Abstract
Drug metabolism studies play a critical role in the discovery and development of new chemical entities. These studies provide in-depth understanding of absorption, distribution, metabolism, and excretion (ADME) properties of a drug. Optimization of these properties is important to ensure that the exposure is sufficient to achieve proof of concept, and ultimately efficacy and safety in clinical trials to address unmet medical need. In the past two decades, multiple in silico, in vitro, and in vivo ADME tools have been developed and implemented in various stages of the drug discovery and development process to alert chemists of potential ADME issues in the clinic. Most of the ADME studies in drug discovery are conducted using cold material. However, ADME studies in drug development are generally conducted using radiolabeled (3H or 14C) material. The use of radiolabeled material offers a unique mode of quantification of total drug-related molecules.
This chapter describes, in detail, the utility and the challenges of these tools both with in vitro and in vivo metabolism studies that are used to design better molecules that have properties that include lower systemic clearance, and also assist in the selection of nonclinical species for use in safety assessment studies in preclinical development. Additionally, these tools aid in the understanding of reactive metabolites to avoid idiosyncratic adverse drug reactions. Practical case examples are provided.
References and Further Reading
Arrowsmith J, Miller P (2013) Trial watch: phase II and phase III attrition rates 2011–2012. Nat Rev Drug Discov 12(8):569
Ballard TE, Orozco CC, Obach RS (2014) Generation of major human excretory and circulating drug metabolites using a hepatocyte relay method. Drug Metab Dispos 42(5):899–902
Barton P, Relay RJ (2016) A new paradigm for navigating compound property related drug attrition. Drug Discov Today 21(1):72–81
Bjornsson TD, Callaghan JT, Einolf HJ, Fischer V, Gan L, Grimm S, Kao J, King SP, Miwa G, Ni L (2013) Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism/Clinical Pharmacology Technical Working Group; FDA Center for Drug Evaluation and Research (CDER) The conduct of in vitro and in vivo drug-drug interaction studies: a Pharmaceutical Research and Manufacturers of America (PhRMA) perspective. Drug Metab Dispos 31:815–832
Bohnert T, Prakash C (2012) ADME profiling in drug discovery and development. In: Shahi J (ed) An overview in encyclopedia of drug metabolism and interactions, vol 2. Wiley, pp 1–42
Bohnert T, Patel A, Templeton I, Chen Y, Lu C, Lai G, Leung L, Tse S, Einolf HJ, Wang YY, Sinz M, Stearns R, Walsky R, Geng W, Sudsakorn S, Moore D, He L, Wahlstrom J, Keirns J, Narayanan R, Lang D, Yang X (2016) International consortium for innovation and quality in pharmaceutical development (IQ) victim drug-drug interactions working group evaluation of a new molecular entity as a victim of metabolic drug-drug interactions—an industry perspective. Drug Metab Dispos 44(8):1399–1423
Bonn P, Svanberg P, Janefeldt A, Hultman I, Grime KK (2016) Determination of human hepatocyte intrinsic clearance for slowly metabolized compounds: comparison of a primary hepatocyte/stromal cell co-culture with plated primary hepatocytes and HepaRG. Drug Metab Dispos 44:527–533
Burton RD, Hieronymus T, Chamem T, Heim D, Anderson S, Zhu X, Hutzler JM (2018) Assessment of the biotransformation of low turnover drugs in the HμREL human hepatocyte coculture model. Drug Metab Dispos 46:1617–1622
