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14. Hinderling, P. H. Red blood cells: a neglected compartment in pharmacokinetics and pharmacodynamics. Pharmacol. Rev. 1997, 49(3), 279–295.
15. Rowland, M. and Tozer, T. N. Clinical Pharmacokinetics: Concepts and Applications, 3rd Edition, Williams & Wilkins, Baltimore, MD, 1995, xiv, p. 601.
16. Davies, B. and Morris, T. Physiological parameters in laboratory animals and humans. Pharm. Res. 1993, 10(7), 1093–1095.
17. Kubitz, R., Helmer, A., and Haussinger, D. Biliary transport systems: short-term regulation. Methods Enzymol. 2005, 400, 542–557.
18. Brockmeier, D. and von Hattingberg, H. M. Mean residence time. Methods Find Exp. Clin. Pharmacol. 1986, 8(5), 309–312.
19. Gibaldi, M. and Perrier, D. Pharmacokinetics. In Drugs and the Pharmaceutical Sciences, 2nd Edition, Vol. 15, Dekker, New York, 1982, viii, p. 494.
20. Shargel, L., Wu-Pong, S. and Yu, A. B. C. Applied Biopharmaceutics & Pharmacoki- netics, 5th Edition, McGraw-Hill, Medical Publishing Division, New York, 2005, xx, p. 892.
21. Kleiber, M. Body size and metabolic rate. Physiol. Rev. 1947, 27, 511–541.
22. Hu, T. M. and Hayton, W. L. Allometric scaling of xenobiotic clearance: uncertainty versus universality. AAPS PharmSci. 2001, 3(4), E29.
23. Lave, T., et al. Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs. J. Pharm. Sci. 1997, 86(5), 584–590.
24. Mahmood, I. Application of allometric principles for the prediction of pharmacokinetics in human and veterinary drug development. Adv. Drug Deliv. Rev. 2007, 59(11), 1177–1192.
25. Hosea, N. A., et al. Prediction of human pharmacokinetics from preclinical information: comparative accuracy of quantitative prediction approaches. J. Clin. Pharmacol. 2009, 49(5), 513–533.
26. Rowland, M., Balant, L., and Peck, C. Physiologically based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown University, Washington, DC, May 29–30, 2002). AAPS Pharm. Sci. 2004, 6(1), E6.
27. Bonate, P. L., Swann, A., and Silverman, P. B. Preliminary physiologically based pharmacokinetic model for cocaine in the rat: model development and scale-up to humans. J. Pharm. Sci. 1996, 85(8), 878–883.
28. De Buck, S. S., et al. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs. Drug Metab. Dispos. 2007, 35(10), 1766–1780.
29. Naritomi, Y.,et al. 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(10), 1316–1324.
30. Ghibellini, G., et al.
In vitro–in vivo correlation of hepatobiliary drug clearance in
humans. Clin. Pharmacol. Ther. 2007, 81(3), 406–413.
31. Miners, J. O., et al. In vitro–in vivo correlation for drugs and other compounds eliminated by glucuronidation in humans: pitfalls and promises. Biochem. Pharmacol. 2006, 71(11), 1531–1539.
32. Tabrizi, M. A., et al. Translational strategies for development of monoclonal antibodies from discovery to the clinic. Drug Discov. Today. 2009, 14(5–6), 298–305.
278
PHARMACOKINETICS FOR MEDICINAL CHEMISTS
https://t.me/medicina_free
33. Gan, L.-S., et al. Case Study—Use of ADME Studies for Optimization of Drug Candidates. In Optimizing the Drug-LikeProperties of Leads in Drug Discovery, Borchardt R. T., et al. (ed.), American Association of Pharmaceutical Scientists, New York, NY, 2006, pp. 81–101.
34. Jewell, C., et al. Specificity of procaine and ester hydrolysis by human, minipig, and rat skin and liver. Drug. Metab. Dispos. 2007, 35(11), 2015–2022.
