Comprehensive assessment of ADMET risks in drug discovery

Current Pharmaceutical Design

Volumn 15, Issue 19, 2009, Pages 2195-2219

  Wang, Jianling ^a  

^a NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

Author keywords

Absorption; ADMET; Bioavailability; Drugability; Metabolism; Permeability; Profiling; Solubility

Indexed keywords

CYTOCHROME P450; DIGOXIN; DRUG METABOLIZING ENZYME; MIFEPRISTONE; MULTIDRUG RESISTANCE PROTEIN 1; MYCOPHENOLIC ACID; RIFAMPICIN; TRIAZOLAM; WARFARIN; XENOBIOTIC AGENT;

AREA UNDER THE CURVE; BIOTRANSFORMATION; BLOOD BRAIN BARRIER; CELL STRAIN CACO 2; COST EFFECTIVENESS ANALYSIS; COVALENT BOND; DISSOLUTION; DRUG ABSORPTION; DRUG BIOAVAILABILITY; DRUG CLEARANCE; DRUG DISTRIBUTION; DRUG ELIMINATION; DRUG FORMULATION; DRUG METABOLISM; DRUG PENETRATION; DRUG POTENTIATION; DRUG SCREENING; DRUG TRANSPORT; ENZYME INDUCTION; ENZYME INHIBITION; GENOTOXICITY; HIGH THROUGHPUT SCREENING; HUMAN; IC 50; LIVER MICROSOME; LIVER TOXICITY; MAXIMUM PLASMA CONCENTRATION; NONHUMAN; PARTICLE SIZE; PRIORITY JOURNAL; PROCESS OPTIMIZATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; RECEPTOR BINDING; REVIEW; RISK ASSESSMENT; THERMODYNAMICS; TOXICITY TESTING;

ANIMALS; BIOLOGICAL AVAILABILITY; CHEMISTRY, PHARMACEUTICAL; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; HUMANS; PERMEABILITY; PHARMACEUTICAL PREPARATIONS;

EID: 69249141066     PISSN: 13816128     EISSN: None     Source Type: Journal    
DOI: 10.2174/138161209788682514     Document Type: Review

References (273)

1. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev 2004; 3: 711-715.
2. Penzotti JE, Landrum GA, Putta S. Building predictive ADMET models for early decisions in drug discovery. Curr Opin Drug Discov Dev 2004; 7: 49-61.
3. Wang J, Urban L, Bojanic D. Maximising use of in vitro ADMET tools to predict in vivo bioavailability and safety. Expert Opin Drug Metab Toxicol 2007; 3(5): 641-665.
4. Kennedy T. Managing the drug discovery/development interface. Drug Discov Tech 1997; 2: 436-441.
5. Leeson PD, Springthorpe B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 2007; 6: 881-890.
6. Bender A, Jenkins JL, Glick M, Davies JW, Azzaoui K, Jacoby E, et al. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effect from chemical structure. Chem Med Chem 2007; 2: 1-14.
7. Vistoli G, Pedretti A, Testa B. Assessing drug-likeness - what are we missing? Drug Discov Today 2008; 13(7/8): 285-294.
8. Li AP. Building predictive ADMET models for early decisions in drug discovery. Drug Discov Today 2001; 6: 357-366.
9. Kerns EH, Di L. Physicochemical profiling: Overview of the screens. Drug Discov Today Technol 2004; 1(4): 343-348.
10. Thomas VH, Bhattachar S, Hitchingham L, Zocharski P, Naath M, Surendran N, et al. The road map to oral bioavailability: An industrial perspective. Expert Opin Drug Metab Toxicol 2006; 2(4): 591-608.
11. Biller SA, Custer L, Dickinson KE, Durham SK, Gavai A, Hamann LG, et al. The challenge of quality in candidate optimization. In: Borchardt RT, Kerns EH, Lipinski CA, Thakker DR, Wang B Eds. Pharmaceutical profiling in drug discovery for lead selection. AAPS Press 2004; pp. 413-429.
12. Di L, Kerns EH. Application of pharmaceutical profiling assays for optimization of drug-like properties. Curr Opin Drug Discov Dev 2005; 8(4): 495-504.
13. Faller B, Wang J, Zimmerlin A, Bell L, Hamon J, Whitebread S, et al. High-throughput in vitro profiling assays: Lessons learnt from experiences at Novartis. Expert Opin Drug Metab Toxicol 2006; 2(6): 823-833.
14. Lahoz A, Gombau L, Donato MT, Castell JV, Gómez-Lechón MJ. in vitro ADME medium/high-throughput screening in drug preclinical Development. Mini-Rev Med Chem 2006; 6(9): 1053-1062.
15. Wang, J, Faller B. Progress in bioanalytics and automation robotics for ADME screening. In: Testa B, van de Waterbeemd H, Eds, Comprehensive medicinal chemistry (second ed.) ADME-Tox Approaches. Oxford: Elsevier Ltd. 2007; vol. 5: Pp. 341-356.
16. Clark DE. In silico ADMET tools: The dawn of a new generation? Expert Opin Drug Discov (2007); 2(11): 1423-1429.
17. Egan WJ. Computational models for ADME. Ann Rep Med Chem 2007; 42: 449-467.
18. Shaikh SA, Jain T, Sandhu G, Latha N, Jayaram B. From drug target to leads-sketching a physicochemical pathway for lead molecule design in silico. Curr Pharmaceut Dev 2007; 13(34): 3454-3470.
19. Lombardo F, Faller B, Shalaeva M, Tetko I, Tilton S. The good, the bad and the ugly of distribution coefficients: Current status, views and outlook. In: Molecular drug properties-measurement and prediction. Methods and principles in medicinal chemistry. Weinheim. Wiley-VCH Verlag GmbH & Co. KGaA 2008; 37(Molecular Drug Properties) pp. 407-437.
20. Amidon GL, Lennernas H, Shah VP, Crison JR. A theoretical basis for a biopharmaceutics drug classification: The correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res (1995); 12: 413-420.
21. Avdeef A. Absorption and drug development, solubility, permeability and charge state. Hoboken, New Jersey, USA: Wiley-Interscience 2003.
22. Wen B, Fitch WL. Analytical strategies for the screening and evaluation of chemically reactive drug metabolites. Expert Opin Drug Metab Toxicol (2009); 5(1): 39-55.
23. Kerns EH, Di L, Carter GT. in vitro solubility assays in drug discovery. Curr Drug Metab 2008; 9: 879-885.
24. Press B, Grandi DD. Permeability for intestinal absorption: Caco-2 assay and related issues. Curr Drug Metab 2008; 9: 893-900.
25. Weksler BB, Subileau EA, Perrière N, Charneau P, Holloway K, Leveque M et al. Blood-brain barrier-specific properties of a human adult brain endothelial cell line. FASEB J 2005; Sept. doi:10.1096/fj.04-3458fje.
26. Di L, Kerns EH, Carter GT. Strategies to assess blood-brain barrier penetration. Expert Opin Drug Discov 2008; 3(6): 677-687.
27. Wohnsland F, Faller B. High-throughput permeability pH profile and high-throughput alkane/water LogP with artificial membranes. J Med Chem 2001; 44: 923-930.
28. Bergström CAS, Luthman K, Artursson P. Accuracy of calculated pH-dependent aqueous drug solubility. Eur J Pharm Sci 2004; 22(5): 387-398.
29. Wang J, Urban L. The impact of early ADME profiling on drug discovery and development strategy. Drug Discov World 2004; 5: 73-86.
