评估GastroPlus预测准确性的应用文章 （2011—2020）
2020-10-11 18:09:39
凡默谷技术部精取了2011-2020年10月评估GastroPlus预测准确性的应用文章23篇。其中编号1-10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. 生理药代动力学PBPK模型在预测药物-食物相互作用中的应用：行业观点
Use of Physiologically Based Pharmacokinetic (PBPK) Modeling for Predicting Drug-Food Interactions: an Industry Perspective.Riedmaier AE, DeMent K, Huckle J, Bransford P, Stillhart C, Lloyd R, Alluri R, Basu S, Chen Y, Dhamankar V, Dodd S, Kulkarni P, Olivares-Morales A, Peng CC, Pepin X, Ren X, Tran T, Tistaert C, Heimbach T, Kesisoglou F, Wagner C, Parrott N. AAPS J. Article number: 123 (2020). IF= 3.7372. 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= 3.7373. IMI-口服药物的生物药剂学方法-评价自下而上的PBPK方法预测的成功率的第4部分：采用改进后的数据和建模策略的预测准确性和软件比较
IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with improved data and modelling strategies.Ahmad A, Pepin X, Aarons L, Wang Y, Darwich AS, Wood JM, et al. Eur J Pharm Biopharm. Volume 156, November 2020, Pages 50-63. IF= 4.6044. 用结构多样且溶解度低的药物，来评估口服吸收模拟软件的预测特征
Prediction characteristics of oral absorption simulation software evaluated using structurally diverse low solubility drugs.Matsumura N, Hayashi S, Akiyama Y, Ono A, Funaki S, Tamura N, Kimoto T, Jiko M, Haruna Y, Sarashina A, Ishida M, Nishiyama K, Fushimi M, Kojima Y, Yoneda K, Nakanishi M, Kim S, Fujita T, Sugano K. J Pharm Sci. Volume 109, Issue 3, March 2020, Pages 1403-1416. IF=2.9975. 采用生理药代动力学PBPK模型预测普拉克索Pramipexole在帕金森氏病肾功能不全患者中的药代动力学
Development of a Physiologically Based Pharmacokinetic Model for Prediction of Pramipexole Pharmacokinetics in Parkinson's Disease Patients With Renal Impairment.Xiang You, Wanhong Wu, Jing Xu, Zheng Jiao, Meng Ke, Pinfang Huang, Cuihong Lin. J Clin Pharmacol. 2020 Aug;60(8):999-1010. IF=4.1936. 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=5.27. 在肾功能不全的儿童患者中的厄他培南生理药代动力学PBPK模型
A Physiologically Based Pharmacokinetic Model of Ertapenem in Pediatric Patients With Renal Impairment.Lingling Ye, Meng Ke, Xiang You, Pinfang Huang, Cuihong LinJournal of Pharmaceutical Sciences. Volume 109, Issue 9, September 2020, Pages 2909-2918. IF= 2.9978. 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=1.6639. 联合体外-计算机模拟的方法，预测BCS II / IV类弱碱阿苯达唑及其主要代谢物阿苯达唑亚砜的口服生物利用度边界
A combined in vitro in-silico approach to predict the oral bioavailability of borderline BCS Class II/IV weak base Albendazole and its main metabolite Albendazole Sulfoxide.Pettarin M, Bolger MB, Chronowska M. Eur J Pharm Sci. Volume 155, 1 December 2020, 105552. IF= 3.61610. 采用生理药代动力学PBPK建模，以了解利培酮口腔崩解膜剂的吸收机理
Physiologically based pharmacokinetic modeling to understand the absorption of risperidone orodispersible film.Fang Chen, Hongrui Liu, Bing Wang, Liuliu Yang, Weimin Cai, Zheng Jiao, Zhou Yang, Yusheng Chen, Yingjun Quan, Xiaoqiang Xiang, Hao Wang. Front. Pharmacol., 03 February 2020. IF=4.54511. 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=3.61612. 药物发现阶段，采用PBPK模型预测酪氨酸激酶抑制剂在人体内PK特征的通用方法
Evaluation of Generic Methods to Predict Human Pharmacokinetics Using Physiologically Based Pharmacokinetic Model for Early Drug Discovery of Tyrosine Kinase Inhibitors.
