, Issue1-2, February 2020, Pages 72-88. IF=1.663
7. 预测不同的三唑类抗真菌药物对他莫昔芬PK的影响
Predicting the Effects of Different Triazole Antifungal Agents on the Pharmacokinetics of Tamoxifen.
Chen L, Zhu L, Li M, Li N, Qi F, Wang N. AAPS PharmSciTech. Jan 2, 2019.IF=2.401
8. 甘草酸很可能是肝脏OATP1B1/1B3转运体介导的药物相互作用DDI的“受害者”
Glycyrrhizin has a high likelihood to be a victim of drug-drug interactions mediated by hepatic OATP1B1/1B3.
Dong J, Olaleye OE, Jiang R, Li J, Lu C, Du F, Xu F, Yang J, Wang F, Jia W, Li C. Br J Pharmacol. 2018 Sep;175(17):3486-3503. IF=7.73
9. 根据碱性盐形药物在胃酸过少或胃酸缺乏的生物相关介质中数据，建立其基于生理学的吸收模型
Physiologically Based Absorption Modeling of Salts of Weak Bases Based on Data in Hypochlorhydric and Achlorhydric Biorelevant Media.
Kesisoglou F, Vertzoni M, Reppas C. AAPS PharmSciTech. 2018 Jun 5. IF=2.401
10. 采用基于生理学的口服吸收模型研究药物在肠道中的药物相互作用
Physiologically Based Oral Absorption Modelling to Study Gut-Level Drug Interactions.
Chung J, Kesisoglou F. J Pharm Sci. 2018 Jan;107(1):18-23. IF=3.616
11. 在药物发现和开发阶段，预测胃酸减少剂ARA/质子泵抑制剂PPI导致的药物相互作用DDI
Prediction of ARA/PPI Drug-Drug Interactions at the Drug Discovery and Development Interface.
Dodd S, Kollipara S, Sanchez-Felix M, Kim H, Meng Q, Beato S, Heimbach T. J Pharm Sci. Oct 29, 2018. IF=3.616
12. Ribociclib的生物利用度不受胃pH变化或食物摄入的影响：通过计算机预测In Silico和临床试验进行评估
Ribociclib Bioavailability Is Not Affected by Gastric pH Changes or Food Intake: In Silico and Clinical Evaluations.
Samant TS, Dhuria S, Lu Y, Laisney M, Yang S, Grandeury A,et,al. Clin Pharmacol Ther. 2017 Nov 14.IF=6.565
13. 在早期阶段，采用GastroPlusTM DDI模块预测时间依赖性CYP抑制剂对临床药物相互作用DDI的策略
A strategy for early-risk predictions of clinical drug–drug interactions involving the GastroPlusTM DDI module for time-dependent CYP inhibitors.
Sohlenius-Sternbeck A K, Meyerson G, Hagbjörk A L, et al. Xenobiotica, 2017: 1-9.IF=1.902
14. 不同的质子泵抑制剂PPI对伏立康唑PK的影响
Influence of different proton pump inhibitors on the pharmacokinetics of voriconazole.
Qi F, Zhu L, Li N, et al. International Journal of Antimicrobial Agents, 2017, 49(4): 403-409. IF=4.621
15. 代谢酶介导的临床相关药物相互作用DDI的预测和解释方面的进展：近期发展和当前机遇的简要介绍
Progress in Prediction and Interpretation of Clinically Relevant Metabolic Drug-Drug Interactions: a Minireview Illustrating Recent Developments and Current Opportunities.
Fowler S, Morcos P N, Cleary Y, et al. Current Pharmacology Reports, 2017, 3(1): 36-49.
16. 使用生理药代动力学PBPK建模方法预测药物的PK和药物相互作用DDI风险：以咖啡因和环丙沙星为案例
Prediction of pharmacokinetics and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach: A case study of caffeine and ciprofloxacin.
Park M H, Shin S H, Byeon J J, et al. The Korean Journal of Physiology & Pharmacology, 2017, 21(1): 107-115.IF=1.805
17. 采用体外溶出-渗透池室定量预测pH依赖性药物与胃酸减少剂的药物相互作用DDI：采用生理药代动力学PBPK模型进行比较
Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of pH-Dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling [J].
Zhu A Z X, Ho M C D, Gemski C K, et al. The AAPS journal, 2016, 18(6): 1512-1523. IF=3.737
18. CPY450 3A4抑制剂酮康唑和红霉素对Bitopertin PK的影响，并对比生理药代动力学PBPK的预测结果
Effects of Cytochrome P450 3A4 Inhibitors - Ketoconazole and Erythromycin - on Bitopertin Pharmacokinetics and Comparison with Physiologically Based Modelling Predictions.