30. Liu R, So SS. Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery 1 aqueous solubility. J Chem Inf Comput Sci 2001; 41: 1633-1639.
31. Chen XQ, Cho SJ, Li Y, Venkatesh S. Prediction of aqueous solubility of organic compounds using a quantitative structure-property relationship. J Pharm Sci 2002; 91(8): 1838-1852.
32. James KC. Solubility and Related Properties. Drugs and the Pharmaceutical Sciences. NewPYork: Marcel Dekker Inc. 1986; vol. 28: pp. 36-52.
33. Yalkowsky SH, Banerjee S. In: Aqueous solubility methods of estimation for organic compounds. New York, Marcel Dekker Inc. 1992; 149-154.
34. Grant DJW, Brittain HG. Solubility of pharmaceutical solids. In: Brittain HB Ed. Drugs and the pharmaceutical sciences (Volume 70). Physical Characterization of Pharmaceutical Solids. New York, Marcel Dekker Inc. 1995; 321-386.
35. Avdeef A, Voloboy D, Foreman A. Dissolution and solubility. In: Testa B, van de Waterbeemd H Eds. Comprehensive medicinal chemistry (second edition) (Volume 5). ADME-Tox approaches. Oxford, UK, Elsevier Ltd. 2007; 399-423.
36. Zhou L, Yang L, Tilton S, Wang J. Development of high throughput equilibrium solubility assay using miniaturized shake-flask method in early drug discovery. J Pharm Sci 2007; 98(11): 3052-3071.
37. Kerns EH. High throughput physicochemical profiling for drug discovery. J Pharma Sci 2001; 90:1838-1858.
38. Glomme A, Marz J, Dressman JB. 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.
39. Chen XQ, Venkatesh S. Miniature device for aqueous and nonaqueous solubility measurements during drug discovery. Pharm Res 2004; 21(10): 1758-1761.
40. 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.
41. Tan H, Semin D, Wacker M, Cheetham J. An automated screening assay for determination of aqueous equilibrium solubility enabling SPR study during drug lead optimization. JALA 2005; 10(6): 364-373.
42. Galia E, Nicolaides E, Horter D, LoÉbenberg R, Reppas C, Dressman JB. Evaluation of various dissolution media for predicting in vivo performance of class I and II drugs. Pharm Res 1998; 15: 698-705.
43. Nicolaides E, Galia E, Efthymiopoulos C, Dressman JB, Reppas C. Forecasting the in vivo performance of four low solubility drugs from their in vitro dissolution data. Pharm Res 1999; 16: 1876-1882.
44. Dressman JB, Reppas C. in vitro - in vivo correlations for lipophilic, poorly water-soluble drugs Eur J Pharm Sci 2000; 11(Suppl. 2): S73-S80.
45. Kostewicz ES, Brauns U, Becker R, Dressman JB. Forecasting the oral absorption behavior of poorly soluble weak bases using solubility and dissolution studies in biorelevant media. Pharm Res 2002; 19: 345-349.
46. Vertzoni M, Pastelli E, Psachoulias D, Kalantzi L, Reppas C. Estimation of intragastric solubility of drugs. Pharm Res 2007; 24(5): 909-917.
47. Levis KA, Lane ME, Corrigan OI. Effect of buffer media composition on the solubility and effective permeability coefficient of ibuprofen. Intl J Pharm 2003; 253(1-2): 49-59.
48. Vertzoni M, Fotaki N, Kostewicz E, Stippler E, Leuner C, Nicolaides E, et al. Dissolution media simulating the intralumenal composition of the small intestine: Physiological issues and practical aspects. J Pharm Pharmacol 2004; 56(4): 453-462.
49. Kalantzi L, Persson E, Polentarutti B, Abrahamsson B, Goumas K, Dressman JB, et al. Canine intestinal contents vs. simulated media for the assessment of solubility of two weak bases in the human small intestinal contents. Pharm Res 2006; 23(6): 1373-1381.
50. Obata K, Sugano K, Machida M, Aso Y. Biopharmaceutics classification by high throughput solubility assay and PAMPA. Drug Dev Industrial Pharmacy 2004; 30(2): 181-185.
51. Wei H, Loebenberg R. Biorelevant dissolution media as a predictive tool for glyburide a class II drug. Eur J Pharm Sci 2006; 29(1): 45-52.
52. Kostewicz ES, Wunderlich M, Brauns U, Becker R, Bock T, Dressman JB. Predicting the precipitation of poorly soluble weak bases upon entry in the small intestine. J Pharm Pharmacol 2004; 56(1): 43-51.
53. Persson EM, Gustafsson AS, Carlsson AS, Nilsson RG, Knutson L, Forsell P, et al. The effects of food on the dissolution of poorly soluble drugs in human and in model small intestinal fluids. Pharm Res 2005; 22(12): 2141-2151.
54. Avdeef A, Berger CM, Brownell C. pH-Metric Solubility. 2: Correlation between the acid-base titration and the saturation shake-flask solubility pH methods. Pharm Res 2000; 17(1): 85-89.
55. Stuart M, Box K. Chasing equilibrium: Measuring the intrinsic solubility of weak acids and bases. Anal Chem 2005; 77(4): 983-990.
56. Chaubal MV. Application of drug delivery technologies in lead candidate selection and optimization. Drug Discov Today 2004; 9(14): 603-609.
57. Neervannan S. Preclinical formulations for discovery and toxicology: physicochemical challenges. Expert Opin Drug Metab Toxicol 2006; 2(5): 715-731.
58. Pouton CW. Formulation of poorly water-soluble drugs for oral administration: Physicochemical and physiological issues and the lipid formulation classification system. Eur J Pharm Sci 2006; 29(3-4): 278-287.
59. Yamashita S, Furubayashi T, Kataoka M, Sakane T, Sezaki H, Tokuda H. Optimized conditions for prediction of intestinal drug permeability using Caco-2 cells. Eur J Pharm Sci 2000; 10(3): 195-204.
60. Mountfield RJ, Senepin S, Schleimer M, Walter I, Bittner B. Potential inhibitory effects of formulation ingredients on intestinal cytochrome P450. Int J Pharm 2000; 211(1-2): 89-92.
61. Wagner D, Spahn-Langguth H, Hanafy A, Koggel A, Langguth P. Intestinal drug efflux: Formulation and food effects. Adv Drug Deliv Rev 2001; 50(Suppl. 1): S13-S31.
62. Merisko-Liversidge E, Liversidge GG, Cooper ER. Nanosizing: A formulation approach for poorly-water-soluble compounds. Eur J Pharm Sci 2003; 18(2): 113-120.
63. Dubey R. Impact of nanosuspension technology on drug discovery & development. Drug Deliv Technol 2006; 6(5): 67-71.
64. Kocbek P, Baumgartner S, Kristl J. Preparation and evaluation of nanosuspensions for enhancing the dissolution of poorly soluble drugs. Int J Pharm 2006; 312(1-2): 179-186.
65. Chen H, Zhang Z, McNulty C, Olbert C, Yoon HJ, Lee JW, et al. A high-throughput combinatorial approach for the discovery of a cremophor EL-free paclitaxel formulation. Pharm Res 2003; 20: 1302-1308.
66. Gardner CR, Almarsson O, Chen H, Morissette S, Peterson M, Zhang Z, et al. Application of high throughput technologies to drug substance and drug product development. Comp Chem Eng 2004; 28(6-7): 943-953.