Caldwell GW, Yan Z, Tang W, Dasgupta M, Hasting B (2009) ADME optimization and toxicity assessment in early- and late-phase drug discovery. Curr Top Med Chem 9(11):965–980
Cerny MA (2016) Prevalence of non–cytochrome P450–mediated metabolism in food and drug administration–approved oral and intravenous drugs: 2006–2015. Drug Metab Dispos 44(8):1246–1252
Chiba M, Ishii Y, Sugiyama Y (2009) Prediction of hepatic clearance in human from in vitro data for successful drug development. AAPS J 11(2):262–276
Cruciani G, Millettia F, Storchib L, Sfornab G (2009) In Silico pKa prediction and ADME profiling. Chem Biodivers 6(11):1812–1821
Dai D, Yang H, Nabhan S, Liu H, Hickman D, Liu G, Zacher J, Vutikullird A, Prakash C, Agresta S, Bowden C, Fan B (2019) Effect of itraconazole, food, and ethnic origin on the pharmacokinetics of ivosidenib in healthy subjects. Eur J Clin Pharmacol 75:1099–1108
DiMasi JA, Feldman L, Seckler A, Wilson A (2010) Trends in risks associated with new drug development: success rates for investigational drugs. Clin Pharmacol Ther 87:272–277
Evans DC, Watt AP, Nicoll-Griffith DA, Baillie T (2004) Drug-protein adducts: an industry perspective on minimizing the potential for drug bioactivation in drug discovery and development. Chem Res Toxicol 17:3–6
FDA Guidance for Industry (2010) Safety testing of drug metabolites guidance for industry. U.S. Department of Health and Human Services Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, MD
Foster AJ, Chouhan B, Regan SL et al (2019) Integrated in vitro models for hepatic safety and metabolism: evaluation of a human Liver-Chip and liver spheroid. Arch Toxicol 93:1021–1037
Fura A, Shu Y, Zhu M, Hanson RL, Roongta V, Humphreys WG (2004) Discovering drugs through biological transformation: role of pharmacologically active metabolites in drug discovery. J Med Chem 47:4339–4351
Gerisch M, Heinig R, Engelen A, Lang D, Kolkhof P, Radtke M, Platzek J, Lovis K, Rohde G, Schwarz T (2018) Biotransformation of finerenone, a novel nonsteroidal mineralocorticoid receptor antagonist, in dogs, rats, and humans, in vivo and in vitro. Drug Metab Dispos 46(11):1546–1555
Gomez-Lechon JM, Lahoz A, Gombau L, Castell JV, Donato MT (2010) In vitro evaluation of potential hepatotoxicity induced by drugs. Curr Pharm Des 16:1963–1977
Haglund J, Halldin MM, Brunnström A, Eklund G, Kautiainen A, Sandholm A, Iverson SL (2014) Pragmatic approaches to determine the exposures of drug metabolites in preclinical and clinical subjects in the MIST evaluation of the clinical development phase. Chem Res Toxicol 27(4):601–610
Hamilton RA, Garnett WR, Kline BJ (1981) Determination of mean valproic acid serum level by assay of a single pooled sample. Clin Pharmacol Ther 29(3):408–413
Hop CECA, Wang Z, Chen Q, Kwei G (1998) Plasma-pooling methods to increase throughput for in vivo pharmacokinetic screening. J Pharm Sci 87(7):901–903
Hwang TJ, Carpenter D, Lauffenburger JC, Wang B, Franklin JM, Kesselheim AS (2016) Failure of investigational drugs in late-stage clinical development and publication of trial results. JAMA Intern Med 176(12):1826–1833
International Conference on Harmonization (ICH) (2010) M3(R2) nonclinical safety studies for the conduct of human clinical trials and marketing authorization of pharmaceuticals. The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use, Geneva, Switzerland