35. Hartman, D. A. Determination of the stability of drugs in plasma. Curr. Protoc. Pharmacol. 2003, Suppl. 19, 7.6.1–7.6.8.
36. Morissette, S. L., et al. Elucidation of crystal form diversity of the HIV protease inhibitor ritonavir by high-throughput crystallization. Proc. Natl. Acad. Sci. USA 2003, 100(5), 2180–2184.
37. Huang, L. F. and Tong,W.Q. Impact of solid state properties on developability assessment of drug candidates. Adv. Drug. Deliv. Rev. 2004, 56(3), 321–334.
38. Gibson, M. (ed.). Pharmaceutical Preformulation and Formulation: A Practical Guide
from Candidate Drug Selection to Commercial Dosage Form, 2nd Edition, Drugs and the Pharmaceutical Sciences, Informa Healthcare, London, 2009, p. 560.
39. Gad, S. C. (ed.). Preclinical Development Handbook: ADME and Biopharmaceutical Properties. Pharmaceutical Development Series, Wiley-Interscience, New York, 2008,
p. 1352.
40. Hardee, G. E. and Baggot, J. D. (eds.). Development & Formulation of Veterinary Dosage Forms. 2nd ed. Drugs and the Pharmaceutical Sciences, Vol. 88, Informa HealthCare, London, 1998.
41. Weiner, M. L. and Kotkoskie, L. A. (eds.). Excipient Toxicity and Safety. Drugs and the Pharmaceutical Sciences, Vol. 103, Marsel Dekker, New York, Basel, 2000, p.370.
42. Liu, R. (ed.). Water-Insoluble Drug Formulation, 2nd Edition, CRC Press, Boca Raton, FL, 2008, p. 669.
43. Lee, Y. C., Zocharski, P. D., and Samas, B. An intravenous formulation decision tree for discovery compound formulation development. Int. J. Pharm. 2003, 253(1–2), 111–119.
44. Strickley, R. G. Solubilizing excipients in oral and injectable formulations. Pharm. Res. 2004, 21(2), 201–230.
45. Rowe, R., Sheskey, P., and Weller, P. (eds.). Handbook of Pharmaceutical Excipients, 4th Edition, Pharmaceutical Press, London, 2003.
46. Rowe, R., Sheskey,P., and Quinn, M. E. (eds.). Handbook of Pharmaceutical Excipients, 6th Edition, Pharmaceutical Press, London, 2009, p. 888.
47. Napaporn, J., et al. Assessment of the myotoxicity of pharmaceutical buffers using an
in vitro muscle model: effect of pH, capacity, tonicity, and buffer type. Pharm. Dev. Technol. 2000, 5(1), 123–130.
48. Krzyzaniak, J. F., et al. Lysis of human red blood cells. 4. Comparison of in vitro and in vivo hemolysis data. J. Pharm. Sci. 1997, 86(11), 1215–1217.
49. Krzyzaniak, J. F., Raymond, D. M., and Yalkowsky, S. H. Lysis of human red blood cells 1: effect of contact time on water induced hemolysis. PDA J. Pharm. Sci. Technol. 1996, 50(4), 223–226.
50. Krzyzaniak, J. F. and Yalkowsky, S. H. Lysis of human red blood cells. 3: Effect of contact time on surfactant-induced hemolysis. PDA J Pharm. Sci. Technol. 1998, 52(2), 66–69.
REFERENCES 279
https://t.me/medicina_free
51. Reed, K. W. and Yalkowsky, S. H. Lysis of human red blood cells in the presence of various cosolvents. J. Parenter. Sci. Technol. 1985, 39(2), 64–69.
52. Reed, K. W. and Yalkowsky, S. H. Lysis of human red blood cells in the presence of various cosolvents. II. The effect of differing NaCl concentrations. J. Parenter. Sci. Technol. 1986, 40(3), 88–94.
53. Reed, K. W. and Yalkowsky, S. H. Lysis of human red blood cells in the presence of various cosolvents. III. The relationship between hemolytic potential and structure. J. Parenter. Sci. Technol. 1987, 41(1), 37–39.