67. Chan KLA, Kazarian SG. Fourier transform infrared imaging for high-throughput analysis of pharmaceutical formulations. J Comb Chem 2005; 7(2): 185-189.
68. Chan KLA, Kazarian SG. ATR-FTIR spectroscopic imaging with expanded field of view to study formulations and dissolution. Lab on a Chip 2006; 6(7): 864-870.
69. Hitchingham L, Thomas VH. Development of a semi-automated chemical stability system to analyze solution based formulations in support of discovery candidate selection. J Pharm Biomed Anal 2007; 43(2): 522-526.
70. Gould PL. Salt selection for basic drugs. Int J Pharm 1986; 33(1-3): 201-17.
71. Lmarsson O, Hickey MB, Peterson ML, Morissette SL, Soukasene S, McNulty C, et al. High-throughput surveys of crystal form diversity of highly polymorphic pharmaceutical compounds. Crystal Growth Design 2003; 3(6): 927-933.
72. Bauer J, Spanton S, Henry R, Quick J, Dziki W, Porter W, et al. Ritonavir: An extraordinary example of conformational polymorphism. Pharm Res 2001; 18(6): 859-866.
73. Stephenson GA. Structure determination from conventional powder diffraction data: Application to hydrates, hydrochloride salts, and metastable polymorphs. J Pharma Sci 2000; 89(7): 958-966.
74. Suryanarayanan R. X-ray powder diffractometry. Drugs Pharm Sci 1995; 70: 187-221.
75. Bugay DE. Characterization of the solid-state: Spectroscopic techniques. Adv Drug Deliv Rev 2001; 48(1): 43-65.
76. Artursson P, Tavelin S. Caco-2 and emerging alternatives for prediction of intestinal drugVtransport: A general overview. In: van de Waterbeemd H, Lennernas H, Artursson P, Eds. Drug Bioavailability. Wiley-VCH 2003; 72-89.
77. Egan WJ, Merz KM, Baldwin JJ. J Med Chem 2000; 43: 3867-3877.
78. Hämäläinen MD, Frostell-Karlsson A. Predicting the intestinal absorption potential of hits and leads. Drug Discov Today Technol 2004; 1: 397-406.
79. Balimane PV, Han YH, Chong S. Current industrial practices of assessing permeability and P-glycoprotein interaction. AAPS J 2006; 8(1): E1-E13.
80. 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: 1007-1010.
81. Kansy M, Avdeef A, Fischer H. Advances in screening for membrane permeability: High-resolution PAMPA for medicinal chemists. Drug Discov Today Technol 2004; 1(4): 349-355.
82. Avdeef A. The rise of PAMPA. Expert Opin Drug Metab Toxicol 2005; 1(2): 325-342.
83. Faller B. Artificial Membrane Assays to Assess Permeability. Curr Drug Metab 2008; 9: 886-892.
84. Avdeef A, Strafford M, Block E, Balogh MP, Chambliss W, Khan I. Drug absorption in vitro model: Filter-immobilized artificial membranes. 2. Studies of the permeability properties of lactones in piper methysticum forst. Eur J Pharm Sci 2001; 14: 271-280.
85. Sugano K, Hamada H, Machida M, Ushio H, Saitoh K, Terada K. Optimized conditions of bio-mimetic artificial membrane permeability assay. Int J Pharm 2001; 228: 181-188.
86. Zhu C, Jiang L, Chen TM, Hwang KK. A comparative study of artificial membrane permeability assay for high throughput profiling of drug absorption potential. Eur J Med Chem 2003; 37(5): 399-407.
87. Di L, Kerns EH, Fan K, Mcconnell OJ, Carter GT. High throughput artificial membrane permeability assay for blood-brain barrier. Eur J Med Chem 2003; 38: 223-232.
88. Ruell JA, Tsinman O, Avdeef A. PAMPA - a drug absorption in vitro model. 12. Cosolvent method for permeability assays of amiodarone, itraconazole, tamoxifen, terfenadine, and other very insoluble molecules. Chem Pharm Bull 2004; 52: 561-565.
89. Kansy, M, Fischer H, Kratzat K, Senner F, Wagner B, Parrilla I. High-throughput artificial membrane permeability studies in early lead discovery and development. In: Testa B, van de Waterbeemd H, Folkers G, Guy R Eds, Pharmacokinetic optimization in drug research. Verlag Helvetica Chimica Acta 2001; pp. 447-464.
90. Liu H, Sabus C, Carter GT, Du C, Avdeef A, Tischler M. in vitro permeability of poorly aqueous soluble compounds using different solubilizers in the PAMPA assay with liquid chromatography/mass spectrometry detection. Pharm Res 2003; 20(11): 1820-1826.
91. Bendels S, Tsinman O, Wagner B, Lipp D, Parrilla I, Kansy M, et al. PAMPA-excipient classification gradient map. Pharm Res 2006; 23(11): 2525-2535.
92. Balimane PV, Pace E, Chong S, Zhu M, Jemal M, Van Pelt CK. A novel high-throughput automated chip-based nanoelectrospray tandem mass spectrometric method for PAMPA sample analysis. J Pharm Biomed Anal 2005; 39(1-2): 8-16.
93. Mensch J, Noppe M, Adriaensen J, Melis A, Mackie C, Augustijns P, Brewster ME: Novel generic UPLC/MS/MS method for high throughput analysis applied to permeability assessment in early Drug Discovery. J Chromat B Anal Tech Biomed Life Sci 2007; 847(2): 182-187.
94. Lennernas H, Lundgren E. Intestinal and blood-brain drug transport: beyond involvement of a single transport function. Drug Discov Today Technol 2004; 1: 417-422.
95. Ungell AL, Karlsson J. Cell culture in drug discovery: An industrial perspective. In: Van de Waterbeemd H, Lennernas H, Artursson P. Eds, Drug bioavailability. Wiley-VCH 2003; 90-131.
96. Englund G, Rorsman F, Roennblom A, Karlbom U, Lazorova L, Grasjoe J, et al. Regional levels of drug transporters along the human intestinal tract: Co-expression of ABC and SLC transporters and comparison with Caco-2 cells. Euro J Pharm Sci 2006; 29(3-4): 269-277.
97. Ungell A-LB. Caco-2 replace or refine? Drug Discov Today Technol 2004; 1: 423-430.
98. Steffansen B. Nielsen CU, Brodin B, Eriksson AH, Andersen R, Frokjaer S. Intestinal solute carriers: An overview of trends and strategies for improving oral drug absorption. Eur J Pharm Sci 2004; 21(1): 3-16.
99. Sun D, Lennernas H, Welage LS, Barnett JL, Landowski CP, Foster D, et al. Comparison of human duodenum and Caco-2 gene expression profiles for 12,000 gene sequences tags and correlation with permeability of 26 drugs. Pharm Res 2002; 19: 1400-1416.
100. Hilgendorf C, Ahlin G, Seithel A, Artursson P, Ungell AL, Karlsson J. Expression of thirty-six drug transporter genes in human intestine, liver, kidney, and organotypic cell lines. Drug Metab Disp 2007; 35(8): 1333-1340.
101. Volpe DA. Variability in Caco-2 and MDCK cell-based intestinal permeability assays. J Pharm Sci 2007; 97(2): 712-725.
102. Cheng KC, Li C. USS AS. Prediction of oral drug absorption in humans - from cultured cell lines and experimental animals. Expert Opin Drug Metab Toxicol 2008; 4(5): 581-590.
