These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
224 related articles for article (PubMed ID: 17520801)
21. Passive oral drug absorption can be predicted more reliably by experimental than computational models--fact or myth. Linnankoski J; Ranta VP; Yliperttula M; Urtti A Eur J Pharm Sci; 2008 Jul; 34(2-3):129-39. PubMed ID: 18455374 [TBL] [Abstract][Full Text] [Related]
22. Biopartitioning micellar chromatography to predict blood to lung, blood to liver, blood to fat and blood to skin partition coefficients of drugs. Martín-Biosca Y; Torres-Cartas S; Villanueva-Camañas RM; Sagrado S; Medina-Hernández MJ Anal Chim Acta; 2009 Jan; 632(2):296-303. PubMed ID: 19110108 [TBL] [Abstract][Full Text] [Related]
23. In silico prediction of drug solubility: 2. Free energy of solvation in pure melts. Lüder K; Lindfors L; Westergren J; Nordholm S; Kjellander R J Phys Chem B; 2007 Feb; 111(7):1883-92. PubMed ID: 17266352 [TBL] [Abstract][Full Text] [Related]
24. A novel QSPR study of normalized migration time for drugs in capillary electrophoresis by new descriptors: quantum chemical investigation. Riahi S; Beheshti A; Ganjali MR; Norouzi P Electrophoresis; 2008 Oct; 29(19):4027-35. PubMed ID: 18958895 [TBL] [Abstract][Full Text] [Related]
25. Prediction of retention indices of drugs based on immobilized artificial membrane chromatography using Projection Pursuit Regression and Local Lazy Regression. Du H; Watzl J; Wang J; Zhang X; Yao X; Hu Z J Sep Sci; 2008 Jul; 31(12):2325-33. PubMed ID: 18491354 [TBL] [Abstract][Full Text] [Related]
26. Predicting permeability coefficient in ADMET evaluation by using different membranes-interaction QSAR. Liu J; Li Y; Pan D; Hopfinger AJ Int J Pharm; 2005 Nov; 304(1-2):115-23. PubMed ID: 16182478 [TBL] [Abstract][Full Text] [Related]
27. Prediction of drug absorption based on immobilized artificial membrane (IAM) chromatography separation and calculated molecular descriptors. Yen TE; Agatonovic-Kustrin S; Evans AM; Nation RL; Ryand J J Pharm Biomed Anal; 2005 Jul; 38(3):472-8. PubMed ID: 15890485 [TBL] [Abstract][Full Text] [Related]
28. Application of the solvation parameter model in method development for analysis of residual solvents in pharmaceuticals. Liu Y; Hu CQ J Chromatogr A; 2009 Jan; 1216(1):86-91. PubMed ID: 19041980 [TBL] [Abstract][Full Text] [Related]
29. New QSPR study for the prediction of aqueous solubility of drug-like compounds. Duchowicz PR; Talevi A; Bruno-Blanch LE; Castro EA Bioorg Med Chem; 2008 Sep; 16(17):7944-55. PubMed ID: 18701302 [TBL] [Abstract][Full Text] [Related]
30. Linear Solvation Energy Relationships as classifiers in non-target analysis--a capillary liquid chromatography approach. Ulrich N; Schüürmann G; Brack W J Chromatogr A; 2011 Nov; 1218(45):8192-6. PubMed ID: 21968343 [TBL] [Abstract][Full Text] [Related]
31. Development and validation of in silico models for estimating drug preformulation risk in PEG400/water and Tween80/water systems. Crivori P; Morelli A; Pezzetta D; Rocchetti M; Poggesi I Eur J Pharm Sci; 2007 Nov; 32(3):169-81. PubMed ID: 17714921 [TBL] [Abstract][Full Text] [Related]
32. Quantitative structure-pharmacokinetic/pharmacodynamic relationships. Mager DE Adv Drug Deliv Rev; 2006 Nov; 58(12-13):1326-56. PubMed ID: 17092600 [TBL] [Abstract][Full Text] [Related]
33. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. Zhao YH; Le J; Abraham MH; Hersey A; Eddershaw PJ; Luscombe CN; Butina D; Beck G; Sherborne B; Cooper I; Platts JA J Pharm Sci; 2001 Jun; 90(6):749-84. PubMed ID: 11357178 [TBL] [Abstract][Full Text] [Related]
34. Chromatographic estimation of drug disposition properties by means of immobilized artificial membranes (IAM) and C18 columns. Lázaro E; Ràfols C; Abraham MH; Rosés M J Med Chem; 2006 Aug; 49(16):4861-70. PubMed ID: 16884298 [TBL] [Abstract][Full Text] [Related]
35. Evaluating the performances of quantitative structure-retention relationship models with different sets of molecular descriptors and databases for high-performance liquid chromatography predictions. Wang C; Skibic MJ; Higgs RE; Watson IA; Bui H; Wang J; Cintron JM J Chromatogr A; 2009 Jun; 1216(25):5030-8. PubMed ID: 19439313 [TBL] [Abstract][Full Text] [Related]
36. Prediction of gastro-intestinal absorption using multivariate adaptive regression splines. Deconinck E; Xu QS; Put R; Coomans D; Massart DL; Vander Heyden Y J Pharm Biomed Anal; 2005 Oct; 39(5):1021-30. PubMed ID: 16040225 [TBL] [Abstract][Full Text] [Related]
37. Quantitative structure-retention (property) relationships in micellar electrokinetic chromatography. Poole SK; Poole CF J Chromatogr A; 2008 Feb; 1182(1):1-24. PubMed ID: 18207156 [TBL] [Abstract][Full Text] [Related]
38. An interesting relationship between drug absorption and melting point. Chu KA; Yalkowsky SH Int J Pharm; 2009 May; 373(1-2):24-40. PubMed ID: 19429285 [TBL] [Abstract][Full Text] [Related]
39. Quantitative structure-property relationships for pesticides in biopartitioning micellar chromatography. Ma W; Luan F; Zhang H; Zhang X; Liu M; Hu Z; Fan B J Chromatogr A; 2006 Apr; 1113(1-2):140-7. PubMed ID: 16490199 [TBL] [Abstract][Full Text] [Related]
40. An evaluation of the potential of linear and nonlinear skin permeation models for the prediction of experimentally measured percutaneous drug absorption. Brown MB; Lau CH; Lim ST; Sun Y; Davey N; Moss GP; Yoo SH; De Muynck C J Pharm Pharmacol; 2012 Apr; 64(4):566-77. PubMed ID: 22420662 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]