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GastroPlus药代与制剂模拟软件:PBPK及ACAT模型

 

 

 

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近年来,采用GastroPlus软件进行相关的科研工作越来越多,包括FDA在内的等单位已将GastroPlus的建模与模拟工作纳入日常化工作中。与此同时,大量高水平的文章也层出不穷。

凡默谷特挑选了涵盖法规部门、制药企业、学术单位的典型文章共12篇,内容涉及PBPKPK-PDDDIIVIVC、特殊人群PK预测等多个方面。每篇文献翻译了摘要,以便大家能快速地获取文章内容,希望这些信息能够为大家的科研工作带来一点帮助。

1. PBPK综述】:生理药代动力学模型(PBPK)在药物研发及监管中的研究

Physiologically-Based Pharmacokinetics in Drug Development and Regulatory Science

Malcolm Rowland, Carl Peck, and Geoffrey Tucker. (2011) Annu. Rev. Pharmacol. Toxicol. 51:45–73. (IF: 21.543)

【摘要】生理药代动力学模型(PBPK)在药物研发与监管中得到了广泛应用意味着新时代的来临,这反映了过去10年中,在利用人体外试验数据预测主要的药代动力学参数方面取得了重大进步,并且涌现了一批可获得到的专业软件平台与相关数据库。本文对如下内容进行综述:药物清除率、分布与吸收预测方面的进步与当前挑战,基于PK定量预测的药物药物相互作用(DDI)的程度,及预测年龄、遗传学、疾病与剂型的影响。这在选择和设计合适的临床研究方面具体很好的价值,这隐含了PBPK在资源节约方面具有意义,同时其整体观念将跨越临床前/临床方面药代动力学应用的鸿沟;最后,对PBPK在药物研发、审批示范与个体化用药实践的预期应用方面的定位进行阐述。

2. FDA综述】:机制性吸收模型在基于QbD思想的药物开发中应用

Utility of Physiologically Based Absorption Modeling in Implementing Quality by Design in Drug Development.

Zhang X, Lionberger RA, Davit BM, Yu LX. (2011) AAPS J. 13(1): 59-71. (IF: 4.386)

【摘要】为将质量源于设计(Quality by Design, QbD)的思想用于药物的开发过程,需要选择合适的方法将药品的性质与体内行为关联起来。其中,机制性的吸收模型就是一种很具有潜力的方法,然而,在公开发表的文献里面,还没有对其在QbD的应用有全面的介绍和描述。本文以卡马西平作为模型药物,模拟其四种制剂(速释混悬液、速释片剂、迟释片剂以及胶囊)在空腹和饱腹两种状态下的PK行为,并介绍了在药物开发过程建模与模拟方法应用的一般流程。通过对速释混悬液在空腹状态下的PK数据进行去卷积计算,获得了相应的PK参数和吸收放大系数(ASFs);然后用速释的其它制剂验证模型;最后预测迟释制剂的PK曲线。

在本文中,我们探寻了建模与模拟的方法在QbD中的三个应用领域:1. 指导建立缓释制剂最优的体外溶出条件;2. 通过参数敏感性分析鉴定影响制剂的关键性因素,结果显示随着粒径的减小,速释片剂的PK曲线会有所偏移;Cmax将增加,而Tmax则减小;3. 模型的虚拟模拟整合了群体的内部变量,可进行虚拟生物等效性模拟。对两个受试制剂进行BE模拟,结果提示相比体内PK实验,测定体外溶出曲线是更能区分仿制药是否生物等效的敏感方法。总之,一个经充分验证的模型,将在基于QbD思想的药物开发过程中扮演一个十分重要的角色。

3. 【辉瑞应用案例】:基于生理药代动力学模型(PBPK)预测21个化合物经静脉和口服给药后在人体的PK曲线--

Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling.

Jones HM, et al. (2011) Clin Pharmacokinet. 1; 50(5): 331-47. (IF: 6.109)

【摘要】背景:现在,越来越多的制药企业都意识到,在化合物筛选过程,提前预测化合物在人体的PK行为是十分重要的;文献中也报道了很多方法来实现这种预测。

方法:在本文中,我们比较了GastroPlus软件内建的生理药代动力学模型(PBPK)和辉瑞公司日常用的经典一房室模型,对人体药时曲线预测的准确性。选择了辉瑞公司21个化合物最为模型药物,这些化合物临床前及临床数据都表现出一定的差异性;针对每一个化合物,分别模拟了静脉和口服给药后的药代动力学曲线。此外,为了减小预测的误差,本研究将实测的清除率加载到模型中去。

结果:模拟结果显示,PBPK方法的精准性要由于传统的一房室模型,而且在很多例子中这种差异都体现出一定的统计学分析意义。值得一提的是,PBPK模型可以很准确地预测被动扩散和吸收的过程。当然,在清除率和主动转运的预测方面,目前PBPK模型还有一定的局限性,这个需要在将来的PBPK模型中得到进一步的加强。PBPK模型的一个重要优势,就是对于很多测试化合物,该模型能很准确地预测多形状的药代曲线。

结论:通过本研究的评估,阐述了PBPK方法在人体PK预测方面的功能。PBPK模型可用到药物研发的各个阶段,以增强对一个特定化学系列化合物的理解,指导试验,辅助候选化合物的筛选以及指导临床试验方案的设计等。

4. PSA分析】:基于胃肠道模拟技术确定生物药剂学分类,以考察兰索拉唑肠溶片的吸收特性

Profiling biopharmaceutical deciding properties of absorption of lansoprazole enteric-coated tablets using gastrointestinal simulation technology.
Chunnuan Wu, Jin Sun, Zhonggui He, et al. (2013) Int J Pharm.10; 453(2): 300-6. (IF: 3.458)

【摘要】本研究的目的是为了建立制剂的体外性质与体内行为之间的相关性,进而阐明决定药物口服吸收的性质参数。采用胃肠道模拟技术模拟了药物体内的血药浓度-时间曲线,具体的模拟手段则借助了GastroPlus模拟软件。本文选择了典型的BCS II类药物-兰素拉唑作为模型药物。

首先,通过文献收集兰索拉唑的理化及药代性质参数以建立基础模型;并经对比预测的和实测的药时曲线的差异来进一步验证模型。结果发现,预测曲线和实测值能够很好地重合。然后,进行参数敏感性分析(PSA)以寻找影响口服吸收的关键性参数。结果提示,对于兰索拉唑肠溶片来说,剂量、溶解度和粒径极大地影响了其吸收。在口服单剂量30mg,溶解度为0.04 mg/mL的情况下,该制剂能够完全吸收;此外,粒径控制在25um以下时,兰索拉唑能够很好地被吸收。

通过本文的研究,我们发现胃肠道模拟技术对确定生物药剂学分类,考察兰索拉唑肠溶片的吸收特性、指导制剂处方优化是一个非常有用的方法。

5. IVIVC应用】:卡马西平口服固体制剂联合IVIVC和胃肠道生理模拟的生物豁免论证

Justification of Biowaiver for Carbamazepine, a Low Soluble High Permeable Compound, in Solid Dosage Forms Based on IVIVC and Gastrointestinal Simulation

Ivan Kovacˇevic´, Jelena Parojcˇic´, Irena Homsˇek, et al.(2008) Mol Pharm. 6(1): 40-7. (IF: 4.57)

【摘要】本文旨在联合胃肠道的模拟技术和体内外相关性(IVIVC)的数学模型去探讨BCS II类化合物生物豁免所需的标准尺度。本文以卡马西平为模型药物,药物在胃肠道的体内过程是采用GastroPlus中的高级隔室吸收和转运模型(ACAT)进行模拟的。用于搭建卡马西平IVIVC的体外和体内数据来源于生物等效性研究的报告中。研究表明卡马西平基于其基本的理化性质和生物药剂学性质通过该模型所预测的血药浓度和实测的非常吻合。参数敏感性分析(PSA)表明GastroPlus中所录入的参数并不是影响药物吸收的关键性因素。另外卡马西平的血药浓度也需要依据不同溶出条件下的溶出曲线进行模拟。虽然不同的体外溶出导致模拟的AUC的暴露量是一致的,但是CmaxTmax还是有一定的差异的。通过建立的AIVIVC发现对于IRCR的卡马西平片剂,1%SLS可以考虑做为两种处方的通用溶出介质。最终通过整合胃肠道的模拟技术和IVIVC的数学模型的这套方法对卡马西平的生物豁免提供了很好的支持和依据,并且对卡马西平IR片剂的溶出标准的拓宽也提供了相应依据和指导。

6. 【转运体】:体外方法表征阿西替尼与人外排及肝摄取转运体之间的作用:处置的影响及药物相互作用

In Vitro Characterization of Axitinib Interactions with Human Efflux and Hepatic Uptake Transporters: Implications for Disposition and Drug Interactions.