103. Sun H, Chow ECY, Liu S, Du Y, Pang S. The Caco-2 cell monolayer: usefulness and limitations. Expert Opin Drug Metab Toxicol 2008; 4(4): 395-411.
104. Liang E, Chessic K, Yazdanian M. Evaluation of an accelerated Caco-2 cell permeability model. J Pharm Sci 2000; 89(3): 336-345.
105. Alsenz J, Haenel E. Development of a 7-day, 96-well Caco-2 permeability assay with high-throughput direct UV compound analysis. Pharm Res 2003; 20(12): 1961-1969.
106. Lakeram M, Lockley DJ, Sanders DJ, Pendlington R, Forbes B. Paraben transport and metabolism in the biomimetic artificial membrane permeability assay (BAMPA) and 3-day and 21-day Caco-2 cell systems. J Biomol Screening 2007; 12(1): 84-91.
107. Yamashita S, Konishi K, Yamazaki Y, Taki Y, Sakane T, Sezaki H, et al. New and better protocols for a short-term Caco-2 cell culture system. J Pharm Sci 2002; 91(3): 669-679.
108. Miret S, Abrahamse L, de Groene EM. Comparison of in vitro models for the prediction of compound absorption across the human intestinal mucosa. J Biomol Screening 2004; 9(7): 598-606.
109. Saunders KC. Automation and robotics in ADME screening. Drug Discov Today Technol 2004; 1: 373-380.
110. Kerns EH, Di L, Petusky S, Farris M, Ley R, Jupp P. Combined application of parallel artificial membrane permeability assay and Caco-2 permeability assays in drug discovery. J Pharm Sci 2004; 93(6): 1440-1453.
111. Marino AM, Yarde M, Patel H, Chong S, Balimane PV. Validation of the 96 well Caco-2 cell culture model for high throughput permeability assessment of discovery compounds. Int J Pharm 2005; 297(1-2): 235-241.
112. Balimane PV, Patel K, Marino A, Chong S. Utility of 96 well Caco-2 cell system for increasing throughput of P-gp screening in drug discovery. Eur J Pharm Biopharm 2004; 58: 99-105.
113. Tilton S, Lin X, Wang J, Chen XH, He T, Zhang B. Towards prediction of in vivo exposure using a 96-well Caco-2 permeability assay. Submitted.
114. Saha P, Kou JH. Effect of bovine serum albumin on drug permeability estimation across Caco-2 monolayers. Eur J Pharm Biopharm 2002; 54(3): 319-324.
115. Neuhoff S, Artursson P, Zamora I, Ungell AL. Impact of extracellular protein binding on passive and active drug transport across Caco-2 cells. Pharm Res 2006; 23(2): 350-359.
116. Hochman JH, Yamazaki M, Ohe T, Lin JH. Evaluation of drug interactions with P-glycoprotein in drug discovery: in vitro assessment of the potential for drug-drug interactions with P-glycoprotein. Curr Drug Metab 2002; 3(3): 257-273.
117. Varma MVS, Perumal OP, Panchagnula R. Functional role of P-glycoprotein in limiting peroral drug absorption: Optimizing drug delivery. Curr Opin Chem Biol 2006; 10(4): 367-373.
118. Troutman MD, Thakker DR. Efflux ratio cannot assess P-glycoprotein-mediated attenuation of absorptive transport: Asymmetric effect of P-glycoprotein on absorptive and secretory transport across caco-2 cell monolayers. Pharm Res 2003; 20: 1200-1209.
119. Lennernäs H. Modeling gastrointestinal drug absorption requires more in vivo biopharmaceutical data: Experience from in vivo dissolution and permeability studies in humans. Curr Drug Metab 2007; 8: 645-657.
120. Lin X, Tilton S, Wang J. unpublished data
121. Balimane PV, Chong S, Morrison RA. Current methodologies used for evaluation of intestinal permeability and absorption. J Pharmacol Toxicol 2000; 44: 301-312.
122. Irvine JD, Takahashi L, Lockhart K, Cheong J, Tolan JW, Selick HE, et al. MDCK (Madin-Darby canine kidney) cells: A tool for membrane permeability screening. J Pharm Sci 1999; 88: 28-33.
123. Bohets H, Annaert P, Mannens G, Beijsterveldt VL, Anciaux K, Verboven P, et al. Strategies for absorption screening in drug discovery and development. Curr Top Med Chem 2001; 1: 367-383.
124. Varma MVS, Ashokraj Y, Chinmoy SD, Panchagnula R. P-glycoprotein inhibitors and their screening: A perspective from bioavailability enhancement. Pharmacol Res 2003; 48(4): 347-359.
125. Bourdet DL, Thakker DR. Saturable absorptive transport of the hydrophilic organic cation ranitidine in Caco-2 cells: Role of pH-dependent organic cation uptake system and p-glycoprotein. Pharm Res 2006; 23(6): 1165-1177.
126. Varma MVS, Sateesh K, Panchagnula R. Functional role of p-glycoprotein in limiting intestinal absorption of drugs: Contribution of passive permeability to p-glycoprotein mediated efflux transport. Mol Pharm 2005; 2(1): 12-21.
127. Nicolazzo JA, Charman SA, Charman WN. Methods to assess drug permeability across the blood-brain barrier. J Pharm Pharmacol 2006; 58: 281-293.
128. Hitchcock SA, Pennington LD. Structure-brain exposure relationships. J Med Chem 2006; 49(26): 7559-7583.
129. de Lange ECM. Potential role of ABC transporters as a detoxification system at the blood-CSF barrier. Adv Drug Deliv Rev 2004; 56: 1793-1809.
130. Smith QR. A review of blood-brain barrier transport techniques. In: Nag S Ed, The blood-brain barrier: Biology and research protocols. Totowa, Humana Press Inc. 2003; 193-208.
131. Pardridge WM. Transport of small molecules through the blood-brain barrier: Biology and methodology. Adv Drug Deliv Rev 1995; 15: 5-36
132. Garberg P, Ball M, Borg N, Cecchelli R, Fenart L, Hurst RD, et al. In vitro models for the blood-brain barrier. Toxicol in vitro 2005; 19: 299-334.
133. Bonate PL. Animal models for studying transport across the blood-brain barrier. J Neurosci Met 1995; 56: 1-15.
134. Lundquist S, Renftel M. The use of in vitro cell culture models for mechanistic studies and as permeability screens for the blood-brain barrier in the pharmaceutical industry - background and current status in the drug discovery process. Vascul Pharmacol 2002; 38: 355-364.
135. Terasaki T, Ohtsuki S, Hori S, Takanaga H, Nakashima E, Hosoya K. New approaches to in vitro models of blood-brain barrier drug transport. Drug Discov Today 2003; 8: 944-954.
136. Hansen DK, Scott DO, Otis KW, Lunte SM. Comparison of in vitro BBMEC permeability and in vivo CNS uptake by microdialysis sampling. J Pharm Biomed Anal 2002; 27: 945-958.
137. Lundquist S, Renftel M, Brillault J, Fenart L, Cecchelli R, Dehouck MP. Prediction of drug transport through the blood-brain barrier in vivo: A comparison between two in vitro models. Pharm Res 2002; 19: 976-981.
138. Reichel A, Begley DJ, Abbott NJ. An overview of in vitro techniques for blood-brain barrier studies. In: Nag S, Ed. The blood-brain barrier: Biology and research protocols. Totowa: Humana Press Inc. 2003; pp. 307-324.
