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Predicting Circulating Human Metabolites: How Good Are We?

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Department of Drug Disposition, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46285
* To whom correspondence should be addressed. Tel: 317-276-0711. Fax: 317-433-6432. E-mail: [email protected]
Cite this: Chem. Res. Toxicol. 2009, 22, 2, 243–256
Publication Date (Web):January 12, 2009
https://doi.org/10.1021/tx8004086
Copyright © 2009 American Chemical Society

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    Abstract

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    The FDA issued a guidance on the safety testing of metabolites in February 2008, in which they stated that metabolites of concern are those that are detected at levels greater than 10% of the systemic exposure of the parent at steady state. This has presented many challenges in determining the circulating human metabolites at an early stage of development. The intention of this perspective is to address the question of how effective in vitro metabolism and early exploratory clinical data are in predicting the circulating metabolites from both a qualitative and a quantitative perspective. To this end, data were reviewed from 17 molecules in the Lilly portfolio for which there were in vitro data and a radiolabeled study in humans. Twelve example cases are presented in detail to demonstrate trends for when in vitro data adequately predicted in vivo (41%), when in vitro data underpredicted the circulating metabolites (35%), and when in vitro data overpredicted the circulating metabolites (24%). In addition, cases that present special challenges due to very low levels of the circulating parent or long half-lives of the parent and/or metabolites are presented. The trends indicate that the more complex the metabolism, the less likely the in vitro data were to predict the circulating metabolites. The in vitro data were also less predictive for N-glucuronidations and non-P450-mediated cleavage reactions. Although the in vitro data were better at predicting clearance pathways, the data set often failed to predict the quantity of metabolites, which is needed in consideration of whether or not a “disproportionate” metabolite may be circulating in human plasma.

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    21. Yoko M. Ambrosini, Dana Borcherding, Anumantha Kanthasamy, Hyun Jung Kim, Auriel A. Willette, Albert Jergens, Karin Allenspach, Jonathan P. Mochel. The Gut-Brain Axis in Neurodegenerative Diseases and Relevance of the Canine Model: A Review. Frontiers in Aging Neuroscience 2019, 11 https://doi.org/10.3389/fnagi.2019.00130
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    24. Fallon K. Noto, Valeriya Adjan-Steffey, Min Tong, Kameswaran Ravichandran, Wei Zhang, Angela Arey, Christopher B. McClain, Eric Ostertag, Sahar Mazhar, Jaya Sangodkar, Analisa DiFeo, Jack Crawford, Goutham Narla, Tseten Y. Jamling. Sprague Dawley Rag2 -Null Rats Created from Engineered Spermatogonial Stem Cells Are Immunodeficient and Permissive to Human Xenografts. Molecular Cancer Therapeutics 2018, 17 (11) , 2481-2489. https://doi.org/10.1158/1535-7163.MCT-18-0156
