174
Views
27
CrossRef citations to date
0
Altmetric
Review

Computational models to predict aqueous drug solubility, permeability and intestinal absorption

Pages 613-627 | Published online: 30 Nov 2005

Bibliography

  • KENNEDY T: Managing the drug discovery /development interface. Drug Discov. Today (1997) 2:436–444.
  • CLARK DE, GROOTENHUIS PD: Progress in computational methods for the prediction of ADMET properties. Curr. Opin. Drug Discov. Devel. (2002) 5(3):382–390.
  • MODI S: Computational approaches to the understanding of ADMET properties and problems. Drug Discov. Today (2003) 8(14):621–623.
  • VAN DE WATERBEEMD H, GIFFORD E: ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov. (2003) 2(3):192–204.
  • ARTURSSON P, KARLSSON J: Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells. Biochem. Biophys. Res. Commun. (1991) 175(3):880–885.
  • ARTURSSON P, BORCHARDT RT: Intestinal drug absorption and metabolism in cell culture: Caco-2 and beyond. Pharm. Res. (1997) 14(12):1655–1658.
  • LIPINSKI CA, LOMBARDO F, DOMINY BW, FEENY PJ: Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. (1997) 23:3–25.
  • KOLA I, LANDIS J: Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. (2004) 3(8):711–716.
  • CHIOU WL: The rate and extent of oral bioavailability versus the rate and extent of oral absorption: clarification and recommendation of terminology. J. Pharmacokinet. Biopharm. (2001) 28(1):3–6.
  • PAN L, HO Q, TSUTSUI K, TAKAHASHI L: Comparison of chromatographic and spectroscopic methods used to rank compounds for aqueous solubility. J. Pharm. Sci. (2001) 90(4):521–529.
  • TAUB ME, KRISTENSEN L, FROKJAER S: Optimized conditions for MDCK permeability and turbidimetric solubility studies using compounds representative of BCS classes I - IV. Eur. J. Pharm. Sci. (2002) 15(4):331–340.
  • BERGSTRÖM CAS, NORINDER U, LUTHMAN K, ARTURSSON P: Experimental and computational screening models for prediction of aqueous drug solubility. Pharm. Res. (2002) 19(2):182–188.
  • GLOMME A, MÄRZ J, DRESSMAN J: Comparison of a miniaturized shake-flask solubility method with automated potentiometric acid/base titrations and calculated solubilities. J. Pharm. Sci. (2005) 94(1):1–16.
  • PIDGEON C, ONG S, LIU H et al. : IAM chromatography: an in vitro screen for predicting drug membrane permeability. J. Med. Chem. (1995) 38:590–594.
  • ONG S, LIU H, PIDGEON C: Immobilized-artificial-membrane chromatography: measurements of membrane partition coefficient and predicting drug membrane permeability. J. Chromatogr. A (1996) 728(1–2):113–128.
  • KANSY M, SENNER F, GUBERNATOR K: Physicochemical high throughput screening: parallel artificial membrane permeation assay in the description of passive absorption processes. J. Med. Chem. (1998) 41(7):1007–1010.
  • BERMEJO M, AVDEEF A, RUIZ A et al.: PAMPA-a drug absorption in vitro model 7. Comparing rat in situ, Caco-2, and PAMPA permeability of fluoroquinolones. Eur. J. Pharm. Sci. (2004) 21(4):429–441.
  • HIDALGO IJ, RAUB TJ, BORCHARDT RT: Characterization of the human colon carcinoma cell line (Caco-2) as a model system for intestinal epithelial permeability. Gastroenterology (1989) 96(3):736–749.
  • ENGMAN HA, LENNERNÄS H, TAIPALENSUU J, OTTER C, LEIDVIK B, ARTURSSON P: CYP3A4, CYP3A5, and MDR1 in human small and large intestinal cell lines suitable for drug transport studies. J. Pharm. Sci. (2001) 90(11):1736–1751.
  • POLLI JW, WRING SA, HUMPHREYS JE et al. : Rational use of in vitro P-glycoprotein assays in drug discovery. J. Pharmacol. Exp. Ther. (2001) 299(2):620–628.
  • TAVELIN S, MILOVIC V, OCKLIND G, OLSSON S, ARTURSSON P: A conditionally immortilized epithelial cell line for studies of intestinal drug transport. J. Pharmacol. Exp. Ther. (1999) 290(3):1212–1221.