139. Wang Q, Rager JD, Weinstein K, Kardos PS, Dobson GL, Li J, et al. Evaluation of the MDR-MDCK cell line as a permeability screen for the blood-brain barrier. Int J Pharm 2005; 288: 349-359.
140. Faassen F, Vogel G, Spanings H, Vromans H. Caco-2 permeability, p-glycoprotein transport ratios and brain penetration of heterocyclic drugs. Int J Pharm 2003; 263: 113-122.
141. Doan KMM, Humphreys JE, Webster LO, Wring SA, Shampine LJ, Serabjit-Singh CJ, et al. Passive permeability and P-glycoprotein-mediated efflux differentiate central nervous system (CNS) and non-CNS marketed drugs. J Pharmacol Exp Ther 2002; 303(3): 1029-1037.
142. Summerfield SG, Stevens AJ, Cutler L, Osuna M del Carmen, Hammond B, et al. Improving the in vitro prediction of in vivo central nervous system penetration: Integrating permeability, P-glycoprotein efflux, and free fractions in blood and brain. J Pharmacol Exp Ther 2006; 316(3): 1282-1290.
143. Summerfield SG, Read K, Begley DJ, Obradovic T, Hidalgo IJ, Coggon S, et al. Central nervous system drug disposition: The relationship between in situ brain permeability and brain free fraction. J Pharmacol Exp Ther 2007; 322(1): 205-213.
144. Shitara Y, Horie T, Sugiyama Y. Transporters as a determinant of drug clearance and tissue distribution, Eur J Pharm Sci 2006, 27: 425-446.
145. Sun H, Frassetto L, Benet LZ. Effects of renal failure on drug transport and metabolism. Pharmacol Ther 2006; 109: 1-11.
146. Sica DA. Considerations in drug handling in renal disease. Clin Pharmacokinet 2007; 46(8): 677-679.
147. Nolin TD, Naud J, Leblond FA, Pichette V. Emerging evidence of the impact of kidney disease on drug metabolism and transport, Clin Pharmacol Ther 2008; 83(6): 898-903.
148. Obach RS. The prediction of human clearance from hepatic microsomal metabolism data. Curr Opin Drug Discov Dev 2001; 4: 36-44.
149. Naritomi Y, Terashita S, Kimura S, Suzuki A, Kagayama A, Sugiyama Y. Prediction of human hepatic clearance from in vivo animal experiments and in vitro metabolic studies with liver microsomes from animals and humans. Drug Metab Dispos 2001; 29: 1316-1324.
150. Obach RS, Baxter JG, Liston TE, Silber BM, Jones BC, MacIntyre F, et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther 1997; 283: 46-58.
151. Obach RS. Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: An examination of in vitro halflife approach and nonspecific binding to microsomes. Drug Metab Dispos 1999; 27: 1350-1359.
152. Lau YY, Krishna G, Yumibe NP, Grotz DE, Sapidou E, Norton L, et al. The use of in vitro metabolic stability for rapid selection of compounds in early discovery based on their expected hepatic extraction ratios. Pharm Res 2002; 19: 1606-1610.
153. Wienkers LC, Heath TG. Predicting in vivo drug interactions from in vitro drug discovery data. Nat Rev Drug Disc 2005; 4: 825-833.
154. Lin JH, Wong BK. Complexities of glucuronidation affecting in vitro in vivo extrapolation. Curr Drug Metab 2002; 3: 623-46.
155. Linget JM, du Vignaud P. Automation of metabolic stability studies in microsomes, cytosol and plasma using a 215 Gilson liquid handler. J Pharm Biomed Anal 1999; 19: 893-901.
156. Caldwell GW, Masucci JA, Chacon E. High throughput liquid chromatography-mass spectrometry assessment of the metabolic activity of commercially available hepatocytes from 96-well plates. Comb Chem High Throughput Screen 1999; 2: 39-51.
157. Korfmacher WA, Palmer CA, Nardo C, Dunn-Meynell K, Grotz D, Cox K, et al. Development of an automated mass spectrometry system for the quantitative analysis of liver microsomal incubation samples: A tool for rapid screening of new compounds for metabolic stability. Rapid Commun Mass Spectrom 1999; 13: 901-907.
158. Di L, Kerns EH, Gao N, Li SQ, Huang Y, Bourassa JL, et al. Experimental design on single-time-point high-throughput microsomal stability assay. J Pharm Sci 2004; 93(6): 1537-1544.
159. Di L, Kerns EH, Li SQ, Petusky SL. High throughput microsomal stability assay for insoluble compounds. Int J Pharm 2006; 317: 54-60.
160. Mcginnity DF, Soars MG, Urbanowicz RA, Riley RJ. Evaluation of fresh and cryopreserved hepatocytes as in vitro drug metabolism tools for the prediction of metabolic clearance. Drug Metab Dispos 2004; 32: 1247-53.
161. Reddy A, Heimbach T, Freiwald S, Smith D, Winters R, Michael S, et al. Validation of a semi-automated human hepatocyte assay for the determination and prediction of intrinsic clearance in discovery. J Pharm Biomed Anal 2005; 37(2): 319-326.
162. Hewitt NJ, Lechon MJG, Houston JB, Hallifax D, Brown HS, Maurel P, et al. Primary hepatocytes: Current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab Rev 2007; 39(1): 159-234.
163. Ito K, Houston JB. Comparison of the use of liver models for predicting drug clearance using in vitro kinetic data from hepatic microsomes and isolated hepatocytes. Pharm Res 2004; 21(5): 785-792.
164. Soars MG, McGinnity DF, Grime KR, Robert J. The pivotal role of hepatocytes in drug discovery. Chem.-Biolog Interactions 2007; 168(1): 2-15.
165. Blanchard N, Alexandre E, Abadie C, Lave T, Heyd B, Mantion G, et al. Comparison of clearance predictions using primary cultures and suspensions of human hepatocytes. Xenobiotica 2005; 35(1):1-15.
166. Soars MG, Burchell B, Riley RJ. in vitro analysis of human drug glucuronidation and prediction of in vivo metabolic clearance. J Pharm ExpTher 2002; 301: 382-390.
167. Shibata Y, Takahashi H, Chiba M, Ishii Y. Prediction of hepatic clearance and availability by cryopreserved human hepatocytes: An application of serum incubation method. Drug Metab Dispos 2002; 30: 892-896.
168. Lau YY, Sapidou E, Cui X, White RE, Cheng KC. Development of a novel in vitro model to predict hepatic clearance using fresh, cryopreserved and sandwich-cultured hepatocytes. Drug Metab Dispos 2002; 30: 1446-1454.
169. Blanchard N, Hewitt NJ, Silber P, Jones H, Coassolo P, Lave T. Prediction of hepatic clearance using cryopreserved human hepatocytes: A comparison of serum and serumfree incubations. J Pharm Pharmacol 2006; 58(5): 633-641.
170. Jacobson L, Middleton B, Holmgren J, Eirefelt S, Froejd M, Blomgren A, et al. An optimized automated assay for determination of metabolic stability using hepatocytes: Assay validation, variance component analysis, and in vivo relevance. Assay Drug Dev Technol 2007; 5(3): 403-415.
171. Li AP. Human hepatocytes: Isolation, cryopreservation and applications in drug development. Chemico-Biological Interactions 2007; 168(1): 16-29.
172. Jouin D, Blanchard N, Alexandre E, Delobel F, David-Pierson P, Lavé T, et al. Cryopreserved human hepatocytes in suspension are a convenient high throughput tool for the prediction of metabolic clearance. Eur J Pharma Biopharm 2006; 63: 347-355.