    25. Nuggehally R. Srinivas. Pharmacology of Pimasertib, A Selective MEK1/2 Inhibitor. European Journal of Drug Metabolism and Pharmacokinetics 2018, 43 (4) , 373-382. https://doi.org/10.1007/s13318-018-0466-x
    26. Fan Yang, David Machalz, Sisi Wang, Zhengyi Li, Gerhard Wolber, Matthias Bureik. A common polymorphic variant of UGT 1A5 displays increased activity due to optimized cofactor binding. FEBS Letters 2018, 592 (11) , 1837-1846. https://doi.org/10.1002/1873-3468.13072
    27. Jian Zhou, Yong Ma. The Importance of Metabolite Pharmacokinetics Studies in Drug Development. International Journal of Pharmacokinetics 2018, 3 (1) , 5-9. https://doi.org/10.4155/ipk-2017-0020
    28. Mercedes Barzi, Francis P. Pankowicz, Barry Zorman, Xing Liu, Xavier Legras, Diane Yang, Malgorzata Borowiak, Beatrice Bissig-Choisat, Pavel Sumazin, Feng Li, Karl-Dimiter Bissig. A novel humanized mouse lacking murine P450 oxidoreductase for studying human drug metabolism. Nature Communications 2017, 8 (1) https://doi.org/10.1038/s41467-017-00049-x
    29. Andrew TL Wotherspoon, Mitra Safavi-Naeini, Richard B Banati. Microdosing, Isotopic Labeling, Radiotracers and Metabolomics: Relevance in Drug Discovery, Development and Safety. Bioanalysis 2017, 9 (23) , 1913-1933. https://doi.org/10.4155/bio-2017-0137
    30. Debra Luffer-Atlas, Aisar Atrakchi. A decade of drug metabolite safety testing: industry and regulatory shared learning. Expert Opinion on Drug Metabolism & Toxicology 2017, 13 (9) , 897-900. https://doi.org/10.1080/17425255.2017.1364362
    31. Hoa Q. Nguyen, Jian Lin, Emi Kimoto, Ernesto Callegari, Susanna Tse, R. Scott Obach. Prediction of Losartan-Active Carboxylic Acid Metabolite Exposure Following Losartan Administration Using Static and Physiologically Based Pharmacokinetic Models. Journal of Pharmaceutical Sciences 2017, 106 (9) , 2758-2770. https://doi.org/10.1016/j.xphs.2017.03.032
    32. Hidetaka Kamimura, Satoshi Ito, Hiroyuki Chijiwa, Takeshi Okuzono, Tomohiro Ishiguro, Yosuke Yamamoto, Sho Nishinoaki, Shin-Ichi Ninomiya, Marina Mitsui, Amit S. Kalgutkar, Hiroshi Yamazaki, Hiroshi Suemizu. Simulation of human plasma concentration–time profiles of the partial glucokinase activator PF-04937319 and its disproportionate N-demethylated metabolite using humanized chimeric mice and semi-physiological pharmacokinetic modeling. Xenobiotica 2017, 47 (5) , 382-393. https://doi.org/10.1080/00498254.2016.1199063
    33. T. Hartung. A Comprehensive Overview of the Current Status and Application of Predictive ADMET: Introduction and Overview. 2017, 150-155. https://doi.org/10.1016/B978-0-12-409547-2.12378-9
    34. Gordon J. Dear, Angus N. R. Nedderman. “MIST” AND OTHER METABOLITE GUIDELINES IN THE CONTEXT OF INDUSTRIAL DRUG METABOLISM. 2016, 17-43. https://doi.org/10.1002/9781118949689.ch2
    35. R. Scott Obach, Amit S. Kalgutkar, Deepak K. Dalvie. IN VITRO METHODS FOR EVALUATION OF DRUG METABOLISM. 2016, 87-110. https://doi.org/10.1002/9781118949689.ch4