  • TAVELIN S, TAIPALENSUU J, SODERBERG L, MORRISON R, CHONG S, ARTURSSON P: Prediction of the oral absorption of low-permeability drugs using small intestine-like 2/4/A1 cell monolayers. Pharm. Res. (2003) 20(3):397–405.
  • IRVINE JD, TAKAHASHI L, LOCKHART K et al. : MDCK (Madin- Darby canine kidney) cells: a tool for membrane permeability screening. J. Pharm. Sci. (1999) 88(1):28–33.
  • LENNERNÄS H, AHRENSTEDT Ö, HÄLLGREN R, KNUTSON L, RYDE M, PAALZOW L: Regional jejunal perfusion, a new in vivo approach to study oral drug absorption in man. Pharm. Res. (1992) 9:1243–1251.
  • FAGERHOLM U, JOHANSSON M, LENNERNÄS H: Comparison between permeability coefficients in rats and human jejunum. Pharm. Res. (1996) 13:1336–1342.
  • LENNERNÄS H, NYLANDER S, UNGELL A-L: Jejunal permeability: a comparison between the ussing chamber technique and the single-pass perfusion in humans. Pharm. Res. (1997) 14:667–671.
  • UNGELL AL, NYLANDER S, BERGSTRAND S, SJÖBERG A, LENNERNÄS H: Membrane transport of drugs in different regions of the intestinal tract of the rat. J. Pharm. Sci. (1998) 87(3):360–366.
  • KIER LB, HALL LH: Connectivity in structure-activity analysis. Research Studies Press, John Wiley and Sons, Letchworth, UK (1986).
  • KIER LB, HALL LH: An electrotopological-state index for atoms in molecules. Pharm. Res. (1990) 7(8):801–807.
  • MANNHOLD R, REKKER RF, SONNTAG C, TER LAAK AM, DROSS K, POLYMEROPOULOS EE: Comparative evaluation of the predictive power of calculation procedures for molecular lipophilicity. J. Pharm. Sci. (1995) 84(12):1410–1419.
  • ABRAHAM MH: Scales of solute hydrogen-bonding: their construction and application to physicochemical and biochemical processed. Chem. Soc. Rev. (1993) 22:73–83.
  • MANNHOLD R, VAN DE WATERBEEMD H: Substructure and whole molecule approaches for calculating logP. J. Comput. Aided. Mol. Des. (2001) 15(4):337–354.
  • RAEVSKY OA, SKVORTSOV VS: 3D hydrogen bond thermodynamics (HYBOT) potentials in molecular modelling. J. Comput. Aided. Mol. Des. (2002) 16(1):1–10.
  • PALM K, STENBERG P, LUTHMAN K, ARTURSSON P: Polar molecular surface properties predict the intestinal absorption of drugs in humans. Pharm. Res. (1997) 14(5):568–571.
  • STENBERG P, LUTHMAN K, ARTURSSON P: Prediction of membrane permeability to peptides from calculated dynamic molecular surface properties. Pharm. Res. (1999) 16(2):205–212.
  • STENBERG P, NORINDER U, LUTHMAN K, ARTURSSON P: Experimental and computational screening models for the prediction of intestinal drug absorption. J. Med. Chem. (2001) 44(12):1927–1937.
  • VAN DE WATERBEEMD H, KANSY M: Hydrogen-bonding capacity and brain penetration. Chimia (1992) 46:299–303.
  • WINIWARTER S, BONHAM NM, AX F, HALLBERG A, LENNERNÄS H, KARLEN A: Correlation of human jejunal permeability (in vivo) of drugs with experimentally and theoretically derived parameters. A multivariate data analysis approach. J. Med. Chem. (1998) 41(25):4939–4949.
  • ERTL P, ROHDE B, SELZER P: Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. J. Med. Chem. (2000) 43(20):3714–3717.
  • CRUCIANI G, PASTOR M, GUBA W: VolSurf: a new tool for the pharmacokinetic optimization of lead compounds. Eur. J. Pharm. Sci. (2000) 11(Suppl. 2):S29–S39.
  • NORINDER U, OSTERBERG T, ARTURSSON P: Theoretical calculation and prediction of Caco-2 cell permeability using MolSurf parametrization and PLS statistics. Pharm. Res. (1997) 14(12):1786–1791.
  • NORINDER U, OSTERBERG T, ARTURSSON P: Theoretical calculation and prediction of intestinal absorption of drugs in humans using MolSurf parametrization and PLS statistics. Eur. J. Pharm. Sci. (1999) 8(1):49–56.
  • CLARK DE: Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood.brain barrier penetration. J. Pharm. Sci. (1999) 88(8):815–821.
