GastroPlus 在預測藥物相互作用DDI 的應用文章 （2011 —2020 ）

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凡默谷技術部精取了2011-2020年10月在預測藥物相互作用DDI的應用文章28篇。

其中編號1-6的文章是2019年8月-2020年10月新增的文章。

希望對您的業務或專業學習有所幫助。內容如下：

1.  通過體外研究、靜態和生理藥代動力學PBPK模型，評估埃沙西林酮Esaxerenone作為作促變藥導致的藥物相互作用DDI風險

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.  構建和驗證主要由葡萄糖醛酸代謝清除的4種藥物的生理藥代動力學PBPK模型：勞拉西泮, 奧沙西泮, 納洛酮, 齊多夫定

Construction and Verification of Physiologically Based Pharmacokinetic Models for Four Drugs Majorly Cleared by Glucuronidation: Oxazepam, Naloxone, and Zidovudine.

Docci L, Umehara K, Kr?henbühl S, Fowler S, Parrott N. AAPS J. 2020 Oct 8;22(6):128. IF= 3.737

3.  采用生理藥代動力學PBPK模型預測具有pH依賴的弱堿性藥物的藥物相互作用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.   采用生理藥代動力學模型，考察腸道CYP3A弱調節劑對藥物相互作用風險的關鍵影響

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藥劑學PBBM模型預測具有pH依賴的堿性藥物的藥物相互作用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.  采用生理藥代動力學PBPK模型考察羥考酮的藥物相互作用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.  預測不同的三唑類抗真菌藥物對他莫昔芬PK的影響

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.   甘草酸很可能是肝臟OATP1B1/1B3轉運體介導的藥物相互作用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.   根據堿性鹽形藥物在胃酸過少或胃酸缺乏的生物相關介質中數據，建立其基于生理學的吸收模型

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.  采用基于生理學的口服吸收模型研究藥物在腸道中的藥物相互作用

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.  在藥物發現和開發階段，預測胃酸減少劑ARA/質子泵抑制劑PPI導致的藥物相互作用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變化或食物攝入的影響：通過計算機預測In Silico和臨床試驗進行評估

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.  在早期階段，采用GastroPlusTM DDI模塊預測時間依賴性CYP抑制劑對臨床藥物相互作用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, Hagbj?rk A L, et al. Xenobiotica, 2017: 1-9.IF=1.902

14.   不同的質子泵抑制劑PPI對伏立康唑PK的影響

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.   代謝酶介導的臨床相關藥物相互作用DDI的預測和解釋方面的進展：近期發展和當前機遇的簡要介紹

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.  使用生理藥代動力學PBPK建模方法預測藥物的PK和藥物相互作用DDI風險：以咖啡因和環丙沙星為案例

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.  采用體外溶出-滲透池室定量預測pH依賴性藥物與胃酸減少劑的藥物相互作用DDI：采用生理藥代動力學PBPK模型進行比較

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抑制劑酮康唑和紅霉素對Bitopertin PK的影響，并對比生理藥代動力學PBPK的預測結果

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.  采用生理藥代動力學PBPK模型定量預測草本-藥物相互作用的框架

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拮抗劑Idasanutlin在食蟹猴體內的自身誘導作用及該誘導與人體相關性的研究

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.  采用生理藥代動力學PBPK模型預測雙環醇控釋制劑在人體的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.  采用生理藥代動力學PBPK模擬利福平對人體CYP3A4誘導的作用：底物與誘導劑不同的給藥間隔的影響

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.  使用生理藥代動力學PBPK模型預測涉及多種機制的藥物相互作用DDI：以Ruxolitinib為案例

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. 采用計算機模擬預測鹽酸環丙沙星/金屬化合物的藥物相互作用

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.  通過對阿西替尼Axitinib與人外排和肝臟攝取轉運體的體外相互作用進行表征，了解這些因素對處置和藥物相互作用的影響

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模型預測口服劑型的體內性能

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, Sj?gren E, Tannergren C, Turner DB, Wagner C, Weitschies W, Dressman J. (2013) Eur J Pharm Sci. Sep 21. IF=3.616

27.  通過建模與模擬研究質子泵抑制劑PPI對鎂離子吸收的影響

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.  鹽酸環丙沙星與硫酸亞鐵相互作用后的生物藥劑學特征

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

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