    36. Lars Weidolf, Ian D. Wilson. UNDERSTANDING DRUG METABOLISM IN HUMANS. 2016, 141-176. https://doi.org/10.1002/9781118949689.ch6
    37. I. J. Martin, S. E. Hill, J. A. Baker, S. V. Deshmukh, E. F. Mulrooney. A Pharmacokinetic Modeling Approach to Predict the Contribution of Active Metabolites to Human Efficacious Dose. Drug Metabolism and Disposition 2016, 44 (8) , 1435-1440. https://doi.org/10.1124/dmd.116.070391
    38. Hidetaka Kamimura, Satoshi Ito. Assessment of chimeric mice with humanized livers in new drug development: generation of pharmacokinetics, metabolism and toxicity data for selecting the final candidate compound. Xenobiotica 2016, 46 (6) , 557-569. https://doi.org/10.3109/00498254.2015.1091113
    39. H. Q. Nguyen, E. Kimoto, E. Callegari, R. S. Obach. Mechanistic Modeling to Predict Midazolam Metabolite Exposure from In Vitro Data. Drug Metabolism and Disposition 2016, 44 (5) , 781-791. https://doi.org/10.1124/dmd.115.068601
    40. J. Iegre, M. A. Hayes, R. A. Thompson, L. Weidolf, E. M. Isin. Database Extraction of Metabolite Information of Drug Candidates: Analysis of 27 AstraZeneca Compounds with Human Absorption, Distribution, Metabolism, and Excretion Data. Drug Metabolism and Disposition 2016, 44 (5) , 732-740. https://doi.org/10.1124/dmd.115.067850
    41. S.-E. W. Huskey, C.-q. Zhu, M. M. Lin, R. R. Forseth, H. Gu, O. Simon, F. K. Eggimann, M. Kittelmann, A. Luneau, A. Vargas, H. Li, L. Wang, H. J. Einolf, J. Zhang, S. Favara, H. He, J. B. Mangold. Identification of Three Novel Ring Expansion Metabolites of KAE609, a New Spiroindolone Agent for the Treatment of Malaria, in Rats, Dogs, and Humans. Drug Metabolism and Disposition 2016, 44 (5) , 653-664. https://doi.org/10.1124/dmd.115.069112
    42. Nico Scheer, Ian D. Wilson. A comparison between genetically humanized and chimeric liver humanized mouse models for studies in drug metabolism and toxicity. Drug Discovery Today 2016, 21 (2) , 250-263. https://doi.org/10.1016/j.drudis.2015.09.002
    43. Dan Xu, Gary Peltz. Can Humanized Mice Predict Drug “Behavior” in Humans?. Annual Review of Pharmacology and Toxicology 2016, 56 (1) , 323-338. https://doi.org/10.1146/annurev-pharmtox-010715-103644
    44. J. Matthew Hutzler, Barbara J. Ring, Shelby R. Anderson. Low-Turnover Drug Molecules: A Current Challenge for Drug Metabolism Scientists. Drug Metabolism and Disposition 2015, 43 (12) , 1917-1928. https://doi.org/10.1124/dmd.115.066431
    45. Thomas A. Baillie. Chemically Reactive Versus Stable Drug Metabolites: Role in Adverse Drug Reactions. 2015, 202-226. https://doi.org/10.1039/9781782622376-00202
    46. Francisco Altamirano, Zhao V. Wang, Joseph A. Hill. Cardioprotection in ischaemia–reperfusion injury: novel mechanisms and clinical translation. The Journal of Physiology 2015, 593 (17) , 3773-3788. https://doi.org/10.1113/JP270953
    47. Kota Kato, Masato Ohbuchi, Satoko Hamamura, Hiroki Ohshita, Yasuhiro Kazuki, Mitsuo Oshimura, Koya Sato, Naoyuki Nakada, Akio Kawamura, Takashi Usui, Hidetaka Kamimura, Chise Tateno. Development of Murine Cyp3a Knockout Chimeric Mice with Humanized Liver. Drug Metabolism and Disposition 2015, 43 (8) , 1208-1217. https://doi.org/10.1124/dmd.115.063479