  • CLARK DE: Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. J. Pharm. Sci. (1999) 88(8):807–814.
  • MOTULSKY H: Intuitive biostatistics. Oxford University Press, Inc., New York, US (1995).
  • HOSKULDSSON A: PLS regression methods. J. Chemometr. (1988) 2:211–228.
  • OPREA TI, GOTTFRIES J: Toward minimalistic modeling of oral drug absorption. J. Mol. Graph. Model. (1999) 17(5–6):261–274.
  • ICHIKAWA H: Hierarchy neural networks as applied to pharmaceutical problems. Adv. Drug Deliv. Rev. (2003) 55(9):1119–1147.
  • WINKLER DA, BURDEN FR: Bayesian neural nets for modeling in drug discovery. Drug Discov. Today: Biosilico (2004) 2(3):104–111.
  • GOMBAR VK, POLLI JW, HUMPHREYS JE, WRING SA, SERABJIT-SINGH CS: Predicting Pglycoprotein substrates by a quantitative structure-activity relationship model. J. Pharm. Sci. (2004) 93(4):957–968.
  • BERGSTROM CAS, LUTHMAN K, ARTURSSON P: Accuracy of calculated pH-dependent aqueous drug solubility. Eur. J. Pharm. Sci. (2004) 22(5):387–398.
  • AJAY A, WALTERS WP, MURCKO MA: Can we learn to distinguish between ’edruglike’ and ’enondrug-like’ molecules? J. Med. Chem. (1998) 41(18):3314–3324.
  • FRIMURER TM, BYWATER R, NAERUM L, LAURITSEN LN, BRUNAK S: Improving the odds in discriminating ’edrug-like’ from ’enon druglike’ compounds. J. Chem. Inf. Comput. Sci. (2000) 40(6):1315–1324.
  • OPREA TI: Property distribution of drugrelated chemical databases. J. Comput. Aided. Mol. Des. (2000) 14(3):251–264.
  • OPREA TI, GOTTFRIES J: Chemography: the art of navigating in chemical space. J. Comb. Chem. (2001) 3(2):157–166.
  • WALTERS WP, MURCKO MA: Prediction of ’edrug-likeness’. Adv. Drug Deliv. Rev. (2002) 54(3):255–271.
  • PICKETT SD, MCLAY IM, CLARK DE: Enhancing the hit-to-lead properties of lead optimization libraries. J. Chem. Inf. Comput. Sci. (2000) 40(2):263–272.
  • HILDEBRAND J: Solubility. XII. Regular solutions. J. Am. Chem. Soc. (1929) 51:66–80.
  • SCATCHARD G: Equilibria in nonelectrolyte solutions in relation to the vapor pressures and densities of the components. Chem. Rev. (1931) 8:321–333.
  • HILDEBRAND JC, SCOTT RL: The solubility of nonelectrolytes. Reinhold Publishing Corporation, New York, US (1950).
  • KAMLET MJ, ABBOUD J-LM, ABRAHAM MH, TAFT RW: Linear solvation energy relationships. 23. A comprehensive collection of the solvatochrominc parameters, γ, α and α, and some methods for simplifying the generalized solvatochromic equation. J. Org. Chem. (1983) 48:2877–2887.
  • KAMLET MJ, DOHERTY RM, ABBOUD J-LM, ABRAHAM MH, TAFT RW: Linear solvation energy relationships: 36. Molecular properties governing solubilities of organic nonelectrolytes in water. J. Pharm. Sci. (1986) 75(4):338–349.
  • BUSTAMANTE P, MARTIN A, GONZALEZ-GUISANDEZ MA: Partial solubility parameters and solvatochromic parameters for predicting the solubility of single and multiple drugs in individual solvents. J. Pharm. Sci. (1993) 82(6):635–640.
  • BUSTAMANTE P, ESCALERA B, MARTIN A, SELLES E: A modification of the extended Hildebrand approach to predict the solubility of structurally related drugs in solvent mixtures. J. Pharm. Pharmacol. (1993) 43:253–257.
  • KAMLET MJ, DOHERTY RM, FISEROVA-BERGEROVA V, CARR PW, ABRAHAM MH, TAFT RW: Solubility properties in biological media 9. Prediction of solubility and partition of organic nonelectrolytes in blood and tissue from solvatochromic parameters. J. Pharm. Sci. (1987) 76(1):14–17.
  • ABRAHAM MH, LE J: The correlation and prediction of the solubility of compounds in water using an amended solvation energy relationship. J. Pharm. Sci. (1999) 88(9):868–880.