54. Regev, R., et al. Modulation of P-glycoprotein-mediated multidrug resistance by accel­eration of passive drug permeation across the plasma membrane. FEBS J. 2007, 274(23), 6204–6214.
55. Martin-Facklam, M., et al. Dose-dependent increase of saquinavir bioavailability by the pharmaceutic aid cremophor EL. Br. J. Clin. Pharmacol. 2002, 53(6), 576–581.
56. Suckow, M. A., Weisbroth, S. H., and Franklin, C. L. (eds.). The Laboratory Rat. American College of Laboratory Animal Medicine Series, Academic Press, New York, 2006, p. 912.
57. Hau, J. and Hoosier, G. L. V. (eds.). Handbook of Laboratory Animal Science: Essential Principles and Practices. In Handbook of Laboratory Animal Science, 2nd Edition, Vol. 2, CRC Press, Boca Raton, FL, 2002, p. 568.
58. Rollin, E. B. and Kesel, M. L. (eds.). The Experimental Animal in Biomedical Research: Care, Husbandry, and Well-Being: An Overview by Species. In The Experimental Animal in Biomedical Research, Vol. 1, CRC Press, Boca Raton, FL, 1995, p. 560.
59. Hughes, R. N. Sex does matter: comments on the prevalence of male-only investigations of drug effects on rodent behaviour. Behav. Pharmacol. 2007, 18(7), 583–589.
60. Imamura, Y. and Shimada, H. Differential pharmacokinetics of acetohexamide in male Wistar-Imamichi and Sprague-Dawley rats: role of microsomal carbonyl reductase. Biol. Pharm. Bull. 2005, 28(1), 185–187.
61. Louvet, C., et al. Tyrosine kinase inhibitors reverse type 1 diabetes in nonobese diabetic mice. Proc. Natl. Acad. Sci. USA 2008, 105(48), 18895–18900.
62. Satterwhite, J. H. and Boudinot, F. D. Effects of age and dose on the pharmacokinetics of ibuprofen in the rat. Drug Metab. Dispos. 1991, 19(1), 61–67.
63. Lin, J. H. Applications and limitations of genetically modified mouse models in drug discovery and development. Curr. Drug. Metab. 2008, 9(5), 419–438.
64. Cartwright, E. J. Large-scale mouse mutagenesis. Methods Mol. Biol. 2009, 561, 275–283.
65. Gondo, Y. Trends in large-scale mouse mutagenesis: from genetics to functional genomics. Nat. Rev. Genet. 2008, 9(10), 803–810.
66. Stanley, L. A., et al. Drug transporters: gatekeepers controlling access of xenobiotics to the cellular interior. Drug Metab. Rev. 2009, 41(1), 27–65.
67. Katoh, M., et al. Chimeric mice with humanized liver. Toxicology 2008, 246(1), 9–17.
68. Katoh, M. and Yokoi, T. Application of chimeric mice with humanized liver for predictive ADME. Drug Metab. Rev. 2007, 39(1), 145–57.
69. Katoh, M., et al. In vivo drug metabolism model for human cytochrome P450 enzyme using chimeric mice with humanized liver. J. Pharm. Sci. 2007, 96(2), 428–437.
70. Okumura, H., et al. Humanization of excretory pathway in chimeric mice with humanized liver. Toxicol. Sci. 2007, 97(2), 533–538.
280
PHARMACOKINETICS FOR MEDICINAL CHEMISTS
https://t.me/medicina_free
71. Kacew, S. and Festing, M. F. Role of rat strain in the differential sensitivity to pharmaceutical agents and naturally occurring substances. J. Toxicol. Environ. Health 1996, 47(1), 1–30.
72. Kacew, S. Confounding factors in toxicity testing. Toxicology 2001, 160(1–3), 87–96.
73. Lawson, P. T. (ed.). Assistant Laboratory Animal Technician. ALAT Training Manual, AALAS, Cordova, TN, 1998, p. 202.
74. Moriyasu, A., et al. In vivo–in vitro relationship of methotrexate 7-hydroxylation by aldehyde oxidase in four different strain rats. Drug Metab. Pharmacokinet. 2006, 21(6), 485–491.