    48. Ari Tolonen, Olavi Pelkonen. Analytical challenges for conducting rapid metabolism characterization for QIVIVE. Toxicology 2015, 332 , 20-29. https://doi.org/10.1016/j.tox.2013.08.010
    49. Dan Xu, Manhong Wu, Sachiko Nishimura, Toshihiko Nishimura, Sara A. Michie, Ming Zheng, Zicheng Yang, Alexander John Yates, Jeffrey S. Day, Kathleen M. Hillgren, Saori Takedai Takeda, Yuan Guan, Yingying Guo, Gary Peltz. Chimeric TK-NOG Mice: A Predictive Model for Cholestatic Human Liver Toxicity. Journal of Pharmacology and Experimental Therapeutics 2015, 352 (2) , 274-280. https://doi.org/10.1124/jpet.114.220798
    50. Thomas J. Bateman, Vijay G.B. Reddy, Masakazu Kakuni, Yoshio Morikawa, Sanjeev Kumar. Application of Chimeric Mice with Humanized Liver for Study of Human-Specific Drug Metabolism. Drug Metabolism and Disposition 2014, 42 (6) , 1055-1065. https://doi.org/10.1124/dmd.114.056978
    51. T. Eric Ballard, Christine C. Orozco, R. Scott Obach. Generation of Major Human Excretory and Circulating Drug Metabolites Using a Hepatocyte Relay Method. Drug Metabolism and Disposition 2014, 42 (5) , 899-902. https://doi.org/10.1124/dmd.114.057026
    52. Yoshiyuki Igawa, Tomomichi Fujitani, Bharti Shah, Charles Oo, Yasushi Kanai. In vitro and in vivo metabolism of a novel chymase inhibitor, SUN13834, and the predictability of human metabolism using mice with humanized liver. Xenobiotica 2014, 44 (2) , 154-163. https://doi.org/10.3109/00498254.2013.865857
    53. John R. Foster, Garry Lund, Svetlana Sapelnikova, D. Lorne Tyrrell, Norman M. Kneteman. Chimeric rodents with humanized liver: bridging the preclinical/clinical trial gap in ADME/toxicity studies. Xenobiotica 2014, 44 (2) , 109-122. https://doi.org/10.3109/00498254.2013.867553
    54. Natalia A. Penner, Joanna Zgoda‐Pols, Chandra Prakash. Early Assessment of Exposure of Drug Metabolites in Humans Using Mass Spectrometry. 2014, 1-29. https://doi.org/10.1002/9781118541203.xen0031
    55. Takako Ohkura, Kunihiro Ohta, Takuya Nagao, Kumiko Kusumoto, Akiko Koeda, Tadayoshi Ueda, Tomoko Jomura, Takeshi Ikeya, Emiko Ozeki, Kazuki Wada, Kazushi Naitoh, Yukiko Inoue, Naoki Takahashi, Hisakazu Iwai, Hiroshi Arakawa, Takuo Ogihara. Evaluation of Human Hepatocytes Cultured by Three-dimensional Spheroid Systems for Drug Metabolism. Drug Metabolism and Pharmacokinetics 2014, 29 (5) , 373-378. https://doi.org/10.2133/dmpk.DMPK-13-RG-105
    56. Ragu Ramanathan, Dil M. Ramanathan. Metabolites in Safety Testing. 2013, 71-82. https://doi.org/10.1002/9781118671276.ch7
    57. Gary Peltz. Can ‘humanized’ mice improve drug development in the 21st century?. Trends in Pharmacological Sciences 2013, 34 (5) , 255-260. https://doi.org/10.1016/j.tips.2013.03.005
    58. Toshihiko Nishimura, Yajing Hu, Manhong Wu, Edward Pham, Hiroshi Suemizu, Menashe Elazar, Michael Liu, Ramazan Idilman, Cihan Yurdaydin, Peter Angus, Catherine Stedman, Brian Murphy, Jeffrey Glenn, Masato Nakamura, Tatsuji Nomura, Yuan Chen, Ming Zheng, William L. Fitch, Gary Peltz. Using Chimeric Mice with Humanized Livers to Predict Human Drug Metabolism and a Drug-Drug Interaction. Journal of Pharmacology and Experimental Therapeutics 2013, 344 (2) , 388-396. https://doi.org/10.1124/jpet.112.198697