  • HANSCH C, QUINLAN JE, LAWRENCE GL: The linear free-energy relationship between partition coefficients and the aqueous solubility of organic liquids. J. Org. Chem. (1968) 33(1):347–350.
  • YALKOWSKY SH, VALVANI SC: Solubility and partitioning I: solubility of nonelectrolytes in water. J. Pharm. Sci. (1980) 69(8):912–922.
  • YALKOWSKY SH: Solubility and partitioning V: dependence of solubility on melting point. J. Pharm. Sci. (1981) 70(8):971–973.
  • YALKOWSKY SH, PINAL R, BANERJEE S: Water solubility: a critique of the solvatochromic approach. J. Pharm. Sci. (1988) 77(1):74–77.
  • YALKOWSKY SH, PINAL R: Estimation of the aqueous solubility of complex organic componds. Chemosphere (1993) 26(7):1239–1261.
  • LI A, YALKOWSKY SH: Solubility of organic solutes in ethanol/water mixtures. J. Pharm. Sci. (1994) 83(12):1735–1740.
  • MYRDAL PB, MANKA AM, YALKOWSKY SH: Aquafac 3: aqueous functional group activity coefficients; application to the estimation of aqueous solubility. Chemosphere (1995) 30(9):1619–1637.
  • RAN Y, YALKOWSKY SH: Prediction of drug solubility by the general solubility equation (GSE). J. Chem. Inf. Comput. Sci. (2001) 41(2):354–357.
  • BERGSTROM CAS, NORINDER U, LUTHMAN K, ARTURSSON P: Molecular descriptors influencing melting point and their role in classification of solid drugs. J. Chem. Inf. Comput. Sci. (2003) 43(4):1177–1185.
  • CLARK M: Generalized fragmentsubstructure- based property prediction method. J. Chem. Inf. Model. (2005) 45(1):30–38.
  • KARTHIKEYAN M, GLEN RC, BENDER A: General melting point prediction based on a diverse compound data set and artificial neural networks. J. Chem. Inf. Model. (2005) 45(3):581–590.
  • MEYLAN WM, HOWARD PH, BOETHLING RS: Improved method for estimating water solubility from octanol/ water partition coefficient. Environ. Toxicol. Chem. (1996) 15(2):100–106.
  • MCFARLAND JW, AVDEEF A, BERGER CM, RAEVSKY OA: Estimating the water solubilities of crystalline compounds from their chemical structures alone. J. Chem. Inf. Comput. Sci. (2001) 41:1355–1359.
  • RAEVSKY OA, TREPALIN SV, TREPALINA HP, GERASIMENKO VA, RAEVSKAJA OE: SLIPPER-2001 - software for predicting molecular properties on the basis of physicochemical descriptors and structural similarity. J. Chem. Inf. Comput. Sci. (2002) 42(3):540–549.
  • AMIDON GL, YALKOWSKY SH, LEUNG S: Solubility of nonelectrolytes in polar solvents II. Solubility of aliphatic alcohols in water. J. Pharm. Sci. (1974) 63(12):1866.
  • JORGENSEN WL, DUFFY EM: Prediction of drug solubility from structure. Adv. Drug Deliv. Rev. (2002) 54(3):355–366.
  • MITCHELL BE, JURS PC: Prediction of aqueous solubility of organic compounds from molecular structure. J. Chem. Inf. Comput. Sci. (1998) 38(3):489–496.
  • WANCHANA S, YAMASHITA F, HASHIDA M: Quantitative structure/ property relationship analysis on aqueous solubility using genetic algorithm-combined partial least squares method. Pharmazie (2002) 57(2):127–129.
  • CATANA C, GAO H, ORRENIUS C, STOUTEN PF: Linear and nonlinear methods in modeling the aqueous solubility of organic compounds. J. Chem. Inf. Model. (2005) 45(1):170–176.
  • BODOR N, HUANG M-J: A new method for the estimation of the aqueous solubility of organic compounds. J. Pharm. Sci. (1992) 81(9):954–960.
  • NELSON TM, JURS PC: Prediction of aqueous solubility of organic compounds. J. Chem. Inf. Comput. Sci. (1993) 34(3):601–609.
  • SUTTER JM, JURS PC: Prediction of aqueous solubility for a diverse set of heteroatom-containing organic compounds using a quantitative structure-property relationship. J. Chem. Inf. Comput. Sci. (1996) 36:100–107.