75. Itoh, K., et al. Lack of dimer formation ability in rat strains with low aldehyde oxidase activity. Xenobiotica 2007, 37(7), 709–716.
76. Yilmazer-Hanke, D. M. Morphological correlates of emotional and cognitive behaviour: insights from studies on inbred and outbred rodent strains and their crosses. Behav. Pharmacol. 2008, 19(5–6), 403–434.
77. Musick, T. J., et al. Pharmacokinetics, disposition, and metabolism of bicifadine in the mouse, rat, and monkey. Drug Metab. Dispos. 2008, 36(2), 241–251.
78. Matta, S. G., et al. Guidelines on nicotine dose selection for in vivo research. Psycho- pharmacology (Berl.) 2007, 190(3), 269–319.
79. Mordenti, J. Man versus beast: pharmacokinetic scaling in mammals. J. Pharm. Sci. 1986, 75(11), 1028–1040.
80. Guo, Z., et al. Ciclesonide disposition and metabolism: pharmacokinetics, metabolism, and excretion in the mouse, rat, rabbit, and dog. Am. J. Ther. 2006, 13(6), 490–501.
81. Mordenti, J. Forecasting cephalosporin and monobactam antibiotic half-lives in humans from data collected in laboratory animals. Antimicrob. Agents Chemother. 1985, 27(6), 887–891.
82. Prescott, M. J. and s.a.o.a.i.P. file, Refining dog husbandry and care. Eighth Report of BVAAWF/FRAME/RSPCA/UFAW Joint Working Groxxxup on Refinement. Lab. Anim. 2004, 38(1), 1–94.
83. Gipson, C.Animal Care Annual Report of Activities. Fiscal Year 2007, U.S.D.O. Agriculture, A.A.P.H.I. Service, and A. 41-35-075, Editors, 2007, United States Depart­ment of Agriculture.
84. Ward, K. W., Nagilla, R., and Jolivette, L. J. Comparative evaluation of oral systemic exposure of 56 xenobiotics in rat, dog, monkey and human. Xenobiotica. 2005, 35(2), 191–210.
85. Ward, K. W. and Smith, B. R. A comprehensive quantitative and qualitative evaluation of extrapolation of intravenous pharmacokinetic parameters from rat, dog, and monkey to humans. I. Clearance. Drug. Metab. Dispos. 2004, 32(6), 603–611.
86. Ward, K. W. and Smith, B. R. A comprehensive quantitative and qualitative evaluation of extrapolation of intravenous pharmacokinetic parameters from rat, dog, and monkey to humans. II. Volume of distribution and mean residence time. Drug Metab. Dispos. 2004, 32(6), 612–619.
87. Hearn, J. P. Primate Priorities—An International Perspective. In International Perspec- tives: The Future of Nonhuman Primate Resources, Proceedings of the Workshop, The National Academies Press, Washington, DC, 2003.
88. Hearn, J. P. Science, ethics and regulation in primate research. Gynecol. Obstet. Invest. 2004, 57(1), 8–10.
REFERENCES 281
https://t.me/medicina_free
89. Cohen, J. Biomedical research. The endangered lab chimp. Science 2007, 315(5811), 450–452.
90. VandeBerg, J. L. and Zola, S. M. A unique biomedical resource at risk. Nature 2005, 437 (7055), 30–32.
91. Varki, A. The uncertain future of research chimpanzees. Science 2007, 315(5818), 1493–1494.
92. Moore, J. The uncertain future of research chimpanzees. Science 2007, 315(5818), 1493–1494.
93. Prince, A. M. The uncertain future of research chimpanzees. Science 2007, 315(5818), 1493–1494.
94. Rowan, A. N. The uncertain future of research chimpanzees. Science 2007, 315(5818), 1493–1494.
95. Cai, H., et al. A Humanized UGT1 Mouse Model Expressing the UGT1A1
28 Allele for Assessing Drug Clearance by UGT1A1—Dependent Glucuronidation. Drug. Metab. Dispos. 2010, doi:10.1124/dmd.109.030130.