Kalgutkar A, Griffith D, Ryder T, Sun H, Miao Z, Bauman J, Didiuk JM, Frederick K, Zhao S, Prakash C, Soglia J, Bagley S, Bechle B, Kelley R, Dirico K, Zawistoski M, Li J, Oliver R, Guzman-Perez A, Liu K, Walker D, Benbow J, Morris J (2010) Discovery tactics to mitigate toxicity risks due to reactive metabolite formation with 2-(2-hydroxyaryl)-5-(trifluoromethyl)pyrido[4,3-d]pyrimidin-4(3H)-one derivatives, potent calcium-sensing receptor antagonists and clinical candidate(s) for the treatment of osteoporosis. Chem Res Toxicol 23(4):1115–1126
Kamel A, Harriman S, Prakash C (2013) Strategies for the identification of unusual and novel metabolites using derivatization, hydrogen-deuterium exchange (HDX) and liquid chromatography-nuclear magnetic resonance (LC-NMR) spectroscopy. In: Lee PW, Aizawa H, Gan LL, Prakash C, Zhong D (eds) Techniques in handbook of metabolic pathways of xenobiotics, vol 2. Wiley, pp 591–618
Kamel A, Bowlin S, Hosea N, Arkilo D, Laurenza A (2021) In vitro metabolism of slowly cleared TAK-041. Drug Metab Dispos 49(2):121–132
Karin A, Sternbeck S, Terelius Y (2021) Evaluation of ADMET predictor in early discovery drug metabolism and pharmacokinetics project work. Drug Metab Dispos 50:95–104
Kitamura Y, Saeki KI (2020) Phenotypic analysis of human CYP 2C9 polymorphisms using fluorine-substituted tolbutamide. Drug Discov Ther 14(4):204–208
Manevski N, King L, Pitt WR, Lecomte F, Toselli F (2019) Metabolism by aldehyde oxidase: drug design and complementary approaches to challenges in drug discovery. J Med Chem 62(24):10955–10994
Miao Z, Scott DO, Griffith DA, Day R, Prakash C (2011) Excretion, metabolism, and pharmacokinetics of 1-(8-(2-chlorophenyl)-9-(4 chlorophenyl)-9h-purin-6-yl)-4-(ethylamino)piperidine-4-carboxamide, cp-945,598, a selective cannabinoid receptor antagonist, in rats, mice and dogs: species and gender related differences. Drug Metab Dispos 39:2191–2208
Miao Z, Sun H, Liras J, Prakash C (2012) Excretion, metabolism, and pharmacokinetics of 1-(8-(2-chlorophenyl)-9-(4 chlorophenyl)-9h-purin-6-yl)-4-(ethylamino)piperidine-4-carboxamide, cp-945,598, a selective cannabinoid receptor antagonist in healthy male volunteers. Drug Metab Dispos 40:568–578
Morgan P, Van Der Graaf PH, Arrowsmith J, Feltner DE, Drummond KS, Wegner CD, Street SDA (2012) Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov Today 17:419–424
Onakpoya IJ, Heneghan CJ, Aronson JK (2016) Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med 14:10
Penner N, Woodward C, Prakash C (2012a) Drug metabolizing enzymes and biotransformation reactions. In: Zhang D, Surapaneni S (eds) ADME-enabling technologies in drug design and development, pp 545–565
Penner N, Xu L, Prakash C (2012b) Radiolabeled absorption, distribution, metabolism, and excretion studies in drug development: why, when, and how? Chem Res Toxicol 25(3):513–531
Penner N, Zgoda-Pols J, Prakash C (2014) Early assessment of exposure of drug metabolites in humans using mass spectrometry. In: Lee PW, Aizawa H, Gan LL, Prakash C, Dafang Zhong D (eds) Handbook of metabolic pathways of xenobiotics, vol 2. Wiley, pp 693–722
Prakash C, Vaz ADN (2009) In: Xie W (ed) Drug metabolism: significance and challenges. Nuclear receptors in drug metabolism. Wiley, pp 1–42
Prakash C, Kamel A, Anderson W, Howard H (1997) Metabolism and excretion of the novel antipsychotic drug ziprasidone in rats after oral administration of a mixture of 14C- and 3H-labeled ziprasidone. Drug Metab Dispos 25(2):206–218