  • HUUSKONEN J, SALO M, TASKINEN J: Neural network modeling for estimation of the aqueous solubility of structurally related drugs. J. Pharm. Sci. (1997) 86(4):450–454.
  • HUUSKONEN J, SALO M, TASKINEN J: Aqueous solubility prediction of drugs based on molecular topology and neural network modeling. J. Chem. Inf. Comput. Sci. (1998) 38:450–456.
  • HUUSKONEN J, RANTANEN J, LIVINGSTONE D: Prediction of aqueous solubility for a diverse set of organic compounds based on atom-type electrotopological state indices. Eur. J. Med. Chem. (2000) 35(12):1081–1088.
  • HUUSKONEN J: Estimation of aqueous solubility for a diverse set of organic compounds based on molecular topology. J. Chem. Inf. Comput. Sci. (2000) 40(3):773–777.
  • HUUSKONEN J: Estimation of water solubility from atom-type electrotopological state indices. Environ. Toxicol. Chem. (2001) 20(3):491–497.
  • HUUSKONEN J: Estimation of aqueous solubility in drug design. Comb. Chem. High Throughput Screen. (2001) 4(3):311–316.
  • YAFFE D, COHEN Y, ESPINOSA G, ARENAS A, GIRALT F: A fuzzy ARTMAP based on quantitative structure-property relationships (QSPRs) for predicting aqueous solubility of organic compounds. J. Chem. Inf. Comput. Sci. (2001) 41(5):1177–1207.
  • TETKO IV, TANCHUK VY, KASHEVA TN, VILLA AE: Estimation of aqueous solubility of chemical compounds using E-state indices. J. Chem. Inf. Comput. Sci. (2001) 41(6):1488–1493.
  • ENGKVIST O, WREDE P: Highthroughput, in silico prediction of aqueous solubility based on one- and twodimensional descriptors. J. Chem. Inf. Comput. Sci. (2002) 42(5):1247–1249.
  • CHENG A, MERZ KM: Prediction of aqueous solubility of a diverse set of compounds using quantitative structure- property relationships. J. Med. Chem. (2003) 46:3572–3580.
  • VOTANO JR, PARHAM M, HALL LH, KIER LB: New predictors for several ADME/Tox properties: aqueous solubility, human oral absorption, and Ames genotoxicity using topological descriptors. Mol. Div. (2004) 8(4):379–391.
  • BERGSTRÖM CAS, STRAFFORD M, LAZOROVA L, AVDEEF A, LUTHMAN K, ARTURSSON P: Absorption classification of oral drugs based on molecular surface properties. J. Med. Chem. (2003) 46(4):558–570.
  • BERGSTRÖM CAS, WASSVIK CM, NORINDER U, LUTHMAN K, ARTURSSON P: Global and local computational models for prediction of aqueous solubility of drug-like molecules. J. Chem. Inf. Comput. Sci. (2004) 44(4):1477–1488.
  • CONRADI RA, HILGERS AR, HO NF, BURTON PS: The influence of peptide structure on transport across Caco-2 cells. Pharm. Res. (1991) 8(12):1453–1460.
  • CONRADI RA, HILGERS AR, HO NF, BURTON PS: The influence of peptide structure on transport across Caco-2 cells. II. Peptide bond modification which results in improved permeability. Pharm. Res. (1992) 9(3):435–439.
  • REN S, DAS A, LIEN EJ: QSAR analysis of membrane permeability to organic compounds. J. Drug Target. (1996) 4:103–107.
  • PALM K, LUTHMAN K, UNGELL AL et al. : Evaluation of dynamic polar molecular surface area as predictor of drug absorption: comparison with other computational and experimental predictors. J. Med. Chem. (1998) 41(27):5382–5392.
  • CAMENISCH G, ALSENZ J, VAN DE WATERBEEMD H, FOLKERS G: Estimation of permeability by passive diffusion through Caco-2 cell monolayers using the drugs’ lipophilicity and molecular weight. Eur. J. Pharm. Sci. (1998) 6(4):317–324.
  • HJORTH KRARUP L, THOGER CHRISTENSEN I, HOVGAARD L, FROKJAER S: Predicting drug absorption from molecular surface properties based on molecular dynamics simulations. Pharm. Res. (1998) 15(7):972–978.
  • VAN DE WATERBEEMD H, CAMENISCH G, FOLKERS G, CHRETIEN JR, RAEVSKY OA: Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. J. Drug Target. (1998) 6(2):151–165.