Ren HC, Sai Y, Chen T. Eur J Drug Metab Pharmacokinet. Jul 23, 2018. IF=1.91313. 生理药代动力学PBPK模型在肿瘤药物开发中的应用及其准确性：系统性的综述
Utility of physiologically based pharmacokinetic (PBPK) modeling in oncology drug development and its accuracy: a systematic review. Saeheng T, Na-Bangchang K, Karbwang J. Eur J Clin Pharmacol. 2018 Nov;74(11):1365-1376. IF=3.26314. 用静态和PBPK模型预测氯沙坦给药后,氯沙坦-活性的羧酸代谢物在体内的暴露
Prediction of Losartan-Active Carboxylic Acid Metabolite Exposure Following Losartan Administration Using Static and Physiologically Based Pharmacokinetic Models. Nguyen H Q, Lin J, Kimoto E, et al. Journal of Pharmaceutical Sciences, 2017.IF=3.61615. 通过GastroPlus®软件探索和验证芒果苷的物理化学性质
Exploring and validating physicochemical properties of mangiferin through GastroPlus® software.Khurana R K, Kaur R, Kaur M, et al. Future Sci OA. 2017. CiteScore=3.116. IMI-口服药物生物药剂学方法项目-评价自下而上的PBPK方法预测的成功率的第2部分：模拟训练的介绍和结果的概述
IMI–Oral biopharmaceutics tools project– Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results. Margolskee A, Darwich A S, Pepin X, et al. EUR J Pharm Sci, 2017, 96: 610-625.IF=3.61617. IMI-口服药物生物药剂学方法项目-评价自下而上的PBPK方法预测的成功率的第3部分：通过对不同类别化合物的计算机预测In Silico性能分析，鉴定系统参数中与目标的差距
IMI–Oral biopharmaceutics tools project– Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes. Darwich A S, Margolskee A, Pepin X, et al. EUR J Pharm Sci, 2017, 96: 626-642.IF=3.61618. 在药物早期发现阶段，评估GastroPlus™高级房室和转运（ACAT）模型的适用性
Evaluation of the GastroPlus™ Advanced Compartmental and Transit (ACAT) Model in Early Discovery. Gobeau N, Stringer R, De Buck S, Tuntland T, Faller B. (2016). Pharm Res. Jun 8.IF=3.24219. 通过计算机模拟药物在胃肠道的吸收：三种基于生理学的吸收模型的预测性能
In silico modeling of gastrointestinal drug absorption: predictive performance of three physiologically based absorption models. Sjögren E, Thörn H, Tannergren C. (2016). Mol Pharm. Feb 29. IF=4.321
Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds. Zhang T, Heimbach T, Lin W, Zhang J, He H. (2015). J Pharm Sci. Feb 17. IF=3.616
Predicting Pharmacokinetic Profiles Using In Silico Derived Parameters. Hosea NA, Jones HM. (2013). Mol Pharm. Feb 21. IF=4.32122. 通过计算机预测，体外和临床前体内数据对BCS / BDDCS类化合物进行实际食物效应评估的案例研究
Case Studies for Practical Food Effect Assessments across BCS/BDDCS Class Compounds using In Silico, In Vitro, and Preclinical In Vivo Data. Heimbach T, Xia B, Lin TH, He H. (2012). AAPS J. Nov 10. IF=3.73723. 使用生理学药代动力学PBPK模型模拟21种不同化合物静脉和口服给药后在人体的药代动力学
Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling. Jones HM, Gardner IB, Collard WT, Stanley PJ, Oxley P, Hosea NA, Plowchalk D, Gernhardt S, Lin J, Dickins M, Rahavendran SR, Jones BC, Watson KJ, Pertinez H, Kumar V, Cole S. (2011). Clin Pharmacokinet. 1;50(5):331-47. IF=4.604