Prakash C, Kamel A, Miao Z (2004) In radiochemical tracers: essential tools for the drug metabolism studies. In: Dean DC, Filer CN, KE MC (eds) Syntheis and application of isotopically labelled compounds. Wiley, pp 115–120
Prakash C, Shaffer C, Nedderman A (2007) Analytical strategies for identifying drug metabolites. Mass Spectrom Rev 26:340–369
Prakash C, Sharma R, Gleave M, Nedderman A (2008a) In vitro screening techniques for reactive metabolites for minimizing the bioactivation potential in drug discovery. Curr Drug Metab 9(9):952–964
Prakash C, Chen W, Rossulek M, Johnson K, Zhang C, O'Connell T, Potchoiba M, Dalvie D (2008b) Metabolism, pharmacokinetics, and excretion of a cholesteryl ester transfer protein inhibitor, torcetrapib, in rats, monkeys, and mice: characterization of unusual and novel metabolites by high-resolution liquid chromatography-tandem mass spectrometry and 1H nuclear magnetic resonance. Drug Metab Dispos 36(10):2064–2079
Prakash C, Johnson K, Schroeder C, Potchoiba M (2008c) Metabolism, distribution, and excretion of a next generation selective estrogen receptor modulator, lasofoxifene, in rats and monkeys. Drug Metab Dispos 36(9):1753–1769
Prakash C, Altaf BFB, Agresta S, Liu H, Yang H (2019) Pharmacokinetics, absorption, metabolism, and excretion of [14C]ivosidenib (AG-120) in healthy male subjects. Cancer Chemother Pharmacol 83(5):837–848
Prakash C, Fan B, Ke A, Lee K, Yang H (2020) Physiologically based pharmacokinetic model predictions of ivosidenib (AG-120) as a victim of drug-drug interactions. Cancer Chemother Pharmacol 86(5):619–632
Riede J, Wollmann BM, Molden E, Ingelman-Sundberg M (2021) Primary human hepatocyte spheroids as an in vitro tool for investigating drug compounds with low hepatic clearance. Drug Metab Dispos 49(7):501–508
Rock D, Wahlstrom J, Wienkers L (2008) Cytochrome P450s: drug-drug interactions. In: Methods and principles in medicinal chemistry, vol 38, pp 197–246
Sanders JM, Beshore DC, Culberson JC, Fells JI, Imbriglio JE, Gunaydin H, Haidle AM, Labroli M, Mattioni BE, Sciammetta N, Shipe WD, Sheridan RP, Suen LM, Verras A, Walji A, Joshi EM, Bueters T (2017) Informing the selection of screening hit series with in silico absorption, distribution, metabolism, excretion, and toxicity profiles. J Med Chem 60:6771–6780
Saravanakumar A, Sadighi A, Ryu R, Akhlaghi F (2019) Physicochemical properties, biotransformation, and transport pathways of established and newly-approved medications: a systematic review of the top 200 most prescribed drugs versus the FDA-approved drugs between 2005 and 2016. Clin Pharmacokinet 58(10):1281–1294
Schadt S, Bister B, Chowdhury SK, Funk C, Hop CECA, Humphreys WG, Igarashi F, James AD, Kagan M, Cyrus Khojasteh S, Nedderman A, Prakash C, Runge F, Scheible H, Spracklin DK, Swart P, Tse S, Yuan J, Obach RS (2018) A decade in the MIST: learnings from investigations of drug metabolites in drug development under the “metabolites in safety testing” regulatory guidance. Drug Metab Dispos 46(6):865–878
Shaffer CL, Langer CS (2007) Metabolism of a 14C/3H-labeled GABAA receptor partial agonist in rat, dog and human liver microsomes: evaluation of a dual-radiolabel strategy. J Pharm Biomed Anal 43(4):1195–1205
Sinha K, Ghosh J, Sil PC (2022) Machine learning in drug metabolism study. Curr Drug Metab. https://doi.org/10.2174/1389200224666221227094144. Epub ahead of print. PMID: 36578255.