Reyner EL, et al. (2013) Drug Metab Dispos. 41(8):1575-83. (IF: 3.361)

【摘要】阿西替尼是血管内皮生长因子酪氨酸激酶受体123的抑制剂。阿西替尼的ATP结合盒转运体(ABC)和溶质转运蛋白(SLC)性质受所选择的蜂窝系统决定。所有的细胞体系试验测定发现,阿西替尼展现高的透膜特性(Papp6×10-6 cm/s)。主动外排作用首先采用Caco-2细胞观测的;然后选择多药耐药基因1(MDR1)或乳腺癌耐药蛋白(BCRP)转染的犬肾传代细胞2(MDCK)进行深入地评估,结果提示除了BCRP之外,阿西替尼还是P-gp的一个弱的底物。在Caco-2细胞实验中发现,阿西替尼对P-gp协调转运体底物地高辛有部分的抑制作用;而在BCRP转染的MDCK细胞实验中发现,阿西替尼对BCRP转运体底物托普乐肯也有部分抑制作用,相应的IC50值分别为3mM4.4mM。按照当前的法规指南,10mg的阿西替尼不会造成对P-gpPCRP的药物相互作用。

然而,由于口服给药10mg (服用250mL)的阿西替尼的浓度是IC50值的十倍,因此认为在胃肠道中该药对P-gpBCRP有潜在的药物相互作用的风险。但是,通过GastroPlus软件模拟发现,由于阿西替尼的低溶解度会导致其在胃肠道中的浓度较低,因此在胃肠道中产生对P-gpBCRP底物相互作用的风险也较低。转运阿西替尼至一小量并被悬浮的肝细胞摄取的有机阴离子转运多肽1B1(OATP1B1)OATP1B3转染的人胚肾293(HEK293)细胞,是不受利福平SV抑制的,提示该药物被动渗透占据主导地位。采用小鼠全身放射显影技术,将阿西替尼进行C14标记,结果显示除了脑部组织外,阿西替尼能够快速地在各个组织中吸收和分布。该结果表明阿西替尼的外排转运作用将发生在小鼠的血脑屏障中。

7. 【代谢酶】:通过计算机模拟建模的方法研究P-gpCYP3A4的底物UK-343,664的非线性吸收药动学

In Silico Modeling for the Nonlinear Absorption Kinetics of UK-343,664: A P-gp and CYP3A4 Substrate.

Abuasal BS, Bolger MB, Walker DK, Kaddoumi A. (2012) Mol Pharm. 9: 492-504. (IF: 4.57)

【摘要】UK-343,664P-gpCYP3A4所介导的底物,本文旨在通过该化合物的体外数据和临床前的动物数据去外推在人体的药动行为。另外,该研究通过高级隔室吸收和转运的模型(ACAT)搭建了化合物相应的吸收模型,从而去诠释UK-343,664由于P-gpCYP3A4所介导引起的非线性吸收、首过效应等多种机制相互作用的药动行为。最后,对模型预测的结果和临床实测的结果进行了对比。在体灌流、异数放大、生理的PBPK方法、体外的代谢数据和适当的体内数据可以被用来分别解释药物在机体内的吸收、分布和代谢行为。GastroPlus可以很好的将以上信息整合起来,便于搭建UK-343,664的生理人体模型,从而机制性的去解释临床口服给予30100200400800mg的药动行为。CYP3A4的体外Km=465μM(假设17.8%的微粒体结合进行校正)和CYP2C8, 2C9, 2C19, 2D63A438.9 pmol/min/pmol)的Vmax被用来模拟预测肝脏的首过和系统清除率。CYP3A4的体外KmVmax2D6Vmax被用来模拟预测胃肠道中的首过现象。P-gpKmVmax是通过拟合体内药动行为获取的,并且被用来模拟胃肠道中的外排转运。通过对比虚拟敲除P-gp或胃肠道中代谢酶后UK-343,664的吸收百分数、到达门静脉的吸收量和在胃肠道中被代谢的量,进一步去探讨P-gpCYP 3A4在肠道中所介导的相互作用。通过对比模拟和实测的结果发现在30-800mg的临床给药范围内,计算机辅助的建模和模拟方法可以很好的诠释和表征UK-343,664的体内非线性药动行为。GastroPlus所模拟预测的AUCCmax和实测值非常的吻合和接近。该模型可以很好的解释和表征UK-343,664在体内的真实药动行为,并且暗示随着剂量的递增,体内呈现非线性的行为可能归功于外排转运体P-gp和肠道代谢酶所引起的。然而,在该浓度范围内P-gp和酶的饱和并不是重叠的,因此导致的体内药动行为和单纯的随剂量递增AUC增加的情况相比有较大的区别。当低剂量的时候,肠腔内的浓度在P-gp拟合的Km之下,P-gp起到保护作用,进行药物的外排,将导致UK-343,664在胃肠道中被3A4首过的代谢量减少,当高剂量的时候,随着P-gp趋于饱和,UK-343,664在胃肠道中被3A4首过的代谢量增加,最后当给药剂量达到最大时,3A4出现饱和,UK-343,664在胃肠道中被3A4首过的代谢量又开始减少,如此复杂的体外体内外推是生理吸收模型突显其价值和意义的另一个代表力作。

8. PK-PD结合模型】:整合体外和临床前的体内数据预测药物在人体的有效剂量和药动行为

Practical Anticipation of Human Efficacious Doses and Pharmacokinetics Using In Vitro and Preclinical In Vivo Data.

Heimbach T, Lakshminarayana SB, Hu W, He H. (2009) AAPS J. 11(3):602-14. (IF: 4.386)

【摘要】在药物早期的研究过程中能否精准的预测人体的PKPD将会起到至关重要的作用,特别是对于有潜力的化合物,我们必须明确它的安全、有效和可调控的给药方案。虽然在人体预期的给药剂量的研究中,成功的整合临床前的PK/PD数据所带来的优越性是得到了公认的。但是制药科学家们在实际的工作中却面临着众多的困难和挑战,尤其是化合物因受到吸收、分布、代谢、排泄和处方性质等影响后最终引发的PK/PD的影响。本文分别对BCS I-IV类药物基于其临床前数据去估算人体的PK/PD,以及通过该模型如何对处方制剂的有效剂量进行估算进行了综述。人体预期给药剂量的案例表明临床前和临床的PK/PD对处方开发的风险评估、先导候选化合物的筛选和临床结果的预测都起到了非常有效的作用。清除率采用异数放大的方法进行估算,人体表观分布容积则采用GastroPlusPBPK模型进行表征。并且对利用肝微粒体的体外代谢数据进行清除率的IVIVE转换从而提高模型预测的准确性进行了讨论。整合先导化合物临床PK/PD和制剂的信息通过“反向药理学策略”的案例可以最大限度的减少PK/PD预测不确定性。生理模拟软件GastroPlus可以用来指导临床前的处方设计和估算人体的PK/PD,从而便于进行化合物的筛选和对后期药物的发展进行风险评估等工作。

9. 【特殊人群】:通过PBPK模型模拟比索洛尔在健康人和肾功能损伤的患者中的PK

Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling

Guo-fu LI, Kun WANG, Rui CHEN et al. (2012) Acta Pharmacol Sin .33: 1359–1371. (IF: 2.354)

【摘要】目的:建立和评估比索洛尔的PBPK模型,并且分别模拟比索洛尔在健康人和肾功能损伤的患者中的体内暴露和处置情况。

方法:采用GastroPlus搭建比索洛尔的生理PBPK模型,该模型分别由14个组织隔室组成,每个组织分别为灌流限速组织。比索洛尔的吸收和组织分布分别通过GastroPlus的高级隔室吸收和转运模型(ACAT)和处置模型PBPK来预测的,该模型的搭建主要基于每个组织的数学模型和药物来自文献报道的基本特性,如logP、通透性、血浆蛋白结合率。肾脏和肝脏的清除率是通过经验性的放大方法估算获取,并整合到整体的生理PBPK模型中用于模拟。通过搭建好的初始模型首先分别模拟了比索洛尔经IVPO给药后在健康人体内的PK,通过对比模拟和实测的结果对初始模型进行优化。最终优化后的模型联合蒙地卡罗(Monte Carlo)的模拟方法预测了比索洛尔在虚拟的健康人群和肾功能损伤的病人人群中的PK和变异性。

结果:经IVPO给药后,在比索洛尔临床报道的多个剂量水平下,通过模型预测的结果和实测的数据都保持非常好的一致性。单次口服给予5mg20mg,模型预测的AUC, Cmax,Tmax均在1.3倍的误差范围内,连续7天口服给予比索洛尔后,无论是健康人群还是肾功能不全的患者,模拟的结果和实测的结果均有很好的吻合。

结论:PBPK模型可以成功的预测比索洛尔经IVPO给药后分别在健康人和肾功能不全的患者中的PK

10. 【儿科用药】:建立奥司他韦的机制性模型并模拟其在新生儿和婴幼儿体内的PK行为

Development of a Physiologically Based Model for Oseltamivir and Simulation of Pharmacokinetics in Neonates and Infants

Parrott N, Davies B, Hoffmann G, et al. (2011) Clin Pharmacokinet.50(9):613-23. (IF: 6.109)

【摘要】背景:在病患人群如儿童人群体内进行药物治疗及方案设定一直是一个挑战,生理药代动力学模型(PBPK)或许在开发这方面的应用有一定的作用。本研究描述了PBPK模型的一些应用策略,以给新生儿和婴幼儿静脉注射神经氨酸苷酶抑制剂奥司他韦治疗流行性感冒作为研究对象。

