193 related articles for article (PubMed ID: 18490437)
1. A combined model for predicting CYP3A4 clinical net drug-drug interaction based on CYP3A4 inhibition, inactivation, and induction determined in vitro.
Fahmi OA; Maurer TS; Kish M; Cardenas E; Boldt S; Nettleton D
Drug Metab Dispos; 2008 Aug; 36(8):1698-708. PubMed ID: 18490437
[TBL] [Abstract][Full Text] [Related]
2. Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: predictions of compounds as precipitants of interaction.
Fahmi OA; Hurst S; Plowchalk D; Cook J; Guo F; Youdim K; Dickins M; Phipps A; Darekar A; Hyland R; Obach RS
Drug Metab Dispos; 2009 Aug; 37(8):1658-66. PubMed ID: 19406954
[TBL] [Abstract][Full Text] [Related]
3. Prediction of human drug-drug interactions from time-dependent inactivation of CYP3A4 in primary hepatocytes using a population-based simulator.
Xu L; Chen Y; Pan Y; Skiles GL; Shou M
Drug Metab Dispos; 2009 Dec; 37(12):2330-9. PubMed ID: 19773538
[TBL] [Abstract][Full Text] [Related]
4. Prediction of in vivo drug-drug interactions from in vitro data : factors affecting prototypic drug-drug interactions involving CYP2C9, CYP2D6 and CYP3A4.
Brown HS; Galetin A; Hallifax D; Houston JB
Clin Pharmacokinet; 2006; 45(10):1035-50. PubMed ID: 16984215
[TBL] [Abstract][Full Text] [Related]
5. General framework for the prediction of oral drug interactions caused by CYP3A4 induction from in vivo information.
Ohno Y; Hisaka A; Ueno M; Suzuki H
Clin Pharmacokinet; 2008; 47(10):669-80. PubMed ID: 18783297
[TBL] [Abstract][Full Text] [Related]
6. Drugs behave as substrates, inhibitors and inducers of human cytochrome P450 3A4.
Zhou SF
Curr Drug Metab; 2008 May; 9(4):310-22. PubMed ID: 18473749
[TBL] [Abstract][Full Text] [Related]
7. Quantitative prediction and clinical observation of a CYP3A inhibitor-based drug-drug interactions with MLN3897, a potent C-C chemokine receptor-1 antagonist.
Lu C; Balani SK; Qian MG; Prakash SR; Ducray PS; von Moltke LL
J Pharmacol Exp Ther; 2010 Feb; 332(2):562-8. PubMed ID: 19889796
[TBL] [Abstract][Full Text] [Related]
8. Prediction of the effect of erythromycin, diltiazem, and their metabolites, alone and in combination, on CYP3A4 inhibition.
Zhang X; Jones DR; Hall SD
Drug Metab Dispos; 2009 Jan; 37(1):150-60. PubMed ID: 18854379
[TBL] [Abstract][Full Text] [Related]
9. Prediction of crizotinib-midazolam interaction using the Simcyp population-based simulator: comparison of CYP3A time-dependent inhibition between human liver microsomes versus hepatocytes.
Mao J; Johnson TR; Shen Z; Yamazaki S
Drug Metab Dispos; 2013 Feb; 41(2):343-52. PubMed ID: 23129213
[TBL] [Abstract][Full Text] [Related]
10. Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.
Youdim KA; Zayed A; Dickins M; Phipps A; Griffiths M; Darekar A; Hyland R; Fahmi O; Hurst S; Plowchalk DR; Cook J; Guo F; Obach RS
Br J Clin Pharmacol; 2008 May; 65(5):680-92. PubMed ID: 18279465
[TBL] [Abstract][Full Text] [Related]
11. Prediction of time-dependent CYP3A4 drug-drug interactions by physiologically based pharmacokinetic modelling: impact of inactivation parameters and enzyme turnover.
Rowland Yeo K; Walsky RL; Jamei M; Rostami-Hodjegan A; Tucker GT
Eur J Pharm Sci; 2011 Jun; 43(3):160-73. PubMed ID: 21540107
[TBL] [Abstract][Full Text] [Related]
12. Predictions of metabolic drug-drug interactions using physiologically based modelling: Two cytochrome P450 3A4 substrates coadministered with ketoconazole or verapamil.
Perdaems N; Blasco H; Vinson C; Chenel M; Whalley S; Cazade F; Bouzom F
Clin Pharmacokinet; 2010 Apr; 49(4):239-58. PubMed ID: 20214408
[TBL] [Abstract][Full Text] [Related]
13. Modeling, prediction, and in vitro in vivo correlation of CYP3A4 induction.
Shou M; Hayashi M; Pan Y; Xu Y; Morrissey K; Xu L; Skiles GL
Drug Metab Dispos; 2008 Nov; 36(11):2355-70. PubMed ID: 18669588
[TBL] [Abstract][Full Text] [Related]
14. Predictive utility of in vitro rifampin induction data generated in fresh and cryopreserved human hepatocytes, Fa2N-4, and HepaRG cells.
Templeton IE; Houston JB; Galetin A
Drug Metab Dispos; 2011 Oct; 39(10):1921-9. PubMed ID: 21771933
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of various static and dynamic modeling methods to predict clinical CYP3A induction using in vitro CYP3A4 mRNA induction data.
Einolf HJ; Chen L; Fahmi OA; Gibson CR; Obach RS; Shebley M; Silva J; Sinz MW; Unadkat JD; Zhang L; Zhao P
Clin Pharmacol Ther; 2014 Feb; 95(2):179-88. PubMed ID: 23995268
[TBL] [Abstract][Full Text] [Related]
16. A novel model for the prediction of drug-drug interactions in humans based on in vitro cytochrome p450 phenotypic data.
Lu C; Miwa GT; Prakash SR; Gan LS; Balani SK
Drug Metab Dispos; 2007 Jan; 35(1):79-85. PubMed ID: 17020957
[TBL] [Abstract][Full Text] [Related]
17. Use of a Physiologically Based Pharmacokinetic Model for Quantitative Prediction of Drug-Drug Interactions via CYP3A4 and Estimation of the Intestinal Availability of CYP3A4 Substrates.
Mano Y; Sugiyama Y; Ito K
J Pharm Sci; 2015 Sep; 104(9):3183-93. PubMed ID: 26045365
[TBL] [Abstract][Full Text] [Related]
18. A mechanistic physiologically based pharmacokinetic-enzyme turnover model involving both intestine and liver to predict CYP3A induction-mediated drug-drug interactions.
Guo H; Liu C; Li J; Zhang M; Hu M; Xu P; Liu L; Liu X
J Pharm Sci; 2013 Aug; 102(8):2819-36. PubMed ID: 23760985
[TBL] [Abstract][Full Text] [Related]
19. Application of Static Models to Predict Midazolam Clinical Interactions in the Presence of Single or Multiple Hepatitis C Virus Drugs.
Cheng Y; Ma L; Chang SY; Humphreys WG; Li W
Drug Metab Dispos; 2016 Aug; 44(8):1372-80. PubMed ID: 27226352
[TBL] [Abstract][Full Text] [Related]
20. IC50-based approaches as an alternative method for assessment of time-dependent inhibition of CYP3A4.
Burt HJ; Galetin A; Houston JB
Xenobiotica; 2010 May; 40(5):331-43. PubMed ID: 20230210
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