Smith SR, Lyman MJ, Ma B, Tweedie DJ, Menzel K (2021) Reaction phenotyping of low-turnover compounds in long-term hepatocyte cultures through persistent selective inhibition of cytochromes P450. Drug Metab Dispos 49(11):995–1002
Stepan AF, Karki K, Scott McDonald W, Dorff PH, Dutra JK, DiRico KJ, Won A, Subramanyam C, Efremov IV, O’Donnell CJ, Nolan CE, Becker SL, Pustilnik LR, Sneed B, Sun H, Lu Y, Robshaw AE, Riddell D, O'Sullivan TJ, Sibley E, Capetta S, Atchison K, Hallgren AJ, Miller E, Wood A, Obach RS (2011) Metabolism-directed design of oxetane-containing arylsulfonamide derivatives as γ-secretase inhibitors. J Med Chem 54:7772–7778
Stypinski D, Fostvedt L, Lam JL, Vaz A, Johnson TR, Boerma JS, Pithavala YK (2020) Metabolism, excretion, and pharmacokinetics of lorlatinib (PF-06463922) and evaluation of the impact of radiolabel position and other factors on comparability of data across 2 ADME studies. J Clin Pharmacol 60(9):1254–1267
Tyzack JD, Kirchmair J (2019) Computational methods and tools to predict cytochrome P450 metabolism for drug discovery. Chem Biol Drug Des 93:377–386
US Food and Drug Administration (FDA) (2020) In vitro drug interaction studies —cytochrome P450 enzyme-and transporter-mediated drug interactions. Guidance for industry. Draft Guidance Center for Drug Evaluation and Research (CDER). https://www.fda.gov/media/134582/download
Wager TT, Kormos BL, Brady JT, Will Y, Aleo MD, Stedman DB, Kuhn M, Chadrasekaran RY (2013) Improving the odds of success in drug discovery: choosing the best compounds for in vivo toxicology studies. J Med Chem 56:9771–9779
Wait JCM, Vaccharajani N, Mitroka J, Jemal M, Khan S, Bonacorsi SJ, Rinehart JK, Iyer RA (2006) Metabolism of [14C]gemopatrilat after oral administration to rats, dogs, and humans. Drug Metab Dispos 34(6):961–970
Wang WW, Khetani SR, Krzyzewski S, Duignan DB, Obach RS (2010) Assessment of a micropatterned hepatocyte coculture system to generate major human excretory and circulating drug metabolites. Drug Metab Dispos 38:1900–1905
Wang D, Liu W, Shen Z, Jiang L, Wang J, Li S, Li H (2019) Deep learning based drug metabolites prediction. Front Pharmacol 10:1586
Wen B, Fitch WL (2009) Screening and characterization of reactive metabolites using glutathione ethyl ester in combination with Q-trap mass spectrometry. J Mass Spectrom 44(1):90–10
White RE, Evans DC, Hop CE, Moore DJ, Prakash C, Surapaneni S, Tse FL (2013) Radiolabeled mass-balance excretion and metabolism studies in laboratory animals: a commentary on why they are still necessary. Xenobiotica 43:219–225
Xu L, Das B, Prakash C (2012) CYP450 enzymes in drug discovery and development: an overview. In: Encyclopedia of drug metabolism and interaction, vol 6, pp 1–28
Yang X, Atkinson K, Di L (2016) Novel cytochrome P450 reaction phenotyping for low-clearance compounds using the hepatocyte relay method. Drug Metab Dispos 44(3):460–465
Yu C, Chen CL, Gorycki FL, Neiss TG (2007) A rapid method for quantitatively estimating metabolites in human plasma in the absence of synthetic standards using a combination of liquid chromatography/mass spectrometry and radiometric detection. Rapid Commun Mass Spectrom 21:497–502
Yuan L, Kaplowitz N (2013) Mechanisms of drug-induced liver injury. Clin Liver Dis 17:507–518
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We thank Allyson Jenkins, Agios, for her editorial assistance.
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Das, B., Prakash, C. (2023). In Vitro and In Vivo Metabolism Studies. In: Hock, F.J., Gralinski, M.R., Pugsley, M.K. (eds) Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays. Springer, Cham. https://doi.org/10.1007/978-3-030-73317-9_96-1
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