方法:分别在狨猴在人体内建立了奥司他韦及其代谢产物奥司他韦羧酸盐(OC)PBPK模型。这些模型整合了药物的理化性质及体外代谢数据以描述其PK过程的机制性特征。建模过程包括了吸收、全身分布、肾脏排泄、前药的代谢转换、OC在肝脏处置中的渗透性限速步骤,以及所有这些过程年龄依赖型特点。模型优化是通过静脉和口服之后,对比预测及实测成年及新生狨猴血浆及肝脏中药物浓度差异来进行的。在人体模型中,模拟结果也与健康成人静脉及口服的临床数据进行比对;同时还比对了新生儿和婴幼儿口服数据。最后,预测了静脉给药后在新生儿体内的暴露。

结果:经过优化前药的转换、OC的肝脏处置以及肾脏排泄之后,得到了成年狨猴一个非常好的模拟结果。通过调整年龄依赖型参数,包括降低肝脏代谢酶的分布及肾功能,模型成功模拟出与成年狨猴对比,新生狨猴体内暴露增多的趋势。对于成年人,在静脉及口服给药后,模拟结果与实测数据都能很好地吻合;尽管目前数据有限,但所模拟的1岁儿童及新生儿结果与文献报道的口服给药后数据也比较合理的吻合。模拟在新生儿体内静脉滴注的血浆药时曲线与口服治疗浓度的OC药时曲线非常接近,奥司他韦的暴露量高出实测相同口服剂量的三倍。

结论:本研究介绍了PBPK模型在预测儿童人群PK行为的功能。模拟结果在一定程度上与实测值能够较好地吻合,提示奥司他韦年龄依赖型的PK模型很好地建立起来。

11. Roche经验】:生理的吸收模型在药物研发过程中的应用

Applications of physiologically based absorption models in drug discovery and development.

Parrott N, Lave T. (2008) Mol Pharm. 5(5):760-75. (IF: 4.57)

【摘要】本文综述了应用生理的吸收模型去指导新药的研究和开发。从药物发现阶段先导化合物的优筛到临床前候选化合物的选择,再外推到临床2期药物的研究以及处方的设计和开发,该模型都能一一起到指导和决策的作用,早期模型是通过整合了众多的数据和转化种属之间的生理差异对临床前不同种属的体内行为进行预测的。通过对比模拟的和实测的血药浓度,能够帮助我们分析和发现更多药物在体内所潜在的机制现象。参数敏感性分析(PSA)可以进一步探讨关键性因素对化合物吸收的不确定性影响,指出哪些因素是化合物吸收的限速因素,有助于化合物的评估和后续的发展。对于人体PK的预测,生理模型的预测方法可以提供非常可靠的准确性,基于临床1期的数据进一步优化后的模型对于后期制剂的开发将有着更大的意义和作用。模拟结果的准确性取决于体外方法所产生的体内相关数据的质量和丰富性,如溶解度,通透性等。此外在转运体所介导的体内过程的研究中,生理模型也将起到非常重要的作用。

12. Pfizer应用案例】:采用生理药代动力学模型及经典一房室模型预测口服cMet激酶抑制剂在人体的PK行为

Prediction of Oral Pharmacokinetics of cMet Kinase Inhibitors in Humans: Physiologically Based Pharmacokinetic Model Versus Traditional One-Compartment Model

Yamazaki S, Skaptason J, Romero D, et al. (2011) Drug Metab Dispos. 39(3):383-93. (IF: 3.361)

【摘要】本研究的目的是为了评估生理药代动力学模型(PBPK)对预测口服适量cMet激酶抑制剂血浆药时曲线的准确性;所采用的药物为(R)-3-[1-(2,6-二氯-3--苯基)-乙氧基]-5-(1-哌啶-4-乙烷-1H-吡唑-4-乙烷)-哌啶-2-(PF02341066) 2-[4-(3-喹啉-6-亚甲基-3H-[1,2,3]三唑并[4,5-b]对二氮杂苯-5-乙烷)-吡唑-1-乙烷]-乙醇(PF04217903)。对比了PBPK模型以及基于异速放大的经典一房室模型对PK预测的准确性。蛋白结合在种属间的差异具有一定的线性关系,采用这种相关性进行异速放大来预测清除率是一种比较有代表性的方法,而且相比其它方法来预测人体PK,该方法将更加准确。

与经典一房室模型相比(预测误差分别为1.8倍和1.9),整体的PBPK模型对PF02341066(1.2倍误差)PF04217903(1.3倍误差)AUC预测更加准确。更加重要的是,PBPK模型对PF02341066PF04217903的血浆药时曲线的预测也与实测曲线比较一致,可以观察到实测曲线的多指数下降趋势,进而在半衰期(t1/2)的预测方面也就更加精确了:对PF02341066PF04217903来说,实测值分别为10小时和12小时,预测值分别为6.6小时和6.3小时;而采用经典一房室模型预测的t1/2分别为17小时和1.9小时。因此,相比经典一房室模型来说,PBPK模型对PF02341066PF04217903PK预测来说是一个更加有用和可信的方法。总之,当前这个研究通过实例展示了PBPK模型可以用于人体PK的预测。

中国客户采用GastroPlus 软件发表的部分文献列表

英文文献:

001 PBPK modeling and simulation in drug research and development. IF=3.138
Zhuang X, Lu C. (2016) Acta Pharmaceutica Sinica B June 23

002 Virtual population pharmacokinetic using physiologically based pharmacokinetic model for evaluating bioequivalence of oral lacidipine formulations in dogs. IF=2.106
Yang B, Wu C, Ji B, Wu M, He Z, Shang L, Sun J. (2016) Asian J. Pharm. Sci. Mar 21
003
Application of physiologically based pharmacokinetic modeling in the prediction of pharmacokinetics of bicyclol controlled-release formulation in human. IF=3.35

Wang B, Liu Z, Li D, Yang S, Hu J, Chen H, Sheng L, Li Y. (2015) Eur J Pharm Sci. Jun 24

004 Preclinical pharmacokinetics of TPN729MA, a novel PDE5 inhibitor, and prediction of its human pharmacokinetics using a PBPK model. IF=2.912
Gao ZW Zhu YT, Yu MM, Zan B, Liu J, Zhang YF, Chen XY, Li XN, Zhong DF. (2015) Acta Pharmacol Sin. Dec; 36(12):1528-36.

005 Prediction of Pharmacokinetics and Penetration of Moxifloxacin in Human with Intra-Abdominal Infection Based on Extrapolated PBPK Model. IF=1.544

Zhu L, Yang J, Zhang Y, Wang Y, Zhang J, Zhao Y, Dong W. (2015) Korean J Physiol Pharmacol. Mar;19(2):99-104.
006 
Prediction of the pharmacokinetics and tissue distribution of levofloxacin in humans based on an extrapolated PBPK model. IF=1.68

Zhu L, Zhang Y, Yang J, Wang Y, Zhang J, Zhao Y, Dong W. (2015) Eur J Drug Metab Pharmacokinet. Mar10.

007 Characterization of preclinical in vitro and in vivo ADME properties and prediction of human PK using a physiologically-based pharmacokinetic model for YQA-14, a new dopamine D3 receptor antagonist candidate for treatment of drug addiction. IF=2.457

Liu F, Zhuang X, Yang C, Li Z, Xiong S, Zhang Z, Li J, Lu C, Zhang Z. (2014) Biopharm Drug Dispos. Mar19.

008 Elucidation of Arctigenin Pharmacokinetics After Intravenous and Oral Administrations in Rats:Integration of In Vitro and In Vivo Findings via Semi-mechanistic Pharmacokinetic Modeling. IF=3.819

Gao Q, Zhang Y, Wo S, Zuo Z. (2014) AAPS J. Oct. 2

009 Interspecies prediction of oral pharmacokinetics of different formulations from dogs to human:physiologically based pharmacokinetic modelling combined with biorelevant dissolution. IF=3.289

Wu C, Kou L, Ma P, Gao L, Li B, Li R, Luo C, Shentu J, Hea Z, Sun J. (2015) RSC Adv. 5:19844

010 Profiling Biopharmaceutical Deciding Properties of Absorption of Lansoprazole Enteric-Coated Tablets Using Gastrointestinal Simulation Technology. IF=3.99

Wu C, Sun L, Sun J, Yang Y, Ren C, Ai X, Lian H, He Z. (2013) Int J Pharm. Jun 24

011 Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling. IF=3.166

Li GF, Wang K, Chen R, Zhao HR, Yang J, Zheng QS. (2012) Acta Pharmacol Sin. Oct. 22