96. Sakaeda, T., et al. Blood flow rate in normal and tumor-bearing rats in conscious state, under urethane anesthesia, and during systemic hypothermia. J. Drug. Target 1998, 6(4), 261–272.
97. Diehl, K. H., et al. A good practice guide to the administration of substances and removal of blood, including routes and volumes. J. Appl. Toxicol. 2001, 21(1), 15–23.
98. Kurosawa, N., Owada, E., and Ito, K. Avoidance of hepatic first-pass effect in the rabbit via rectal route of administration. Biopharm. Drug. Dispos. 1998, 19(9), 589–594.
99. Wilhelm, A. J., et al. Analysis of cyclosporin A in dried blood spots using liquid chromatography tandem mass spectrometry. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2009, 877(14–15), 1595–1598.
100. Spooner, N., Lad, R., and Barfield, M. Dried blood spots as a sample collection technique for the determination of pharmacokinetics in clinical studies: considerations for the validation of a quantitative bioanalytical method. Anal. Chem. 2009, 81(4), 1557–1563.
101. Balls, M., et al. The three Rs: the way forward: the report and recommendations of ECVAM Workshop 11. Altern. Lab. Anim. 1995, 23(6), 838–866.
102. Wu, C. Y. and Benet, L. Z. 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.
103. Martinez, M. N. and Amidon, G. L. A mechanistic approach to understanding the factors affecting drug absorption: a review of fundamentals. J. Clin. Pharmacol. 2002, 42(6), 620–643.
104. Patel, J. P. and Brocks, D. R. The effect of oral lipids and circulating lipoproteins on the metabolism of drugs. Expert Opin. Drug. Metab. Toxicol. 2009, 5(11), 1385–1398.
105. Parrott, N., et al. Predicting pharmacokinetics of drugs using physiologically based modeling—application to food effects. AAPS J. 2009, 11(1), 45–53.
106. Arayne, M. S., Sultana, N., and Bibi, Z. Grape fruit juice–drug interactions. Pak. J. Pharm. Sci. 2005, 18(4), 45–57.
107. Fleisher, D., et al. Drug, meal and formulation interactions influencing drug absorption after oral administration. Clinical implications. Clin. Pharmacokinet. 1999, 36(3), 233–254.
282
PHARMACOKINETICS FOR MEDICINAL CHEMISTS
https://t.me/medicina_free
108. Paulson, S. K., et al. Pharmacokinetics of celecoxib after oral administration in dogs and humans: effect of food and site of absorption. J. Pharmacol. Exp. Ther. 2001, 297(2), 638–645.
109. Kojima, S. Factors influencing absorption and excretion of drugs. I. Effect of food on gastrointestinal absorption of amobarbital in rats. Chem. Pharm. Bull. (Tokyo) 1973, 21(11), 2432–2437.
110. Kohn, D. F. and Lipman, N. S. Anesthesia and Analgesia in Laboratory Animals. In American College of Laboratory Animal Medicine series, Academic Press, San Diego, 1997, xvii, p. 426.
111. Carroll, G. L. Small Animal Anesthesia and Analgesia, Wiley-Blackwell, New York, 2008, p. 283.
112. Xie, F., et al. Good preclinical bioanalytical chemistry requires proper sampling from laboratory animals: automation of blood and microdialysis sampling improves the productivity of LC/MSMS. Anal. Sci. 2003, 19(4), 479–485.
113. He, H., et al. A preliminary study on the feasibility of an automated blood-sampling system in conjunction with liquid chromatography/mass spectrometry. Rapid Commun. Mass Spectrom. 2001, 15(18), 1768–1772.
114. Liu, J. Y., et al. Pharmacokinetic optimization of four soluble epoxide hydrolase inhibitors for use in a murine model of inflammation. Br. J. Pharmacol. 2009, 156(2), 284–296.