173. Soars MG, Grime K, Sproston JL, Webborn PJH, Riley RJ. Use of hepatocytes to assess the contribution of hepatic uptake to clearance in vivo. Drug Metab Dispos 2007; 35(6): 859-865.
174. Liu X, Chism JP, LeCluyse EL, Brouwer KR, Brouwer KLR. Correlation of biliary excretion in sandwich-cultured rat hepatocytes and in vivo in rats. Drug Metab Dispos 1999; 27: 637-44.
175. Fagerholm U. Prediction of human pharmacokinetics-biliary and intestinal clearance and enterohepatic circulation. J Pharm Pharmacol 2008; 60: 535-542.
176. Roberts MS, Magnusson BM, Burczynski FJ, Weiss M. Enterohepatic circulation: Physiological, pharmacokinetic and clinical implications. Clin Pharmacokinet 2002; 41(10): 751-790.
177. Ghibellini G, Vasist LS, Leslie EM, Heizer WD, Kowalsky RJ, Calco BF, et al. in vitro-in vivo correlation of hepatobiliary drug clearance in humans. Clin Pharmacol Ther 2007; 81: 406-413.
178. Marion TL, ELeslie EM, Brouwer KLR. Use of sandwich-cultured hepatocytes to evaluate impaired bile acid transport as a mechanism of drug-induced hepatotoxicity. Mol Pharm 2007; 4(6): 911-918.
179. Ghibellini G, Leslie EM, Brouwer KLR. Methods to evaluate biliary excretion of drugs in humans: An updated review. Mol Pharm 2006; 3: 198-211.
180. Bi YA, Kazolias D, Duignan DB. Use of cryopreserved human hepatocytes in sandwich culture to measure hepatobiliary transport. Drug Metab Dispos 2006; 34(9): 1658-1665.
181. Annaert PP, Turncliff RZ, Booth CL, Thakker DR, Brouwer KLR. P-glycoprotein-mediated in vitro biliary excretion in sandwich-cultured rat hepatocytes. Drug Metab Dispos 2001; 29: 1277-1283.
182. Obach RS, Walsky RL, Venkatakrishnan K, Gaman EA, Houston JB, Tremaine LM. The utility of in vitro cytochrome P450 inhibition data in the prediction of drug-drug interactions. J Pharmacol Exp Ther 2006; 316(1): 336-348.
183. Patsalos PN, Perucca E. Clinically important drug interactions in epilepsy: General features and interactions between antiepileptic drugs. Lancet Neurology 2003; 2(6): 347-356.
184. Bjornsson TD, Callaghan JT, Einolf HJ, Fischer V, Gan L, Grimm S, et al. The conduct of in vitro and in vivo drug-drug interaction studies: A Pharmaceutical Research and Manufacturers of America (PhRMA) perspective. Drug Metab Dispos 2003; 31: 815-832.
185. Crespi CL, Miller VP, Penman BW. Microtiter plate assays for inhibition of human, drug-metabolizing cytochromes P450. Anal Biochem 1997; 248: 188-190.
186. Riley RJ, Grime K. Metabolic screening in vitro: Metabolic stability, CYP inhibition and induction. Drug Discov Today Technol 2004; 1: 365-372.
187. Busby WF Jr, Ackermann JM, Crespi CL. Effect of methanol, ethanol, dimethyl sulfoxide, and acetonitrile on in vitro activities of CDNA-expressed human cytochromes P-450. Drug Metabol Dispos 1999; 27: 246-249.
188. Cohen LH, Remley MJ, Raunig D, Vaz ADN. in vitro drug interactions of cytochrome P450: An evaluation of fluorogenic to conventional substrates. Drug Metab Dispos 2003; 31: 1005-1015.
189. Bell L, Bickford S, Nguyen PN, Wang J, He T, Zhang B, et al. Evaluation of fluorescence- and mass spectrometry-based CYP inhibition assays for use in drug discovery. J Biomol Screening 2008; 13: 343-353.
190. Ito K, Hallifax DR, Obach S, Houston BJ. Impact of parallel pathways of drug elimination and multiple cytochrome P450 involvement on drug-drug interactions: CYP2D6 paradigm. Drug Metabol Dispos 2005; 33: 837-844.
191. Hickman D, Wang JP, Wang Y, Unadkat JD. Evaluation of the selectivity of in vitro probes and suitability of organic solvents for the measurement of human cytochrome P450 monooxygenase activities. Drug Metab Dispos 1998; 26(3): 207-215.
192. Kim MJ, Kim H, Cha IJ, Park JS, Shon JH, Liu KH, et al. High-throughput screening of inhibitory potential of nine cytochrome P450 enzymes in vitro using liquid chromatography/tandem mass spectrometry. Rapid Comm Mass Spectro 2005; 19(18): 2651-2658.
193. Riley RJ, Grime K, Weaver R. Time-dependent CYP inhibition. Expert Opin Drug Metab Toxicol 2007; 3(1): 51-66.
194. Polasek TM, Miners JO. in vitro approaches to investigate mechanism based inactivation of CYP enzymes. Expert Opin Drug Metab Toxicol 2007; 3(3): 321-329.
195. Obach RS, Walsky RL, Venkatakrishnan K. Mechanism-based inactivation of human cytochrome P450 enzymes and the prediction of drug-drug interactions. Drug Metab Dispos 2007; 35(2): 246-255.
196. Grime KH, Bird J, Ferguson D, Riley RJ. Mechanism-based inhibition of cytochrome P450 enzymes: An evaluation of early decision making in vitro approaches and drug-drug interaction prediction methods. Eur J Pharm Sci 2009; 36: 175-191.
197. Backman JT, Wang JS, Wen X, Kivisto KT, Neuvonen PJ. Mibefradil but not isradipine substantially elevates the plasma concentrations of the CYP3A4 substrate triazolam. Clin Pharmacol Therap 1999; 66(4): 401-407.
198. Atkinson A, Kenny JR, Grime K. Automated assessment of the time-dependent inhibition of human cytochrome P450 enzymes using liquid chromatography-tandem mass spectrometry analysis. Drug Metab Dispos 2005; 33(11): 1637-1647.
199. Lim HK, Duczak N Jr, Brougham L, Elliot M, Patel M, Chan K. Inactivation of CYP3A4, CYP2C9, CYP2C19, CYP2D6, and CYP1A2 in pooled human liver microsomes. Drug Metab Dispos 2005; 33: 1211-1219.
200. Mayhew BS, Jones DR, Hall SD. An in vitro model for predicting in vivo inhibition of cytochrome P450 3A4 by metabolic intermediate complex formation. Drug Metab Dispos 2000; 28: 1031-1037
201. Villikka K, Kivistii KT, Backman JT, Olkkola KT, Neuvonen PJ. Triazolam is ineffective in patients taking rifampin. Clin Pharmacol Ther 1997; 61(1): 8-14.
202. Lin JH. CYP induction-mediated drug interactions: in vitro assessment and clinical implications. Pharm Res 2006; 23(6): 1089-1116.
203. Wahlstrom JL, Rock DA, Slatter JG, Wienkers LC. Advances in predicting CYP-mediated drug interactions in the drug discovery setting. Expert Opin Drug Discov 2006; 1(7): 677-691.
204. Pelkonen O, Manenpaa J, Taavitsainen P, Rautio A, Rautio H. Inhibition and induction of human cytochrome P450 (CYP) enzymes. Xenobiotics 1998; 28: 1203-1253.