中文文献与论文:
[1]吴倩,史爱欣.生理药代动力学模型及其在妊娠妇女用药研究中的应用现状[J].中国临床药理学杂志,2017,33(21):2209-2211.
[2]李丽,杨进波.基于生理的口服吸收模型在仿制药研发中的应用和趋势[J].中国临床药理学与治疗学,2017,22(09):961-965.
[3]张凤妹,王建,李佳妮.国内外阿那曲唑片溶出曲线相似性评价及采用GastroPlus~(TM)建立体内外相关性模型的研究[J].中国现代应用药学,2017,34(09):1272-1276.
[4]李丽,杨进波.基于生理的药代动力学模型在创新药临床研发中的应用进展[J].中国临床药理学杂志,2017,33(17):1728-1732.
[5]李莉,李琬晴,李迎,高静,张慧,孙建绪,郑爱萍.不同粒径黄体酮的制备及评价[J].国际药学研究杂志,2017,44(06):609-615.
[6]陈琳.白芷呋喃香豆素的体内外处置以及基于CYP酶的药物相互作用研究[D].中国人民解放军军事医学科学院,2017.硕博论文
[7]孙晓迪,张伟,胡爽,刘建芳.国产硝苯地平缓释片的体外溶出度和虚拟生物等效性研究[J].中国药师,2017,20(05):791-794.
[8]李佳妮.阿那曲唑及其片剂国家药品标准提高研究[D].浙江工业大学,2016. 硕博论文
[9]汪难喜 翟学佳 朱超然 张新林 吕永宁. 头孢地尼在健康人体中生理药动学模型的建立与应用[J] 《中国药房》2016年 第35期
[10] 张伟.盐酸二甲双胍口服制剂的体外溶出及在比格犬体内的相对生物利用度研究[D].河北医科大学,2016.硕博论文
[11]高广宇,梅丹宇,喻芳邻,余惟平,王汝涛,龚伟,梅兴国.新型抗脑卒中化合物TID-101自微乳制剂大鼠体内生物利用度研究[J].国际药学研究杂志,2016,43(04):731-735.
[12]高广宇.TID-101自微乳化释药系统的研究[D].中国人民解放军军事医学科学院,2016. 硕博论文
[13]许羚,李禄金,王鲲等. 新药早期临床试验中的定量药理学方法[J]. 中国新药杂质2015, 24(1): 52-58
[14]李小东,陈悦,李煜,洪利娅.采用GastroPlus~(TM)软件评估甲磺酸多沙唑嗪缓释片的体内外溶出特征[J].中国现代应用药学,2016,33(01):71-75.
[15]吴亮.应用生理药动学模型对甲氨蝶呤在儿童体内药动学的预测及验证[D].西南交通大学,2015.
[16]于明明,高志伟,陈笑艳,钟大放.采用生理药动学模型预测抗肿瘤新药法米替尼在人体中的药动学[J].药学学报,2014,49(12):1684-1688.
[17]潘瑞雪,高源,陈万里,李玉兰,胡昌勤.溶出度实验结合计算机模拟技术评价国产阿莫西林胶囊的生物等效性[J].药学学报,2014,49(08):1155-1161.
[18]潘瑞雪,余方键,邹文博,胡昌勤.用GastroPlus软件模拟技术评价头孢地尼胶囊制剂的有效性[J].中国新药杂志,2014,23(13):1506-1513.
[19]安佃云.磷酸川芎嗪渗透泵片应用GastroPlusTM软件的模拟及处方优化[D].山东中医药大学,2014.硕博论文
[20]胡昌勤,潘瑞雪.溶出度试验评价/预测固体口服制剂生物等效性的研究进展[J].中国新药杂志,2014,23(01):44-51.
[21]李桦,庄笑梅.药代动力学人体预测及其在新药研发中的应用[J].中国药理学与毒理学杂志,2013,27(04):611-615.
[22]潘瑞雪.溶出度实验结合计算机模拟技术评价国产β-内酰胺类抗生素的生物等效性[D].中国食品药品检定研究院,2013.
[23]姜伟明.GastroPlus~(TM)软件在药物模型构建、人体血浆清除率预测和临床试验处方设计中的应用[D].上海交通大学,2013.
[24]胡昌勤.对抗生素药品评价性抽验基本思路与方法的思考[J].中国抗生素杂志,2013,38(01):1-11.
[25]孙乐.基于BCS系统的insilico/invitro模型评价药物及制剂的BA/BE[D].沈阳药科大学,2013.

采用GastroPlus发表的部分文献

Gastrointestinal behavior and ADME phenomena: II. In silico simulation.
Lamberti G, Cascone S, Marra F, Titomanlio G, d’Amore M, Barba AA. (2016) J Drug Del. Sci. and Tech. 35:165

Folate-targeted amphiphilic cyclodextrin.siRNA nanoparticles for prostate cancer therapy exhibit PSMA mediated uptake, therapeutic gene silencing in vitro and prolonged circulation in vivo.
Evans JC, Malhotra M, Guo J, O'Shea JP, Hanrahan K, O'Neill A, Landry W, Griffin BT, Darcy R, Watson RW, O'Driscoll CM. (2016) Nanomedicine. Jul 4

Physiologically Based Absorption Modeling to Design Extended-Release Clinical Products for an Ester Prodrug.
Ding X, Day JS, Sperry DC. (2016) AAPS J. Jul 12

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

Development of In Vitro In Vivo Correlation Models for Clopidogrel Tablets to Describe Administration Under Fasting and Fed Conditions.
Savu SN, Silvestro L, Mircioiu C, Anuta V. (2016) Farmacia 64(2):302-312

Use of physiologically relevant biopharmaceutics tools within the pharmaceutical industry and in regulatory sciences: Where are we now and what are the gaps?
Flanagan T, Van Peer A, Lindahl A. (2016) Eur J Pharm Sci. 91:84-90

Pore blocking: An innovative formulation strategy for the design of alcohol resistant multi-particulate dosage forms.
Schrank S, Jedinger N, Wu S, Piller M, Roblegg E. (2016) Int J Pharm. 509(1-2):219-28

PBPK modeling and simulation in drug research and development.
Zhuang X, Lu C. (2016) Acta Pharmaceutica Sinica B June 23

Toward Biopredictive Dissolution for Enteric Coated Dosage Forms.
Al-Gousous J, Amidon GL, Langguth P. (2016) Mol Pharm. May 10

Comparative human in-vivo study of an immediate release tablet over-encapsulated by gelatin and hydroxypropyl methyl cellulose capsules – impact of dissolution rate on bioequivalence.
Stegemann S, Vishwanath S, Kumar R, Cade D, Lowery M, Hutchison K, Michael Morgen M, Goodwin A, Lee C. (2016) Capsugel white paper

Integration of Life-Stage Physiologically-Based Pharmacokinetic (PBPK) Models with Adverse Outcome Pathways (AOPs) and Environmental Exposure Models to Screen for Environmental Hazards.
El-Masri H, Kleinstreuer N, Hines RN, Adams L, Tal T, Isaacs K, Wetmore BA, Tan YM. (2016) Toxicol Sci. May 4

Using Physiologically Based Pharmacokinetic (PBPK) Modelling to Gain Insights into the Effect of Physiological Factors on Oral Absorption in Paediatric Populations.
Villiger A, Stillhart C, Parrott N, Kuentz M. (2016) AAPS J. Apr 8

Use of Modeling and Simulation Tools for Understanding the Impact of Formulation on the Absorption of a Low Solubility Compound: Ciprofloxacin.
Martinez M, Mistry B, Lukacova V, Polli J, Hoag S, Dowling T, Kona R, Fahmy R. AAPS J. Apr 26

The solubility-permeability interplay and oral drug formulation design: Two heads are better than one.
Dahan A, Beig A, Lindley D, Miller JM. (2016) Adv Drug Deliv Rev. Apr 26

In vivo in silico pharmacokinetic simulation studies of carvedilol-loaded nanocapsules using GastroPlus™.
George JK, Singh SK, Verma P. (2016) Ther Deliv. May;7(5):305-18.

Virtual population pharmacokinetic using physiologically based pharmacokinetic model for evaluating bioequivalence of oral lacidipine formulations in dogs.
Yang B, Wu C, Ji B, Wu M, He Z, Shang L, Sun J. (2016) Asian J. Pharm. Sci. Mar 21

Simulated rat intestinal fluid improves oral exposure prediction for poorly soluble compounds over a wide dose range.
Berghausen J, Seiler FH, Gobeau N, Faller B. (2016) 4(1):35-53

Development of a Physiologically Based Pharmacokinetic/Pharmacodynamic Model to Predict the Impact of Genetic Polymorphisms on the Pharmacokinetics and Pharmacodynamics Represented by Receptor/Transporter Occupancy of Central Nervous System Drugs.
Alqahtani S, Kaddoumi A. (2016) Clin Pharmacokinet. Feb 25

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.

Physiologically-Based Pharmacokinetic Modeling in Pediatric Oncology Drug Development.
Rioux N, Waters NJ. (2016) Drug Metab Dispos. Mar 2

Pharmacokinetic evaluation of cefdinir-loaded floating alginate beads in rabbits using LC–MS/MS.
Praveen R, Singh SK, Verma PRP. (2016) J. Pharm. Investigation Mar 5

Clinical Micro-Dose Studies to Explore the Human Pharmacokinetics of Four Selective Inhibitors of Human Nav1.7 Voltage-Dependent Sodium Channels.
Jones HM, Butt RP, Webster RW, Gurrell I, Dzygiel P, Flanagan N, Fraier D, Hay T, Iavarone LE, Luckwell J, Pearce H, Phipps A, Segelbacher J, Speed B, Beaumont K. (2016) Clin Pharmacokinet. Feb 19.