115. Hassan, M., et al. The effect of busulphan on the pharmacokinetics of cyclophosphamide and its 4-hydroxy metabolite: time interval influence on therapeutic efficacy and therapy­related toxicity. Bone Marrow Transplant. 2000, 25(9), 915–924.
116. Watanabe, T., et al. High-throughput pharmacokinetic method: cassette dosing in mice associated with minuscule serial bleedings and LC/MS/MS analysis. Anal. Chim. Acta. 2006, 559(1), 37–44.
117. Chen, J., et al. Supercritical fluid chromatography-tandem mass spectrometry for the enantioselective determination of propranolol and pindolol in mouse blood by serial sampling. Anal. Chem. 2006, 78(4), 1212–1217.
118. Balani, S. K., et al. Effective dosing regimen of 1-aminobenzotriazole for inhibition of antipyrine clearance in guinea pigs and mice using serial sampling. Drug Metab. Dispos. 2004, 32(10), 1092–1095.
119. Bateman, K. P., et al. Reduction of animal usage by serial bleeding of mice for pharmacokinetic studies: application of robotic sample preparation and fast liquid chromatography-mass spectrometry. J. Chromatogr. B Biomed. Sci. Appl. 2001, 754(1), 245–251.
120. Fraser, I. J., et al. The use of capillary high performance liquid chromatography with electrospray mass spectrometry for the analysis of small volume blood samples from serially bled mice to determine the pharmacokinetics of early discovery compounds. Rapid Commun. Mass Spectrom. 1999, 13(23), 2366–2375.
121. Korfmacher, W. A. (ed.). Using Mass Spectrometry for Drug Metabolism Studies, 2nd Edition, CRC Press, Boca Raton, FL, 2009, p. 464.
122. Venn, R. F. (ed.). Principles and Practice of Bioanalysis, 2nd Edition, CRC Press, Boca Raton, FL, 2008, p. 344.
123. Boyd, R. K., Basic, C., and Bethem, R. A. (eds.). Trace Quantitative Analysis by Mass Spectrometry, Wiley, New York, 2008, p. 748.
REFERENCES 283
https://t.me/medicina_free
124. McMaster, M. C. (ed.). LC/MS: A Practical Users Guide, Wiley-Interscience, Hoboken, NJ, 2005, p. 184.
125. Dass, C. (ed.). Fundamentals of Contemporary Mass Spectrometry. In Interscience Series on Mass Spectrometry, Desederio, D. M. and Nibbering, N. M. M. (eds.), Wiley­Interscience, Hoboken, NJ, 2007, p. 608.
126. Watson, J. T. and Sparkman, O. D. (eds.). Introduction to Mass Spectrometry: Instru- mentation, Applications, and Strategies for Data Interpretation, 4th Edition, Wiley, Hoboken, NJ, 2007, p. 862.
127. Ramanathan, R. (ed.). Mass Spectrometry in Drug Metabolism and Pharmacokinetics, Wiley, Hoboken, NJ, 2009, p. 390.
128. Lavagnini, I., et al. (eds.). Quantitative Applications of Mass Spectrometry, Wiley, Hoboken, NJ, 2006, p. 152.
129. Mallet, A. and Down, S. (eds.). Dictionary of Mass Spectrometry, Wiley, Hoboken, NJ, 2009, p. 184.
130. Sparkman, D. O. (ed.). Mass Spectrometry Desk Reference, 2nd Edition, Global View Publishing, Pittsburgh, PA, 2006, p. 198.
131. Vekey, K., Telekes, A., and Vertes, A. (eds.). Medical Applications of Mass Spectrometry, Elsevier Science, The Netherlands, 2008, p. 606.
132. Rossi, D. T. and Sinz, M. (eds.). Mass Spectrometry in Drug Discovery (Hardcover), Marcel Dekker, New York, NY, 2002, p. 432.
133. Lee, M. S. (ed.). Integrated Strategies for Drug Discovery Using Mass Spectrometry, Wiley-Interscience, New York, 2005, p. 568.