205. Shimada T, Yamazaki H, Mimura M, Inui Y, Guengerich FP. Interindividual variations in human liver cytochromes P450 enzymes involved in the oxidation of drugs, carcinogens and toxic chemicals: Studies with liver microsomes of 30 Japanese and 30 Caucasians. J Pharmacol Exp Ther 1994; 270: 414-423.
206. LeCluyse EL. Human hepatocyte culture systems for the in vitro evaluation of cytochrome P450 expression and regulation. Eur J Pharm Sci 2001; 13: 343-368.
207. Cui X, Thomas A, Han Y, Palamanda J, Montgomery D, White RE, et al. Quantitative PCR assay for cytochromes P450 2B and 3A induction in rat precision-cut liver slices: Correlation study with induction in vivo. J Pharmacol Toxicol Met 2005; 52(2): 234-243.
208. Healan-Greenberg C, Waring JF. Application of new screening methods to assess induction of hepatic drug metabolizing enzymes. Am Pharm Rev 2006; 9(3): 115-118.
209. Mills JB, Rose KA, Sadagopan N, Sahi J, de Morais SM. Induction of drug metabolism enzymes and MDR1 using a novel human hepatocyte cell line. J Pharmacol Exp Ther 2004; 309: 303-309.
210. Willson TM, Kliewer SA. PXR, CAR and drug metabolism. Nat Rev Drug Discov 2002); 1: 259-266.
211. Handschin C, Meyer UA. Induction of drug metabolism: The role of nuclear receptors. Pharmacol Rev 2003; 55: 649-673.
212. El-Sankary W, Gibson GG, Ayrton A, Plant N. Use of a reporter gene assay to predict and rank the potency and efficacy of CYP3A4 inducers. Drug Metab Dispos 2001; 29: 1499-1504.
213. Luo G, Cunningham M, Kim S, Burn T, Lin J, Sinz M, et al. CYP3A4 induction by drugs: Correlation between a pregnane X receptor reporter gene assay and CYP3A4 expression in human hepatocytes. Drug Metab Dispos 2002; 30: 795-804.
214. Morioka Y, Nishimura M, Imai T, Suzuki S, Harada M, Satoh T, et al. Assessment of induction of cytochrome P450 by NO-1886 (ibrolipim), a lipoprotein lipase-promoting agent, in primary cultures of human hepatocytes and in female rat liver. Drug Metab Pharmacokinet 2006; 21(1): 19-28.
215. Hesse LM, Sakai Y, Vishnuvardhan D, Li AP, von Moltke LL, Greenblatt DJ. Effect of bupropion on CYP2B6 and CYP3A4 catalytic activity, immunoreactive protein and mRNA levels in primary human hepatocytes: comparison with rifampicin. J Pharm Pharmacol 2003; 55(9): 1229-1239.
216. Park KB, Pirmohamed M, Kitteringham NR. Role of drug disposition in drug hypersensitivity: A chemical, molecular, and clinical perspective. Chem Res Toxicol 1998; 11(9): 969-988.
217. Iketa T. Idiosyncratic drug toxicity - view from pharmacokinetics and drug metabolism-. J Mass Spectro Soc Japan 2005; 53(3): 142-145.
218. Zhou S, Chan E, Duan W, Huang M Chen YZ. Drug bioactivation, covalent binding to target proteins and toxicity relevance. Drug Metab Rev 2005; 37(1): 41-213.
219. Erve JCL. Chemical toxicology: Reactive intermediates and their role in pharmacology and toxicology. Expert Opin Drug Metab Toxicol 2006; 2(6): 923-946.
220. Park KB, Dalton-Brown E, Hirst C, Williams DP. Selection of new chemical entities with decreased potential for adverse drug reactions. Eur J Pharmacol 2006; 549(1-3): 1-8.
221. Williams, DP. Toxicophores. Investigations in drug safety. Toxicol 2006; 226(1): 1-11.
222. Tang W. Drug metabolite profiling and elucidation of drug-induced hepatotoxicity. Expert Opin Drug Metab Toxicol 2007; 3(3): 407-420.
223. Antoine DJ, Williams DP, Park BK. Understanding the role of reactive metabolites in drug-induced hepatotoxicity: State of the science. Expert Opin Drug Metab Toxicol 2008; 4(11): 1415-1427.
224. Kalgutkar AS, Soglia JR. Minimising the potential for metabolic activation in drug discovery. Expert Opin Drug Metab Toxicol 2005; 1(1): 91-142.
225. Kumar S, Kassahun K, Tschirret-Guth RA, Mitra K, Baillie TA. Minimizing metabolic activation during pharmaceutical lead optimization: Progress, knowledge gaps and future directions. Curr Opin Drug Discov Dev 2008; 11(1): 43-52.
226. US Food and Drug Administration. Guidance for industry: Safety testing of drug metabolites. US FDA, Rockville, MD. 2008; http://www.fda.gov/ cder/guidance/index.htm
227. Guengerich FP. Principles of covalent binding of reactive metabolites and examples of activation of bis-electrophiles by conjugation. Arch Biochem Biophys 2005; 433(2): 369-378.
228. Baillie TA. Future of toxicologymetabolic activation and drug design: Challenges and opportunities in chemical toxicology. Chem Res Toxicol 2006; 19(7): 889-893.
229. Luffer-Atlas D. Unique/major human metabolites: Why, how, and when to test for safety in animals. Drug Metab Rev 2008; 40: 447-463.
230. Baillie TA. Metabolism and toxicity of drugs. Two decades of progress in industrial drug metabolism. Chem Res Toxicol 2008; 21(1): 129-137.
231. Uetrecht J. Screening for the potential of a drug candidate to cause idiosyncratic drug reactions. Drug Discov Today 2003; 8(18): 832-837
232. Evans DC, Watt AP, Nicoll-Griffith DA, Baillie TA. Drug-protein adducts: An industry perspective on minimizing the potential for drug bioactivation in drug discovery and development. Chem Res Toxicol 2004; 17 (1): 3-16.
233. Nassar AF, Kamel AM, Clarimont C. Improving the decision-making process in structural modification of drug candidates: Reducing toxicity. Drug Discov Today 2004; 9(24): 1055-1064.
234. Hop CECA, Kalgutkar AS, Soglia JR. Importance of early assessment of bioactivation in drug discovery. Annu Reports Med Chem 2006; 41: 369-381.
235. Caldwell GW, Yan Z. Screening for reactive intermediates and toxicity assessment in drug discovery. Curr Opin Drug Discov Dev 2006; 9(1): 47-60.
236. Shu YZ, Johnson BM, Yang TJ. Role of Biotransformation studies in minimizing metabolism-related liabilities in drug discovery. AAPSJ 2008; 10(1): 178-192.
237. Soglia JR, Harriman SP, Zhaoa S, Barberia J, Cole MJ, Boyd JG, et al. The development of a higher throughput reactive intermediate screening assay incorporating micro-bore liquid chromatography-micro-electrospray ionization-tandem mass spectrometry and glutathione ethyl ester as a trapping agent. J Pharm Biomed Anal 2004; 36: 105-116.
238. Yan Z, Maher N, Torres R, Huebert N. Use of a trapping agent for simultaneous capturing and high-throughput screening of both "soft" and "hard" reactive metabolites. Anal Chem 2007; 79(11): 4206-4214.
239. Gorrod JW, Aislaitner G. The metabolism of alicyclic amines to reactive iminium ion intermediates. Eur J Drug Metab Pharmacokinet 1994; 19: 209-217.