    59. David S Wagner, Jill L Pirhalla, Gary D Bowers. Metabolite Structure Analysis by High-Resolution MS: Supporting Drug-Development Studies. Bioanalysis 2013, 5 (4) , 463-479. https://doi.org/10.4155/bio.13.3
    60. P Ballard, P Brassil, K H Bui, H Dolgos, C Petersson, A Tunek, P J H Webborn. Metabolism and pharmacokinetic optimization strategies in drug discovery. 2013, 135-155. https://doi.org/10.1016/B978-0-7020-4299-7.00010-X
    61. Seigo Sanoh, Aya Horiguchi, Kazumi Sugihara, Yaichiro Kotake, Yoshitaka Tayama, Naoto Uramaru, Hiroki Ohshita, Chise Tateno, Toru Horie, Shigeyuki Kitamura, Shigeru Ohta. Predictability of Metabolism of Ibuprofen and Naproxen Using Chimeric Mice with Human Hepatocytes. Drug Metabolism and Disposition 2012, 40 (12) , 2267-2272. https://doi.org/10.1124/dmd.112.047555
    62. Kristin Samuelsson, Kathryn Pickup, Sunil Sarda, John G. Swales, Yoshio Morikawa, Timothy Schulz-Utermoehl, Michael Hutchison, Ian D. Wilson. Pharmacokinetics and metabolism of midazolam in chimeric mice with humanised livers. Xenobiotica 2012, 42 (11) , 1128-1137. https://doi.org/10.3109/00498254.2012.689888
    63. Debra Luffer-Atlas. The early estimation of circulating drug metabolites in humans. Expert Opinion on Drug Metabolism & Toxicology 2012, 8 (8) , 985-997. https://doi.org/10.1517/17425255.2012.693159
    64. Peter Ballard, Patrick Brassil, Khanh H. Bui, Hugues Dolgos, Carl Petersson, Anders Tunek, Peter J. H. Webborn. The right compound in the right assay at the right time: an integrated discovery DMPK strategy. Drug Metabolism Reviews 2012, 44 (3) , 224-252. https://doi.org/10.3109/03602532.2012.691099
    65. Timothy Schulz-Utermoehl, Sunil Sarda, John R. Foster, Matt Jacobsen, J. Gerry Kenna, Yoshio Morikawa, Juuso Salmu, Gerhard Gross, Ian D. Wilson. Evaluation of the pharmacokinetics, biotransformation and hepatic transporter effects of troglitazone in mice with humanized livers. Xenobiotica 2012, 42 (6) , 503-517. https://doi.org/10.3109/00498254.2011.640716
    66. Michael D. Coleman, Louis L. Radulovic. Clinical Aspects of Drug Biotransformation: An OverviewDedicated to the memory of Mark J. Winn, Ph.D.,1960–1993. 2012, 1-50. https://doi.org/10.1002/9780470921920.edm116
    67. Robert J. Greene, John A. Davis, Raju Subramanian, Molly R. Deane, Maurice G. Emery, J. Greg Slatter. Regiospecific and Stereospecific Triangulation of the Structures of Metabolites Formed by Sequential Metabolism at Multiple Prochiral Centers. Drug Metabolism and Disposition 2012, 40 (5) , 928-942. https://doi.org/10.1124/dmd.111.043166
    68. Graham Lappin, Mark Seymour, Gerhard Gross, Martin J⊘rgensen, Morten Kall, Lisbet Kværn⊘. Meeting The Mist Regulations: Human Metabolism in Phase I Using Ams And A Tiered Bioanalytical Approach. Bioanalysis 2012, 4 (4) , 407-416. https://doi.org/10.4155/bio.11.334
    69. Thomas A. Baillie. Drug Metabolism in Drug Safety Evaluation. 2012, 1-24. https://doi.org/10.1002/9780470921920.edm054