134. Lee, M. S. LC/MS Applications in Drug Development, Wiley-Interscience Series on Mass Spectrometry, New York, 2002, p. 256.
135. Evans, G. (ed.). A Handbook of Bioanalysis and Drug Metabolism, CRC Press, Boca Raton, FL, 2004, p. 408.
136. Viswanathan, C. T., et al. Quantitative bioanalytical methods validation and implemen­tation: best practices for chromatographic and ligand binding assays. Pharm. Res. 2007, 24(10), 1962–1973.
137. Wells, D. A. (ed.). High Throughput Bioanalytical Sample Preparation, Elsevier, The Netherlands, 2003, p. 628.
138. Lipinski, C. A., et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug. Deliv. Rev. 1997, 23, 3–25.
139. Gleeson, M. P. Generation of a set of simple, interpretable ADMET rules of thumb. J. Med. Chem. 2008, 51(4), 817–834.
140. Smith, D. A., Jones, B. C., and Walker, D. K. Design of drugs involving the concepts and theories of drug metabolism and pharmacokinetics. Med. Res. Rev. 1996, 16(3), 243–266.
141. Kerns, E. and Di, L. (eds.). Drug-like Properties: Concepts, Structure Design and Methods: From ADME to Toxicity Optimization, Academic Press, New York, 2008, p. 552.
142. van de Waterbeemd, H. and Gifford, E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug. Discov. 2003, 2(3), 192–204.
143. Dearden, J. C. In silico prediction of ADMET properties: how far have we come? Expert Opin. Drug Metab. Toxicol. 2007, 3(5), 635–639.
284
PHARMACOKINETICS FOR MEDICINAL CHEMISTS
https://t.me/medicina_free
144. Lipinski, C. A. Drug-like properties and the causes of poor solubility and poor perme­ability. J. Pharmacol. Toxicol. Methods 2000, 44(1), 235–249.
145. Lipinski, C. A., et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001, 46(1–3), 3–26.
146. Birnbaum, L., et al. Physiological Parameter Values for PBPK Models, International Life Science Institute–Risk Science Institute (ILSI–RSI, ILSI@ILSI.org), Washington, DC, 1994, p. III, 87.
147. Kendall, M. D., Johnson, H. R., and Singh, J. The weight of the human thymus gland at necropsy. J. Anat. 1980, 131(3), p. 483–497.
148. Bernareggi, A. and Rowland, M. Physiologic modeling of cyclosporin kinetics in rat and man. J. Pharmacokinet. Biopharm. 1991, 19(1), 21–50.
149. Kwon, Y. Handbook of Essential Pharmacokinetics, Pharmacodynamics and Drug Metabolism for Industrial Scientists, Kluwer Academic/Plenum Publishers, New York, NY, 2001, p. 291.
150. Zwart, L. d., et al. Anatomical and Physiological Differences Between Various Species
Used in Studies on the Pharmacokinetics and Toxicology of Xenobiotics. A Review of Literature, National Institute for Public Health and the Environment, Bilthoven, The
Netherlands, 1999, p. 100.
151. Horter, D. and Dressman, J. B. Influence of physicochemical properties on dissolution of drugs in the gastrointestinal tract. Adv. Drug Deliv. Rev. 2001, 46(1–3), 75–87.
REFERENCES 285
https://t.me/medicina_free
6
CARDIAC TOXICITY
RALF KETTENHOFEN AND SILKE SCHWENGBERG
6.1 INTRODUCTION
In the past 30 years, 28% of all approved drugs had to be withdrawn from the market due to cardiac toxicity. These compounds are categorized into two major groups depending on the mechanisms of their toxic action: ion channel-related and nonion channel-related cardiac toxicity. The former group of compounds interferes with the cardiac electrophysiology and are proarrhythmic or induce arrhythmias and sudden cardiac death (SCD). The latter group consists of compounds exhibiting cardiac cytotoxic properties such as induction apoptosis, necrosis, or metabolic disruption.