  • ÖSTERBERG T, NORINDER U: Prediction of drug transport processes using simple parameters and PLS statistics. The use of ACD/logP and ACD/ChemSketch descriptors. Eur. J. Pharm. Sci. (2001) 12(3):327–337.
  • YAMASHITA F, WANCHANA S, HASHIDA M: Quantitative structure/ property relationship analysis of Caco-2 permeability using a genetic algorithmbased partial least squares method. J. Pharm. Sci. (2002) 91(10):2230–2239.
  • MARRERO PONCE Y, CABRERA PEREZ MA, ROMERO ZALDIVAR V, GONZALEZ DIAZ H, TORRENS F: A new topological descriptors based model for predicting intestinal epithelial transport of drugs in Caco-2 cell culture. J. Pharm. Pharm. Sci. (2004) 7(2):186–199.
  • STENBERG P, LUTHMAN K, ELLENS H et al. : Prediction of the intestinal absorption of endothelin receptor antagonists using three theoretical methods of increasing complexity. Pharm. Res. (1999) 16(10):1520–1526.
  • ZHAO YH, LE J, ABRAHAM MH et al. : Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J. Pharm. Sci. (2001) 90(6):749–784.
  • AGATONOVIC-KUSTRIN S, BERESFORD R, YUSOF AP: Theoretically-derived molecular descriptors important in human intestinal absorption. J. Pharm. Biomed. Anal. (2001) 25(2):227–237.
  • KLOPMAN G, STEFAN LR, SAIAKHOV RD: ADME evaluation: 2. A computer model for the prediction of intestinal absorption in humans. Eur. J. Pharm. Sci. (2002) 17(4–5):253–263.
  • NIWA T: Using general regression and probabilistic neural networks to predict human intestinal absorption with topological descriptors derived from twodimensional chemical structures. J. Chem. Inf. Comput. Sci. (2003) 43(1):113–119.
  • WOLOHAN PR, CLARK RD: Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA. J. Comput. Aided. Mol. Des. (2003) 17(1):65–76.
  • PEREZ MA, SANZ MB, TORRES LR, AVALOS RG, GONZALEZ MP, DIAZ HG: A topological sub-structural approach for predicting human intestinal absorption of drugs. Eur. J. Med. Chem. (2004) 39(11):905–916.
  • SUN H: A universal molecular descriptor system for prediction of logP, logS, logBB and absorption. J. Chem. Inf. Comput. Sci. (2004) 44(2):748–757.
  • XUE Y, LI ZR, YAP CW, SUN LZ, CHEN X, CHEN YZ: Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents. J. Chem. Inf. Comput. Sci. (2004) 44(5):1630–1638.
  • OBATA K, SUGANO K, SAITOH R et al. : Prediction of oral drug absorption in humans by theoretical passive absorption model. Int. J. Pharm. (2005) 293(1–2):183–192.
  • MATSSON P, BERGSTRÖM CAS, NAGAHARA N, TAVELIN S, NORINDER U, ARTURSSON P: Exploring the role of different drug transport routes in permeability screening. J. Med. Chem. (2005) 48(2):604–613.
  • CLARK RD, WOLOHAN PR: Molecular design and bioavailability. Curr. Top. Med. Chem. (2003) 3(11):1269–1288.
  • TURNER JV, MADDALENA DJ, AGATONOVIC-KUSTRIN S: Bioavailability prediction based on molecular structure for a diverse series of drugs. Pharm. Res. (2004) 21(1):68–82.
  • PARROTT N, LAVE T: Prediction of intestinal absorption: comparative assessment of GASTROPLUS and IDEA. Eur. J. Pharm. Sci. (2002) 17(1–2):51–61.
  • AMIDON GL, LENNERNÄS H, SHAH VP, CRISON JR: A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution an in vivo bioavailability. Pharm. Res. (1995) 12(3):413–420.
  • VARMA M, KHANDAVILLI S, ASHOKRAJ Y et al. : Biopharmaceutic classification system: a scientific framework for pharmacokinetic optimization in drug research. Curr. Drug Met. (2004) 5(5):375–388.
  • KASIM NA, WHITEHOUSE M, RAMACHANDRAN C et al. : Molecular properties of WHO essential drugs and provisional biopharmaceutical classification. Mol. Pharm. (2004) 1:85–96.
  • WU CY, BENET LZ: Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm. Res. (2005) 22(1):11–23.
  • LIPINSKI CA: Drug-like properties and the causes of poor solubility and poor permeability. J. Pharmacol. Toxicol. Methods (2000) 44(1):235–249.

Website

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.