    70. Raju Subramanian, J. Greg Slatter. Safety Testing of Drug Metabolites: A Practical Approach for the Implementation of the MIST Guidance in PKDM. 2012, 1-17. https://doi.org/10.1002/9780470921920.edm076
    71. Shelby Anderson, Debra Luffer‐Atlas, Mary Pat Knadler. Predicting Human Biotransformation Pathways. 2012, 1-27. https://doi.org/10.1002/9780470921920.edm120
    72. Justin D. Lutz, Nina Isoherranen. Prediction of Relative In Vivo Metabolite Exposure from In Vitro Data Using Two Model Drugs: Dextromethorphan and Omeprazole. Drug Metabolism and Disposition 2012, 40 (1) , 159-168. https://doi.org/10.1124/dmd.111.042200
    73. N. H. Schebb, B. Franze, R. Maul, A. Ranganathan, B. D. Hammock. In Vitro Glucuronidation of the Antibacterial Triclocarban and Its Oxidative Metabolites. Drug Metabolism and Disposition 2012, 40 (1) , 25-31. https://doi.org/10.1124/dmd.111.042283
    74. R. Scott Obach, Angus N. Nedderman, Dennis A. Smith. Radiolabelled mass-balance excretion and metabolism studies in laboratory animals: are they still necessary?. Xenobiotica 2012, 42 (1) , 46-56. https://doi.org/10.3109/00498254.2011.621985
    75. Angus N.R. Nedderman, Gordon J. Dear, Stephanie North, R. Scott Obach, David Higton. From definition to implementation: a cross-industry perspective of past, current and future MIST strategies. Xenobiotica 2011, 41 (8) , 605-622. https://doi.org/10.3109/00498254.2011.562330
    76. Ronald E. White. Progression of Drug Metabolism. 2011, 1-12. https://doi.org/10.1002/9780470929278.ch1
    77. Takashi Izumi. Assessment of Drug Metabolites. Drug Metabolism and Pharmacokinetics 2011, 26 (2) , 121-122. https://doi.org/10.2133/dmpk.DMPK-11-PF-902
    78. Baskar Nammalwar, Richard A. Bunce, Doris M. Benbrook, Tao Lu, Hui-Fang Li, Ya-Dong Chen, K. Darrell Berlin. Synthesis of N -[3,4-Dihydro-4-(acetoxymethyl)-2,2,4-trimethyl-2 H -1-benzothiopyran-6-yl]- N ′-(4-nitrophenyl)thiourea and N -[3,4-dihydro-4-(hydroxymethyl)-2,2,4-trimethyl-2 H -1-benzothiopyran-6-yl]- N ′-(4-nitrophenyl)thiourea, a Major Metabolite of N -(3,4-Dihydro-2,2,4,4-tetramethyl-2 H -1-benzothiopyran-6-YL)- N ′-(4-nitrophenyl)thiourea. Phosphorus, Sulfur, and Silicon and the Related Elements 2010, 186 (1) , 189-204. https://doi.org/10.1080/10426507.2010.534521
    79. J. Greg Slatter. Safety Testing of Drug Metabolites: Mist Guidance Impact on the Practice of Industrial Drug Metabolism. 2010, 295-312. https://doi.org/10.1002/9780470890387.ch8
    80. Wendy WeiWei Wang, Salman R. Khetani, Stacy Krzyzewski, David B. Duignan, R. Scott Obach. Assessment of a Micropatterned Hepatocyte Coculture System to Generate Major Human Excretory and Circulating Drug Metabolites. Drug Metabolism and Disposition 2010, 38 (10) , 1900-1905. https://doi.org/10.1124/dmd.110.034876
    81. Justin D Lutz, Yasushi Fujioka, Nina Isoherranen. Rationalization and prediction of in vivo metabolite exposures: the role of metabolite kinetics, clearance predictions and in vitro parameters. Expert Opinion on Drug Metabolism & Toxicology 2010, 6 (9) , 1095-1109. https://doi.org/10.1517/17425255.2010.497487