240. Argoti D, Liang L, Conteh A, Chen L, Bershas D, Yu CP, et al. Cyanide trapping of iminium ion reactive intermediates followed by detection and structure identification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Chem Res Toxicol 2005; 18(10): 1537-1544.
241. Mutlib A, Lam W, Atherton J, Chen H, Galatsis P, Stolle W. Application of stable isotope labeled glutathione and rapid scanning mass spectrometers in detecting and characterizing reactive metabolites. Rapid Commun Mass Spectro 2005; 19(23): 3482-3492.
242. Ma L, Wen B, Ruan Q, Zhu M. Rapid screening of glutathione-trapped reactive metabolites by linear ion trap mass spectrometry with isotope pattern-dependent scanning and postacquisition data mining. Chem Res Toxicol 2008; 21(7): 1477-1483.
243. Mutlib AE. Application of stable isotope-labeled compounds in metabolism and in metabolism-mediated toxicity studies. Chem Res Toxicol 2008; 21(9): 1672-1689.
244. Soglia JR, Contillo LG, Kalgutkar AS, Zhao S, Hop CECA, Boyd JG, et al. A semiquantitative method for the determination of reactive metabolite conjugate levels in vitro utilizing liquid chromatography-tandem mass. Chem Res Toxicol 2006; 19(3): 480-490.
245. Mitchell MD, Elrick MM, Walgren JL, Mueller RA, Morris DL, Thompson DC. Peptide-based in vitro assay for the detection of reactive metabolites. Chem Res Toxicol 2008; 21(4): 859-868.
246. Zheng J, Ma L, Xin B, Olah T, Griffith HW, Zhu M. Screening and identification of GSH-trapped reactive metabolites using hybrid triple quadruple linear ion trap mass spectrometry. Chem Res Toxicol 2007; 20(5): 757-766.
247. Wen B, Ma L, Nelson SD, Zhu M. High-throughput screening and characterization of reactive metabolites using polarity switching of hybrid triple quadrupole linear ion trap mass spectrometry. Anal Chem 2008; 80(5): 1788-1799.
248. Madsen KG, Olsen J, Skonberg C, Hansen SH, Jurva U. Development and evaluation of an electrochemical method for studying reactive phase-I metabolites: Correlation to in vitro drug metabolism. Chem Res Toxicol 2007; 20(5): 821-831.
249. Gan J, Harper TW, Hsueh MM, Qu Q, Humphreys WG: Dansyl glutathione as a trapping agent for the quantitative estimation and identification of reactive metabolites. Chem Res Toxicol 2005; 18(5): 896-903.
250. Meneses-Lorente G, Sakatis MZ, Schulz-Utermoehl T, De Nardi C, Watt AP. A quantitative high-throughput trapping assay as a measurement of potential for bioactivation. Anal Biochem 2006; 351(2): 266-272.
251. Masubuchi N, Makino C, Murayama N. Prediction of in vivo potential for metabolic activation of drugs into chemically reactive intermediate: Correlation of in vitro and in vivo generation of reactive intermediates and in vitro glutathione conjugate formation in rats and humans. Chem Res Toxicol 2007; 20(3): 455-464.
252. Obach RS, Kalgutkar AS, Soglia JR, Zhao SX. Can in vitro metabolism-dependent covalent binding data in liver microsomes distinguish hepatotoxic from nonhepatotoxic drugs? An analysis of 18 drugs with consideration of intrinsic clearance and daily dose. Chem Res Toxicol 2008; 21(9): 1814-1822.
253. Takakusa H, Masumoto H, Yukinaga H, Makino C, Nakayama S, Okazaki O, et al. Covalent binding and tissue distribution/retention assessment of drugs associated with idiosyncratic drug toxicity. Drug metab dispos 2008; 36(9): 1770-9.
254. Yan Z, Caldwell GW. Stable-isotope trapping and high-throughput screenings of reactive metabolites using the isotope MS signature. Anal Chem 2004; 76(23): 6835-6847.
255. Zvinavashe E, Murk AJ, Rietjens IMCM. Promises and pitfalls of quantitative structure-activity relationship approaches for predicting metabolism and toxicity. Chem Res Toxicol 2008; 21(12): 2229-2236.
256. Kalgutkar AS, Gardner I, Obach SR, Shaffer CL, Callegari E, Henne KR, et al. A comprehensive listing of bioactivation pathways of organic functional groups. Curr Drug Metab 2005; 6: 161-225.
257. Doss GA, Baillie TA. Addressing metabolic activation as an integral component of drug design. Drug Metab Rev 2006; 38: 641-649.
258. Smith DA, Obach RS. Metabolites and safety: What are the concerns, and how should we address them? Chem Res Toxicol 2006; 19(12): 1570-1579
259. Uetrecht J. Role of drug metabolism for breaking tolerance and the localization of drug hypersensitivity. Toxicol 2005; 209(2): 113-118.
260. Balani SK, Miwa GT, Gan LS, Wu JT, Lee FW. Strategy of utilizing in vitro and in vivo ADME tools for lead optimization and drug candidate selection. Curr Top Med Chem 2005; 5(11): 1033-1038.
261. Li AP. Building predictive ADMET models for early decisions in drug discovery. Drug Discov Today 2001; 6: 357-366.
262. Kaplowitz N. Idiosyncratic drug hepatotoxicity. Nat Rev Drug Discov 2005; 4: 489-99.
263. Lombardo F, Shalaeva M, Tupper KA, Gao F, Abraham MJ. Elog-Poct: A tool for lipophilicity determination in drug discovery. J Med Chem 2000; 43: 2922-2928.
264. 35S]cysteine as trapping agents, to detect reactive intermediates of xenobiotics. Toxicol in vitro 1988; 2(3): 225-230.
265. Yan Z, Maher N, Torres R, Caldwell GW, Huebert N. Rapid detection and characterization of minor reactive metabolites using stableisotope trapping in combination with tandem mass spectrometry. Rapid Commun Mass Spectrom 2005; 19(22): 3322-3330.
266. Hop CECA, Cole MJ, Davidson RE, Duignan DB, Federico J, Janiszewski JS, et al. High throughput ADME screening: Practical considerations, impact on the portfolioand enabler of in silico ADME models. Curr Drug Metab 2008; 9: 847-853.
267. Reichel A, Begley DJ. Potential of immobilized artificial membranes for predicting drug penetration across the blood-brain barrier. Pharm Res 1998; 15: 1270-1274.
268. O'Brien PJ, Chan K, Silber PM. Human and animal hepatocytes in vitro with extrapolation in vivo. Chem Biol Interact 2004; 150: 97-114.
269. DeWitte RS. Avoiding physicochemical artefacts in early ADME-Tox experiments. Drug Discov Today 2006; 11: 855-859.
270. Di L, Kerns EH. Biological assay challenges from compound solubility: Strategies for bioassay optimization. Drug Discov Today 2006; 11: 446-451.
271. Bhogal N, Balls M. Translation of new technologies: From basic research to drug discovery and development. Curr Drug Discov Technol 2008; 5(3): 250-62.
272. Bonam M, Christopher D, Cipolla D, Donovan B, Goodwin D, Holmes S, et al. Minimizing variability of cascade impaction measurements in inhalers and nebulizers. AAPS PharmSciTech 2008; 9(2): 404-13.
273. Gedeck P, Lewis RA. Exploiting QSAR models in lead optimization. Curr Opin Drug Discov Devel 2008; 11(4): 569-75.