Application of in vitro transmucosal permeability, dose number, and maximum absorbable dose for biopharmaceutics assessment during early drug development for intraoral delivery.
Yang Z, Sotthivirat S, Wu Y, Lalloo A, Nissley B, Manser K, Li H. (2016) Int J Pharm. Feb 20

LC-ESI-MS/MS estimation of loratadine-loaded Self-nanoemulsifying drug delivery systems in rat plasma: pharmacokinetic evaluation and computer simulations by GastroPlus™.
Verma S, Singh SK. (2016) J Pharm Biomedical Anal Feb. 8

Estimating Margin of Exposure to Thyroid Peroxidase Inhibitors Using High-throughput In Vitro Data, High-throughput Exposure Modeling, and Physiologically-Based Pharmacokinetic/Pharmacodynamic Modeling.
Leonard JA, Tan YM, Gilbert M, Isaacs K, El-Masri H. (2016) Toxicol Sci. Feb 10.

Physiologically Based Absorption Modeling to Impact Biopharmaceutics and Formulation Strategies in Drug Development—Industry Case Studies.
Kesisoglou F, Chung J, van Asperen J, Heimbach T. (2016) J Pharm Sci Jan. 23

Disease specific modeling: simulation of the pharmacokinetics of meloxicam and ibuprofen in disease state vs. healthy conditions.
Almukainzi M, Jamali F, Aghazadeh-Habashi A, Löbenberg R. (2016) Eur. J. Pharm. Biopharm. Jan. 2

Absorption, distribution, metabolism, excretion, and kinetics of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)proprionic acid ammonium salt following a single dose in rat, mouse, and cynomolgus monkey.
Gannon SA, Fasano WJ, Mawn MP, Nabb DL, Buck RC, Buxton LW, Jepson GW, Frame SR. (2015) Toxicology. Dec 29.

Solidified SNEDDS of loratadine: formulation using hydrophilic and hydrophobic grades of Aerosil®, pharmacokinetic evaluations and in vivo–in silico predictions using GastroPlus™.
Verma S, Singh SK, Verma PRP. (2016) RSC Adv. 6:3099-3116

Development of a Unified Dissolution and Precipitation Model and Its Use for the Prediction of Oral Drug Absorption.
Jakubiak P, Wagner B, Grimm HP, Petrig-Schaffland J, Schuler F, Alvarez-Sánchez R. (2016) Mol Pharm. Jan 5.

Methodology of oral formulation selection in the pharmaceutical industry.
Kuentz M, Holm R, Elder DP. (2015) Eur J Pharm Sci. Dec 11

Establishment of physiologically based pharmacokinetic model of atorvastatin.
Liu J-B, Zhu L-Q, Zhang Y, Yang J-W. (2015) Chinese J Hospital Pharmacy 35(16):1465-1469

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.

Preclinical pharmacokinetics of TPN729MA, a novel PDE5 inhibitor, and prediction of its human pharmacokinetics using a PBPK model.
Gao ZW Zhu YT, Yu MM, Zan B, Liu J, Zhang YF, Chen XY, Li XN, Zhong DF. (2015)Acta Pharmacol Sin. Dec;36(12):1528-36.

Deciphering nifedipine in vivo delivery from modified release dosage forms: Identification of food effect.
Ilic M, Kovacevic I, Parojcic J. (2015) Acta Pharm. 65:427

In vitro anticancer properties and biological evaluation of novel natural alkaloid jerantinine B.
Qazzaz ME, Raja VJ, Lim KH, Kam TS, Lee JB, Gershkovich P, Bradshaw TD. (2015) Cancer Lett. Oct 26.

Mathematical Model-Based Accelerated Development of Extended-release Metformin Hydrochloride Tablet Formulation.
Chen W, Desai D, Good D, Crison J, Timmins P, Paruchuri S, Wang J, Ha K. (2015) AAPS PharmSciTech Oct. 19

Mitigation of Adverse Clinical Events of a Narrow Target Therapeutic Index Compound through Modified Release Formulation Design: An In Vitro, In Vivo, In Silico, and Clinical Pharmacokinetic Analysis.
Good DJ, Hartley R, Mathias N, Crison J, Tirucherai G, Timmins P, Hussain M, Haddadin R, Koo O, Nikfar F, Fung NK. (2015) Mol Pharm. Nov 4

Absorption, Metabolism, Excretion, and the Contribution of Intestinal Metabolism to the Oral Disposition of [14C]Cobimetinib, a MEK Inhibitor, in Humans.
Takahashi RH, Choo EF, Ma S, Wong S, Halladay J, Deng A, Rooney I, Gates M, Hop CE, Khojasteh SC, Dresser M, Musib L. (2015) Drug Metab Dispos. Oct. 8

Utility of PBPK Absorption Modeling to Guide Modified Release Formulation Development of Gaboxadol, a Highly Soluble Compound with Region-Dependent Absorption.
Kesisoglou F, Balakrishnan A, Manser K. (2015) J Pharm Sci. Oct 12.

Quantitative aspects of drug permeation across in vitro and in vivo barriers.
Krämer SD. (2015) Eur J Pharm Sci. Oct 19.

Development of Physiologically Based Pharmacokinetic/Pharmacodynamic Model for Indomethacin Disposition in Pregnancy.
Alqahtani S, Kaddoumi A. (2015) PLoS One. Oct 2;10(10)

Solidified SNEDDS of loratadine: Formulation using hydrophilic and hydrophobic grades of Aerosil®, pharmacokinetic evaluations and in vivo-in silico predictions using GastroPlus.
Verma S, Kumar Singh S, Verma PRP (2015) RSC Adv. Dec. 4

In vitro-in vivo correlation of parenteral risperidone polymeric microspheres.
Shen J, Choi S, Qu W, Wang Y, Burgess DJ. (2015) J Control Release. Sep 28;218:2-12.

Physicochemical and Pharmacokinetic Characterization of Amorphous Solid Dispersion of Meloxicam with Enhanced Dissolution Property and Storage Stability.
Ochi M, Kimura K, Kanda A, Kawachi T, Matsuda A, Yuminoki K, Hashimoto N. (2015) AAPS PharmSciTech Oct 5

A canine biorelevant dissolution method for predicting in vivo performance of orally administered sustained release matrix tablets.
Walsh PL, Bothe JR, Bhardwaj S, Hu M, Nofsinger R, Xia B, Persak S, Pennington J, Bak A. (2015) Drug Dev Ind Pharm. Sep 4:1-9

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.

Development of a Physiologically Based Pharmacokinetic/Pharmacodynamic Model to Identify Mechanisms Contributing to Entacapone Low Bioavailability.
Alqahtani S, Kaddoumi A. (2015) Biopharm Drug Dispos. Aug 21

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A systematic review of published models, applications and model verification.
Sager JE, Yu J, Raguenau-Majlessi I, Isoherranen N. (2015) Drug Metab Dispos. Aug 21.

Comparison of Deconvolution-Based and Absorption Modeling IVIVC for Extended Release Formulations of a BCS III Drug Development Candidate.
Kesisoglou F, Xia B, Agrawal NG. (2015) AAPS J. Aug 20.

PEGylated y-tocotrienol isomer of vitamin E: Synthesis, characterization, in vitro cytotoxicity, and oral bioavailability.
Abu-Fayyad A, Behery F, Sallam A, Alqahtani S, Ebrahim H, El Sayed KA, Kaddoumi A, Sylvester PW, Carroll JL, Cardelli JA, Nazzal S. (2015) Eur J Pharm Biopharm. Jul 30. pii: S0939-6411(15)00325-2

Lipidic dispersion to reduce food dependent oral bioavailability of fenofibrate: In vitro, in vivo and in silico assessments.
O'Shea JP, Faisal W, Ruane-O'Hora T, Devine KJ, Kostewicz ES, O'Driscoll CM, Griffin BT. (2015) Eur J Pharm Biopharm. Jul 26. pii: S0939-6411(15)00303-3

pH-Dependent Solubility and Dissolution Behavior of Carvedilol-Case Example of a Weakly Basic BCS Class II Drug.
Hamed R, Awadallah A, Sunoqrot S, Tarawneh O, Nazzal S, AlBaraghthi T, Al Sayyad J, Abbas A. (2015) AAPS PharmSciTech. Jul 23

A long-duration dihydroorotate dehydrogenase inhibitor (DSM265) for prevention and treatment of malaria.
Phillips MA, Lotharius J, Marsh K, White J, Dayan A, White KL, Njoroge JW, E Mazouni F, Lao Y, Kokkonda S, Tomchick DR, Deng X, Laird T, Bhatia SN, March S, Ng CL, Fidock DA, Wittlin S, Lafuente-Monasterio M, Benito FJ, Alonso LM, Martinez MS, Jimenez-Diaz MB, Bazaga SF, Angulo-Barturen I, Haselden JN, Louttit J, Cui Y, Sridhar A, Zeeman AM, Kocken C, Sauerwein R, Dechering K, Avery VM, Duffy S, Delves M, Sinden R, Ruecker A, Wickham KS, Rochford R, Gahagen J, Iyer L, Riccio E, Mirsalis J, Bathhurst I, Rueckle T, Ding X, Campo B, Leroy D, Rogers MJ, Rathod PK, Burrows JN, Charman SA. (2015) Sci Transl Med. Jul 15;7(296):296ra111

Assessment of In Vivo Clinical Product Performance of a Weak Basic Drug by Integration of In Vitro Dissolution Tests and Physiologically Based Absorption Modeling.
Ding X, Gueorguieva I, Wesley JA, Burns LJ, Coutant CA. (2015) AAPS J. Jul 1.