    82. Ping Yi, Debra Luffer-Atlas. A Radiocalibration Method with Pseudo Internal Standard to Estimate Circulating Metabolite Concentrations. Bioanalysis 2010, 2 (7) , 1195-1210. https://doi.org/10.4155/bio.10.81
    83. Shelby Anderson, Mary Pat Knadler, Debra Luffer-Atlas. Overview of Metabolite Safety Testing from an Industry Perspective. Bioanalysis 2010, 2 (7) , 1249-1261. https://doi.org/10.4155/bio.10.67
    84. Andy Zöllner, Daniela Buchheit, Markus R Meyer, Hans H Maurer, Frank T Peters, Matthias Bureik. Production of Human Phase 1 and 2 Metabolites by Whole-Cell Biotransformation with Recombinant Microbes. Bioanalysis 2010, 2 (7) , 1277-1290. https://doi.org/10.4155/bio.10.80
    85. Ragu Ramanathan, Jonathan L Josephs, Mohammed Jemal, Mark Arnold, W Griffith Humphreys. Novel MS Solutions Inspired by MIST. Bioanalysis 2010, 2 (7) , 1291-1313. https://doi.org/10.4155/bio.10.83
    86. Graham Lappin, Mark Seymour. Addressing Metabolite Safety During First-In-Man Studies Using 14 C-Labeled Drug and Accelerator Mass Spectrometry. Bioanalysis 2010, 2 (7) , 1315-1324. https://doi.org/10.4155/bio.10.87
    87. C. D. Markert, M. P. Meaney, K. A. Voelker, R. W. Grange, H. W. Dalley, J. K. Cann, M. Ahmed, B. Bishwokarma, S. J. Walker, S. X. Yu, M. Brown, M. W. Lawlor, A. H. Beggs, M. K. Childers. Functional muscle analysis of the Tcap knockout mouse. Human Molecular Genetics 2010, 19 (11) , 2268-2283. https://doi.org/10.1093/hmg/ddq105
    88. C B Frederick, R S Obach. Metabolites in Safety Testing: “MIST” for the Clinical Pharmacologist. Clinical Pharmacology & Therapeutics 2010, 87 (3) , 345-350. https://doi.org/10.1038/clpt.2009.283
    89. Stephen R Dueker, Peter N Lohstroh, Jason A Giacomo, Le T Vuong, Bradly D Keck, John S Vogel. Early Human ADME Using Microdoses and Microtracers: Bioanalytical Considerations. Bioanalysis 2010, 2 (3) , 441-454. https://doi.org/10.4155/bio.10.8
    90. Hidetaka Kamimura, Naoyuki Nakada, Katsuhiro Suzuki, Ayako Mera, Kinya Souda, Yuichi Murakami, Kohichiro Tanaka, Takafumi Iwatsubo, Akio Kawamura, Takashi Usui. Assessment of Chimeric Mice with Humanized Liver as a Tool for Predicting Circulating Human Metabolites. Drug Metabolism and Pharmacokinetics 2010, 25 (3) , 223-235. https://doi.org/10.2133/dmpk.25.223
    91. Akihiro INANO. . Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics 2010, 41 (4) , 121S-122S. https://doi.org/10.3999/jscpt.41.121S
    92. Ragu Ramanathan, S Çömezoglu, W Humphreys. Metabolite Identification Strategies and Procedures. 2009, 127-203. https://doi.org/10.1201/9781420092219-c5
    93. Gerhard Gross, Ian Wilson. Issues in the Safety Testing of Metabolites. Future Medicinal Chemistry 2009, 1 (8) , 1381-1390. https://doi.org/10.4155/fmc.09.101
    94. Olavi Pelkonen, Ari Tolonen, Timo Korjamo, Miia Turpeinen, Hannu Raunio. From Known Knowns to Known Unknowns: Predicting in Vivo Drug Metabolites. Bioanalysis 2009, 1 (2) , 393-414. https://doi.org/10.4155/bio.09.32
    95. Thomas N. Thompson. Chapter 22 Safety Testing of Drug Metabolites. 2009, 459-474. https://doi.org/10.1016/S0065-7743(09)04422-4

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