Boetsch C, Parrott N, Fowler S, Poirier A, Hainzl D, Banken L, Martin-Facklam M, Hofmann C. (2015). Clin Pharmacokinet. Sep 4. IF=4.604
19. 采用生理药代动力学PBPK模型定量预测草本-药物相互作用的框架
Physiologically Based Pharmacokinetic Modeling Framework for Quantitative Prediction of an Herb–Drug Interaction.
SJ Brantley, BT Gufford, R Dua, DJ Fediuk, TN Graf, YV Scarlett, KS Frederick, MB Fisher, NH Oberlies, MF Paine. CPT Pharmacometrics Syst Pharmacol. 26 March 2014.CiteScore=5.2
20. 新MDM2拮抗剂Idasanutlin在食蟹猴体内的自身诱导作用及该诱导与人体相关性的研究
Investigating the effect of autoinduction in cynomolgus monkeys of a novel anticancer MDM2 antagonist, idasanutlin, and relevance to humans.
Glenn KJ, Yu LJ, Reddy MB, Fretland AJ, Parrott N, Hussain S, Palacios M, Vazvaei F, Zhi J, Tuerck D. (2015). Xenobiotica. Nov 19:1-10. IF=1.902
21. 采用生理药代动力学PBPK模型预测双环醇控释制剂在人体的PK
Application of physiologically based pharmacokinetic modeling in the prediction of pharmacokinetics of bicyclol controlled-release formulation in human.
Wang B, Liu Z, Li D, Yang S, Hu J, Chen H, Sheng L, Li Y. (2015). Eur J Pharm Sci.Jun 24. IF=3.616
22. 采用生理药代动力学PBPK模拟利福平对人体CYP3A4诱导的作用：底物与诱导剂不同的给药间隔的影响
Physiologically based pharmacokinetic modeling of CYP3A4 induction by rifampicin in human: influence of time between substrate and inducer administration.
Baneyx G, Parrott N, Meille C, Iliadis A, Lavé T. (2014). Eur J Pharm Sci. Feb 12.IF=3.616
23. 使用生理药代动力学PBPK模型预测涉及多种机制的药物相互作用DDI：以Ruxolitinib为案例
Predicting drug-drug interactions involving multiple mechanisms using physiologically based pharmacokinetic modeling: A case study with ruxolitinib.
Shi JG, Fraczkiewicz G, Williams W, Yeleswaram S. (2014). Clin Pharmacol Ther.10.1002/cpt.30. IF=6.565
24. 采用计算机模拟预测盐酸环丙沙星/金属化合物的药物相互作用
A Case Study of In Silico Modelling of Ciprofloxacin Hydrochloride/Metallic Compound Interactions.
Stojkovic A, Parojcic J, Djuric Z, Corrigan OI. (2013) AAPS PharmSciTech. Dec 5.IF=2.401
25. 通过对阿西替尼Axitinib与人外排和肝脏摄取转运体的体外相互作用进行表征，了解这些因素对处置和药物相互作用的影响
In Vitro Characterization of Axitinib Interactions with Human Efflux and Hepatic Uptake Transporters. Implications for Disposition and Drug Interactions.
Reyner E, Sevidal S, West MA, Clouser-Roche A, Freiwald S, Fenner K, Ullah M, Lee C, Smith BJ. (2013) Drug Metab Dispos. May 31.IF=3.231
26. 采用PBPK模型预测口服剂型的体内性能
PBPK models for the prediction of in vivo performance of oral dosage forms.
Kostewicz ES, Aarons L, Bergstrand M, Bolger MB, Galetin A, Hatley O, Jamei M, Lloyd R, Pepin X, Rostami A, Sjögren E, Tannergren C, Turner DB, Wagner C, Weitschies W, Dressman J. (2013) Eur J Pharm Sci. Sep 21. IF=3.616
27. 通过建模与模拟研究质子泵抑制剂PPI对镁离子吸收的影响
Modeling and simulation of the effect of proton pump inhibitors on magnesium homeostasis: part I. oral absorption of magnesium.
Bai JP, Hausman E, Lionberger R, Zhang X. (2012) Mol Pharm. Oct. 11. IF=4.321
28. 盐酸环丙沙星与硫酸亚铁相互作用后的生物药剂学特征
Biopharmaceutical Characterization of Ciprofloxacin HCl–Ferrous Sulfate Interaction.
Jelena parojcic, Aleksandra stojkovic, Lidia tajber, Sandra grbic, Krzysztof J. Paluch. (2011). J Pharm Sci. 100(12):5174-84. IF=3.616