Acute toxicity prediction in multiple species by leveraging mechanistic ToxCast mitochondrial inhibition data and simulation of oral bioavailability.
Bhhatarai B, Wilson DM, Bartels MJ, Chaudhuri S, Price PS, Carney EW. (2015) Toxicol Sci. Jul 2.

In vitro-in vivo correlations: general concepts, methodologies and regulatory applications.
González-García I, Mangas-Sanjuán V, Merino-Sanjuán M, Bermejo M. (2015) Drug Dev Ind Pharm. Jul 2:1-13.

Pharmacometric Models for Characterizing the Pharmacokinetics of Orally Inhaled Drugs.
Borghardt JM, Weber B, Staab A, Kloft C. (2015) AAPS J. Jul;17(4):853-70

Preclinical pharmacokinetic studies of 3-deazaneplanocin A, a potent epigenetic anticancer agent, and its human pharmacokinetic prediction using GastroPlus™.
Sun F, Lee L, Zhang Z, Wang X, Yu Q, Duan X, Chan E. (2015) Eur J Pharm Sci. Jun 25.

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 - See more at: http://www.simulations-plus.com/publication.aspx?pID=11#sthash.10kckxY3.dpuf

 

Application of Absorption Modeling in Rational Design of Drug Product Under Quality-by-Design Paradigm.

Kesisoglou F, Mitra A. (2015) AAPS J. May 22.

Development and validation of in vitro-in vivo correlation (IVIVC) for estradiol transdermal drug delivery systems.
Yang Y, Manda P, Pavurala N, Khan MA, Krishnaiah YS. (2015) J Control Release. May 13;210:58-66.

Application of Physiologically Based Absorption Modeling for Amphetamine Salts Drug Products in Generic Drug Evaluation.
Babiskin AH, Zhang X. (2015) J Pharm Sci. May 13.

Prediction of pH dependent absorption using in vitro, in silico, and in vivo rat models: Early liability assessment during lead optimization.
Saxena A, Shah D, Padmanabhan S, Gautam SS, Chowan GS, Mandlekar S, Desikan S. (2015) Eur J Pharm Sci. May 8;76:173-180

In vitro dissolution methodology, mini-Gastrointestinal Simulator (mGIS), predicts better in vivo dissolution of a weak base drug, dasatinib.
Tsume Y, Takeuchi S, Matsui K, Amidon GE, Amidon GL. (2015) Eur J Pharm Sci. May 12;76:203-212.

Prediction of the pharmacokinetics and tissue distribution of levofloxacin in humans based on an extrapolated PBPK model.
Zhu L, Zhang Y, Yang J, Wang Y, Zhang J, Zhao Y, Dong W. (2015) Eur J Drug Metab Pharmacokinet. Mar 10.

Pharmacometric Models for Characterizing the Pharmacokinetics of Orally Inhaled Drugs.
Borghardt JM, Weber B, Staab A, Kloft C. (2015) AAPS J. Apr 7

Food Effect in Humans: Predicting the Risk Through In Vitro Dissolution and In Vivo Pharmacokinetic Models.

Mathias N, Xu Y, Vig B, Kestur U, Saari A, Crison J, Desai D, Vanarase A, Hussain M. (2015) AAPS J. May 2

 

Prospective Predictions of Human Pharmacokinetics for Eighteen Compounds.

Zhang T, Heimbach T, Lin W, Zhang J, He H. (2015) J Pharm Sci. Feb 17.

Role of Self-Association and Supersaturation in Oral Absorption of a Poorly Soluble Weakly Basic Drug.
Narang AS, Badawy S, Ye Q, Patel D, Vincent M, Raghavan K, Huang Y, Yamniuk A, Vig B, Crison J, Derbin G, Xu Y, Ramirez A, Galella M, Rinaldi FA. (2015) Pharm Res. Feb 28.

Prediction of Pharmacokinetics and Penetration of Moxifloxacin in Human with Intra-Abdominal Infection Based on Extrapolated PBPK Model.
Zhu L, Yang J, Zhang Y, Wang Y, Zhang J, Zhao Y, Dong W. (2015) Korean J Physiol Pharmacol. Mar;19(2):99-104.

Development of a Novel Oral Cavity Compartmental Absorption and Transit Model for Sublingual Administration: Illustration with Zolpidem.
Xia B, Yang Z, Zhou H, Lukacova V, Zhu W, Milewski M, Kesisoglou F. (2015) AAPS J. Feb 26.

Comparison of biorelevant simulated media mimicking the intestinal environment to assess the solubility profiles of poorly soluble drugs.
Prasad D, Gu CH, Kuldipkumar A. (2015) Pharm Dev Technol. Feb 23:1-7

Interspecies prediction of oral pharmacokinetics of different formulations from dogs to human: physiologically based pharmacokinetic modelling combined with biorelevant dissolution.
Wu C, Kou L, Ma P, Gao L, Li B, Li R, Luo C, Shentu J, Hea Z, Sun J. (2015) RSC Adv. 5:19844

Utilizing Physiologically Based Pharmacokinetic Modeling to Inform Formulation and Clinical Development for a Compound with pH-Dependent Solubility.
Chung J, Alvarez-Nunez F, Chow V, Daurio D, Davis J, Dodds M, Emery M, Litwiler K, Paccaly A, Peng J, Rock B, Wienkers L, Yang C, Yu Z, Wahlstrom J. (2015) J. Pharm. Sci. Jan. 15

The potency–insolubility conundrum in pharmaceuticals: Mechanism and solution for hepatitis C protease inhibitors.

Connelly PR, Snyder PW, Zhang Y, McClain B, Quinn BP, Johnston S, Medek A, Tanoury J, Griffith J, Walters WP, Dokou E, Knezic D, Bransford P. (2015) Biophysical Chem. 196:100-108

 

Physiologically based pharmacokinetic modelling in drug discovery and development: A pharmaceutical industry perspective.

Jones HM, Chen Y, Gibson C, Heimbach T, Parrott N, Peters SA, Snoeys J, Upreti VV, Zheng M, Hall SD. (2014) Clin. Pharmacol. Ther. 10.1002/cpt.37

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

Novel Orally Swallowable IntelliCap(®) Device to Quantify Regional Drug Absorption in Human GI Tract Using Diltiazem as Model Drug.
Becker D, Zhang J, Heimbach T, Penland RC, Wanke C, Shimizu J, Kulmatycki K. (2014) AAPS PharmSciTech. Dec;15(6):1490-7.

Dissolution testing combined with computer simulation technology to evaluate the bioequivalence of domestic amoxicillin capsule.
Pan RX, Gao Y, Chen WL, Li YL, Hu CQ. (2014) Yao Xue Xue Bao. Aug;49(8):1155-61.

Model-Based Bioequivalence assessment of a commercial Azithromycin Capsule against Pfizer Zithromax® Tablet marketed in Jamaica
Adebayo AS, McFarlane N (2014) J. Appl. PharmSci. 4(10) 62-68

Biopharmaceutical profiling of new antitumor pyrazole derivatives.
Anuta V, Nitulescu GM, Dinu-Pîrvu CE, Olaru OT. (2014) Molecules. Oct 13;19(10):16381-401

The potency-insolubility conundrum in pharmaceuticals: Mechanism and solution for hepatitis C protease inhibitors.
Connelly PR, Snyder PW, Zhang Y, McClain B, Quinn BP, Johnston S, Medek A, Tanoury J, Griffith J, Walters WP, Dokou E, Knezic D, Bransford P. (2014) Biophysical Chem. Sept. 18

Evaluation of a Three Compartment In Vitro Gastrointestinal Simulator Dissolution Apparatus to Predict In Vivo Dissolution.
Takeuchi S, Tsume Y, Amidon GE, Amidon GL. (2014) J Pharm Sci. Sept 22.

Elucidation of Arctigenin Pharmacokinetics After Intravenous and Oral Administrations in Rats: Integration of In Vitro and In Vivo Findings via Semi-mechanistic Pharmacokinetic Modeling.
Gao Q, Zhang Y, Wo S, Zuo Z. (2014) AAPS J. Oct. 2

Preparation and Evaluation of High Dispersion Stable Nanocrystal Formulation of Poorly Water-Soluble Compounds by Using Povacoat.
Yuminoki K, Seko F, Horii S, Takeuchi H, Teramoto K, Nakada Y, Hashimoto N. (2014) J Pharm Sci. Sep 10.