6.2 ION CHANNEL-RELATED CARDIAC TOX ICITY
Functional and regular rhythmic beating of the heart is a prerequisite for the preservation of vital functions of the body and requires a well-defined and subtle interplay between a subset of cardiac ion channels, ion exchangers, and ion pumps. Interference with and perturbation of these intricate processes may cause cardiac toxicity by rising the proarrhythmic risk, inducing atrial and ventricular arrhythmias and fibrillation, and SCD.
The occurrence of life-threatening Torsades de Pointes (TdP) ventricular tachy­arrhythmia and SCD in patients treated with approved drugs (e.g., cisapride, terolidine, and terfenadine) lead to the withdrawal of the drugs from the market. Additionally, the incidence rendered the necessity to evolve a generally accepted and harmonized guidance to assess torsadogenic potentials of drug candidates in clinical
ADMET for Medicinal Chemists: A Practical Guide, Edited by Katya Tsaioun and Steven A. Kates Copyright 2011 John Wiley & Sons, Inc.
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trials as well as in preclinical studies. The International Conference on Harmonization (ICH) of technical requirements for registration of pharmaceuticals for human use elaborated and filed the guidelines E14 (clinical) and S7B (preclinical) to address the issues of cardiac safety [1, 2].
The scientific basis for the guidelines benefited from the discovery that patients with congenital long QT syndrome (LQTS) have a higher probability to suffer from TdP tachyarrhythmia. To date, mutations in 12 different genes have been identified, including 8 ion channel a- and b-subunits that are able to cause LQTS. The potential to delay ventricular repolarization has become an accepted surrogate biomarker linked to an enhanced proarrhythmic risk of drug candidates although it is not a necessary condition to provoke life-threatening arrhythmias because other mechan­isms are also reported to be proarrhythmic (see 6.2.3 and 6.2.4).
It is discussed that an increase in transmural dispersion of the repolarization (TDR, differential repolarization in the endo-, epi-, and myocard) rather than a delayed ventricular repolarization is predictive and responsible for torsadogenic risk [3]. To date, effects on TDR can be approximated only by in vivo or ex vivo preparation of perfused ventricular wedges or Langendorff-perfused hearts. These studies are costly and time-consuming that cause early cardiac safety studies to rely on simplified models that are discussed in Section 6.2.5.
In addition to delayed ventricular repolarization, evidence was recently provided and discussed that shortening of ventricular repolarization is a risk factor for ventricular arrhythmias [4–6]. Only a few patients with congenital short QT syndrome (SQTS) have been described to date, but all suffer from an increased vulnerability to atrial and ventricular fibrillation and sudden cardiac death [7]. Mutations in four cardiac ion channels have been identified to have implications in SQTS.
6.2.1 Cardiac Electrophysiology
A short introduction to cardiac electrophysiology is provided to understand the mechanism of ion channel-related cardiac toxicity.
The electrical activity of the heart can be recorded with electrodes from the surface of the body as an electrocardiogram (ECG) (Figure 6.1). The occurring pattern in the ECG is mainly characterized by the P wave, the Q, R, and S spikes (QRS complex), and the T wave.
The QT interval of the ECG describes the time frame starting with the excitation of the ventricle (Q spike) to its relaxation (end of the T wave). The duration of the QT interval has an inverse relationship to the heart rate and has to be normalized to judge drug-induced effects on the heart rate corrected QTc interval. Commonly used correction formulas are described by Fridericia and Bazett although they appear to have some limitations in the correct assessment of drug-induced QTc prolonga­tion [8]. On a single cell level, the QT interval has its counterpart in the action potential duration of a ventricular cardiomyocyte (Figure 6.1).
At rest, the myocyte exhibits an electrochemical gradient across the plasma membrane of the main cardiac ions sodium (Na
þ
), calcium (Ca
2 þ
), and potassium
(K
þ
) with low intracellular Naþand Ca
2 þ
concentrations ([Naþ]i, [Ca
2 þ
]i) and
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