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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-Like Properties 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.
287
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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
288 CARDIAC TOXICITY
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