Application of Absorption Modeling to Predict Bioequivalence Outcome of Two Batches of Etoricoxib Tablets.
Mitra A, Kesisoglou F, Dogterom P. (2014) AAPS PharmSciTech. Sep 3.

Development of nanocrystal formulation of meloxicam with improved dissolution and pharmacokinetic behaviors.
Ochi M, Kawachi T, Toita E, Hashimoto I, Yuminoki K, Onoue S, Hashimoto N. (2014) Int J Pharm. Aug 17;474(1-2):151-156.

Intestinal transport of TRH analogs through PepT1: the role of in silico and in vitro modeling.
Bagul P, Khomane KS, Kesharwani SS, Pragyan P, Nandekar PP, Meena CL, Bansal AK, Jain R, Tikoo K, Sangamwar AT. (2014) J Mol. Recognit. 27:609-617

Improvement of trospium-specific absorption models for fasted and fed states in humans.
Cvijic S, Langguth P. (2014) Biopharm Drug Dispos. Jul 17

 

PEGylated cyclodextrins as novel siRNA nanosystems: Correlations between polyethylene glycol length and nanoparticle stability.

Godinho BM, Ogier JR, Quinlan A, Darcy R, Griffin BT, Cryan JF, Caitriona MO. (2014) Int J Pharm. 473(1-2):105-112

Physiologically Based Absorption Modelling to Predict the Impact of Drug Properties on Pharmacokinetics of Bitopertin.
Parrott N, Hainzl D, Scheubel E, Krimmer S, Boetsch C, Guerini E, Martin-Facklam M. (2014) AAPS J. Jun. 27

Enhanced Solubility and Oral Bioavailability of y-Tocotrienol Using a Self-Emulsifying Drug Delivery System (SEDDS).
Alqahtani S, Alayoubi A, Nazzal S, Sylvester PW, Kaddoumi A. (2014) Lipids Jun 17.

Simulation of the In Vivo Exposure to Ibuprofen Based on In Vitro Dissolution Profiles from Solid Dosage Forms.
Popa DE, Lupuliasa D, Stanescu AA, Barca M, Burcea Dragomiroiu GTA, Miron DS, Radulescu FS. (2014) Farmacia 62(3):483

In vitro – in silico – in vivo drug absorption model development based on mechanistic gastrointestinal simulation and artificial neural networks: Nifedipine osmotic release tablets case study
Ilic M, Duriš J, Kovacevic I, Ibric S, Parojcic J. (2014) Eur J Pharm Sci. Jun 6.

Translational PK/PD modeling for cardiovascular safety assessment of drug candidates: Methods and examples in drug development.
Caruso A, Frances N, Meille C, Greiter-Wilke A, Hillebrecht A, Lave T. (2014) J Pharmacol Toxicol Methods. May 28

Pharmacokinetics of Paracetamol in Göttingen Minipigs: In Vivo Studies and Modeling to Elucidate Physiological Determinants of Absorption.
Suenderhauf C, Tuffin G, Lorentsen H, Grimm HP, Flament C, Parrott N. (2014) Pharm Res. May 3.

Testicular distribution and toxicity of a novel LTA4H inhibitor in rats.
Ward PD, La D. (2014) Toxicol Appl Pharmacol. Apr 22;278(1):26-30

Modelling the Absorption of Metformin with Patients Post Gastric Bypass Surgery.
Almukainzi M, Lukacova V, Löbenberg R. (2014) J Diabetes Metab 5:353

From Bench to Humans: Formulation Development of a Poorly Water Soluble Drug to Mitigate Food Effect.
Pandey P, Hamey R, Bindra DS, Huang Z, Mathias N, Eley T, Crison J, Yan B, Perrone R, Vemavarapu C. (2014) AAPS PharmSciTech. Jan 18.


Application of Physiologically Based Absorption Modeling to Formulation Development of a Low Solubility, Low Permeability Weak Base: Mechanistic Investigation of Food Effect.
Zhang H, Xia B, Sheng J, Heimbach T, Lin TH, He H, Wang Y, Novick S, Comfort A. (2014) AAPS PharmSciTech. Jan 17.

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.

The Biopharmaceutics Classification System: Subclasses for in vivo predictive dissolution (IPD) methodology and IVIVC.
Tsume Y, Mudie DM, Langguth P, Amidon GE, Amidon GL. (2014) Eur J Pharm Sci. Jan 28.

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.

 

Clinical Pharmacokinetics of Buffered Propranolol Sublingual Tablet (Promptol™)—Application of a New “Physiologically Based” Model to Assess Absorption and Disposition.
Wang Y, Wang Z, Zuo Z, Tomlinson B, Lee BT, Bolger MB, Chow MS. (2013) AAPS J. Apr 19

Physiologically Based Pharmacokinetic Modelling to Predict Single- and Multiple-Dose Human Pharmacokinetics of Bitopertin
Parrott N, Hainzl D, Alberati D, Hofmann C, Robson R, Boutouyrie B, Martin-Facklam M. (2013) Clin Pharmacokinet. Apr 17

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

Compartmental absorption modeling and site of absorption studies to determine feasibility of an extended-release formulation of an HIV-1 attachment inhibitor phosphate ester prodrug.
Brown J, Chien C, Timmins P, Dennis A, Doll W, Sandefer E, Page R, Nettles RE, Zhu L, Grasela D. (2013) J Pharm Sci. 102(6):1742-51

Amorphous solid dispersions and nano-crystal technologies for poorly water-soluble drug delivery.
Brough C, Williams RO 3rd. (2013) Int J Pharm. Jun 7

Profiling Biopharmaceutical Deciding Properties of Absorption of Lansoprazole Enteric-Coated Tablets Using Gastrointestinal Simulation Technology.
Wu C, Sun L, Sun J, Yang Y, Ren C, Ai X, Lian H, He Z. (2013) Int J Pharm. Jun 24

Physiologically based pharmacokinetic and pharmacodynamic modeling of an antagonist (SM-406/AT-406) of multiple inhibitor of apoptosis proteins (IAPs) in a mouse xenograft model of human breast cancer.
Zhang T, Li Y, Zou P, Yu JY, McEachern D, Wang S, Sun D. (2013) Biopharm. & Drug Dispos. DOI: 10.1002/bdd.1850

A Simplified PBPK Modeling Approach for Prediction of Pharmacokinetics of Four Primarily Renally Excreted and CYP3A Metabolized Compounds During Pregnancy.
Xia B, Heimbach T, Gollen R, Nanavati C, He H. (2013) AAPS J. Jul 9

In Vitro-In Vivo Correlation of Efavirenz Tablets Using GastroPlus®
Honório TD, Pinto EC, Rocha HV, Esteves VS, Dos Santos TC, Castro HC, Rodrigues CR, de Sousa VP, Cabral LM. (2013) AAPS PharmSciTech Aug. 14

Incorporation of Physiologically Based Pharmacokinetic Modeling in the Evaluation of Solubility Requirements for the Salt Selection Process: A Case Study Using Phenytoin.
Chiang PC, Wong H. (2013) AAPS J. Aug. 14

Utility of Physiologically Based Modeling and Preclinical In Vitro/In Vivo Data to Mitigate Positive Food Effect in a BCS Class 2 Compound.
Xia B, Heimbach T, Lin TH, Li S, Zhang H, Sheng J, He H. (2013) AAPS PharmSciTech Aug. 17

Use of Preclinical Dog Studies and Absorption Modeling to Facilitate Late Stage Formulation Bridging for a BCS II Drug Candidate.
Kesisoglou F. (2013) AAPS PharmSciTech. Sep 11.

Assessing the Risk of pH-Dependent Absorption for New Molecular Entities: A Novel in Vitro Dissolution Test, Physicochemical Analysis, and Risk Assessment Strategy.
Mathias NR, Xu Y, Patel D, Grass M, Caldwell B, Jager C, Mullin J, Hansen L, Crison J, Saari A, Gesenberg C, Morrison J, Vig BS, Raghavan K. (2013) Mol Pharm. Sep 13.

Investigation of clinical pharmacokinetic variability of an opioid antagonist through physiologically based absorption modeling.
Ding X, He M, Kulkarni R, Patel N, Zhang X. (2013) J Pharm Sci. 102(8):2859-74

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

Effects of novel cathepsin K inhibitor ONO-5334 on bone resorption markers: a study of four sustained release formulations with different pharmacokinetic patterns.
Tanaka M, Hashimoto Y, Sekiya N, Honda N, Deacon S, Yamamoto M. (2013) J Bone Miner Metab. Oct 11

Biowaiver approach for biopharmaceutics classification system class 3 compound metformin hydrochloride using in silico modeling.
Crison JR, Timmins P, Keung A, Upreti VV, Boulton DW, Scheer BJ. (2012) J. Pharm. Sci. Feb. 14

In Silico Modeling for the Nonlinear Absorption Kinetics of UK-343,664: A P-gp and CYP3A4 Substrate.
Abuasal BS, Bolger MB, Walker DK, Kaddoumi A. (2012) Mol. Pharm. Feb. 2

Novel physiologically based pharmacokinetic modeling of patupilone for human pharmacokinetic predictions.
Xia B, Heimbach T, Lin T, He H, Wang Y, Tan E. (2012) Cancer Chemotherapy and Pharmacology 69(4)

The Use of Modeling Tools to Drive Efficient Oral Product Design.
Mathias NR, Crison J. (2012) AAPS J. May 30

Developability assessment of clinical drug products with maximum absorbable doses.
Ding X, Rose JP, Van Gelder J. (2012) Int. J. Pharm. 427(2):260-9

Parameters for pyrethroid insecticide QSAR and PBPK/PD models for human risk assessment.
Knaak JB, Dary CC, Zhang X, Gerlach RW, Tornero-Velez R, Chang DT, Goldsmith R, Blancato JN. (2012) Rev. Environ. Contam. Toxicol. 219:1-114

Preclinical Assessment of the Absorption and Disposition of the Phosphatidylinositol 3-Kinase/Mammalian Target of Rapamycin Inhibitor GDC-0980 and Prediction of Its Pharmacokinetics and Efficacy in Human.
Salphati L, Pang J, Plise EG, Lee LB, Olivero AG, Prior WW, Sampath D, Wong S, Zhang X. (2012) Drug Metab. Dispos. 40(9):1785-96

Application of PBPK modeling to predict human intestinal metabolism of CYP3A substrates – An evaluation and case study using GastroPlus™
Heikkinen AT, Baneyx G, Caruso A, Parrott N. (2012) Eur. J. Pharm. Sci. 47(2):375-86

Developing In Vitro–In Vivo Correlation of Risperidone Immediate Release Tablet.
Saibi Y, Sato H, and Tachiki H. (2012) AAPS PharmSciTech June 14

Comparison of in vitro–in vivo release of Risperdal® Consta® microspheres
Rawata A, Bhardwajb U, Burgess DJ. (2012) Int. J. Pharm. 434(1):115-21

Selection of oral bioavailability enhancing formulations during drug discovery.
Zheng W, Jain A, Papoutsakis D, Dannenfelser RM, Panicucci R, Garad S. (2012) Drug Devel. Indus. Pharm. 38(2):235-47

In silico prediction of drug dissolution and absorption with variation in intestinal pH for BCS class II weak acid drugs: ibuprofen and ketoprofen.
Tsume Y, Langguth P, Garcia-Arieta A, Amidon GL. (2012) Biopharm. Drug Dispos. doi: 10.1002/bdd.1800

Circadian Variations in Exsorptive Transport: In Situ Intestinal Perfusion Data and In Vivo Relevance.
Okyar A, Dressler C, Hanafy A, Baktir G, Lemmer B, Spahn-Langguth H. (2012) Chronobiology International 29(4):443-453

Use of In Vitro-In Vivo Correlation to Predict the Pharmacokinetics of Several Products Containing a BCS Class 1 Drug in Extended Release Matrices.
Mirza T, Bykadi SA, Ellison CD, Yang Y, Davit BM, Khan MA. (2012) Pharm. Res. Aug. 22

Predicting feasibility and characterizing performance of extended-release formulations using physiologically based pharmacokinetic modeling.
Brown J, Crison J, Timmins P. (2012) Therapeutic Del. 3(9):1047-59

Pharmacokinetics and Pharmacodynamics of Phase II Drug Metabolizing/Antioxidant Enzymes Gene Response by Anti-cancer Agent Sulforaphane in Rat Lymphocytes
Wang H, Khor TO, Yang Q, Huang Y, Wu TY, Saw CL, Lin W, Androulakis IP, Kong AN. (2012) Mol. Pharm. Aug. 29

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

Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling.
Li GF, Wang K, Chen R, Zhao HR, Yang J, Zheng QS. (2012) Acta Pharmacol Sin. Oct. 22

Nilotinib preclinical pharmacokinetics and practical application toward clinical projections of oral absorption and systemic availability.
Xia B, Heimbach T, He H, Lin TH. (2012) Biopharm Drug Dispos. Oct. 24

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

Single-Dose Safety, Tolerability, and Pharmacokinetics of the Antibiotic GSK1322322, a Novel Peptide Deformylase Inhibitor.
Naderera OJ, Dumont E, Zhuc J, Kurtinecz M, Jones LS. (2013) Antimicrob Agents Chemother. Feb 12

Predicting Pharmacokinetic Profiles Using In Silico Derived Parameters.
Hosea NA, Jones HM. (2013) Mol Pharm. Feb 21

In vitro to in vivo extrapolation and physiologically based modeling of cytochrome P450 mediated metabolism in beagle dog gut wall and liver.
Heikkinen AT, Fowler S, Gray L, Li J, Peng Y, Yadava P, Railkar A, Parrott N. (2013) Mol Pharm. Feb. 25

Application of Target-Mediated Drug Disposition Model to Small Molecule Heat Shock Protein 90 Inhibitors.
Yamazaki S, Shen Z, Jiang Y, Smith BJ, Vicini P. (2013) Drug Metab Dispos. Apr 4

Pharmacokinetics of dietary cancer chemopreventive compound dibenzoylmethane in rats and the impact of nanoemulsion and genetic knockout of Nrf2 on its disposition
Lin, W, Hong JL, Shen G, Wu RT, Wang Y, Huang MT, Newmark HL, Huang Q, Khor TO, Heimbach T, Kong AN. (2011) Biopharm. Drug Dispos. 32:65–75

Development of a physiologically based model for oseltamivir and simulation of pharmacokinetics in neonates and infants.
Parrott N, Davies B, Hoffmann G, Koerner A, Lave T, Prinssen E, Theogaraj E, Singer T. (2011) Clin. Pharmacokinet. 50(9):613-23

The biowaivers extension for BCS Class III drugs: the effect of dissolution rate on on the bioequivalence of BCS Class III IR drugs predicted by computer simulation.
Tsume Y, Amidon GL. (2010) Mol Pharm. 7(4):1235-43

Dissolution modeling of bead formulations and predictions of bioequivalence for a highly soluble, highly permeable drug.
Sperry DC, Thomas SJ, Lobo E. (2010) Mol Pharm. Aug 12.

A pH-Dilution Method for Estimation of Biorelevant Drug Solubility along the Gastrointestinal Tract: Application to Physiologically Based Pharmacokinetic Modeling.
Gao Y, Carr RA, Spence JK, Wang WW, Turner TM, Lipari JM, Miller JM. (2010) Mol Pharm. 7(5):1516-26

In Vitro-In Vivo Correlation for Gliclazide Immediate-Release Tablets Based on Mechanistic Absorption Simulation.
Grbic S, Parojcic J, Ibric S, Djuric Z. (2010) AAPS PharmSciTech. Dec 23

Black tea improves attention and self-reported alertness.
De Bruin EA, Rowson MJ, Van Buren L, Rycroft JA, Owen GN. (2010) Appetite. Dec 21.

Prediction of Oral Pharmacokinetics of cMet Kinase Inhibitors in Humans: Physiologically Based Pharmacokinetic Model versus Traditional One Compartment Model.
Yamazaki S, Skaptason J, Romero D, Vekich S, Jones HM, Tan W, Wilner KD, Koudriakova T. (2010) Drug Metab. Dispos. Nov 23

Utility of Physiologically Based Absorption Modeling in Implementing Quality by Design in Drug Development.
Zhang X, Lionberger RA, Davit BM, Yu LX. (2011) AAPS J. 13(1):59-71

The Application of Physiologically Based Pharmacokinetic Modelling to Understanding the Clinical Pharmacokinetics of UK-369,003.
Watson KJ, Davis J, Jones HM. (2011) Drug Metab Dispos. Mar 30

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

Effect of gastric pH on the pharmacokinetics of a BCS Class II compound in dogs: Utilization of an artificial stomach and duodenum dissolution model and GastroPlus™ simulations to predict absorption.
Bhattachar SN, Perkins EJ, Tan JS, Burns LJ. (2011) J Pharm Sci. Jun 16.

Physiological modeling and assessments of regional drug bioavailability of danoprevir to determine whether a controlled release formulation is feasible.
Reddy MB, Connor A, Brennan BJ, Morcos PN, Zhou A, McLawhon P, Fretland A, Evans P, Smith P, Tran JQ. (2011) Biopharm Drug Dispos. June 9.

Pre-clinical and clinical pharmacokinetics of PF-02413873, a non-steroidal progesterone receptor antagonist.
Bungay PJ, Tweedy S, Howe DC, Gibson KR, Jones HM, Mount NM. (2011) Drug Metab Dispos. May 4

Application of PBPK modelling in drug discovery and development at Pfizer.
Jones HM, Dickins M, Youdim K, Gosset JR, Attkins NJ, Hay TL, Gurrell IK, Logan YR, Bungay PJ, Jones BC, Gardner IB. (2011) Xenobiotica 0(0):1-13

The role of predictive biopharmaceutical modeling and simulation in drug development and regulatory evaluation.
Jiang W, Kim S, Zhang X, Lionberger RA, Davit BM, Conner DP, Yu LX. (2011) Int J Pharm. 418(2):151-60

 

 

 

 

 

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