Archives of Toxicology

, Volume 93, Issue 3, pp 615–621 | Cite as

Importance of in vitro conditions for modeling the in vivo dose in humans by in vitroin vivo extrapolation (IVIVE)

  • Engi Abdel Hady AlgharablyEmail author
  • Reinhold Kreutz
  • Ursula Gundert-Remy
Toxicokinetics and Metabolism


In vitro studies are increasingly proposed to replace in vivo toxicity testing of substances. We set out to apply physiologically based pharmacokinetic (PBPK) modeling to predict the in vivo dose of amiodarone that leads to the same concentration–time profile in the supernatant and the cell lysate of cultured primary human hepatic cells (PHH). A PBPK human model was constructed based on the structure and tissue distribution of amiodarone in a rat model and using physiological human parameters. The predicted concentration–time profile in plasma was in agreement with human experimental data with the unbound fraction of amiodarone in plasma crucially affecting the goodness-of-fit. Using the validated kinetic model, we subsequently described the in vitro concentration–time data of amiodarone in PHH culture. However, this could be only appropriately modeled under conditions of zero protein binding and the very low clearance of the in vitro system in PHH culture. However, these represent unphysiological conditions and, thus, the main difference between the in vivo and the in vitro systems. Our results reveal that, for meaningful quantitative extrapolation from in vitro to in vivo conditions in PBPK studies, it is essential to avoid non-intended differences between these conditions. Specifically, clearance and protein binding, as demonstrated in our analysis of amiodarone modeling, are important parameters to consider.


Pharmacokinetics Amiodarone Animal alternatives In silico Physiologically based pharmacokinetic modeling Hepatotoxicity 



We would like to thank Dr. E. Di Consiglio and Dr. E. Testai, Istituto Superiore di Sanità, Environment and Primary Prevention Dept., Mechanisms of Toxicity Unit, Rome, Italy, for providing us with the concentration–time data of amiodarone in the supernatant and the human hepatic cells. We also thank Dr. Yuan-Sheng Zhao for the support with the implementation of the rat model.


  1. Adler S et al (2011) Alternative (non-animal) methods for cosmetics testing: current status and future prospects—2010. Arch Toxicol 85:367–485. CrossRefGoogle Scholar
  2. Andreasen F, Agerbaek H, Bjerregaard P, Gotzsche H (1981) Pharmacokinetics of amiodarone after intravenous and oral administration. Eur J Clin Pharmacol 19:293–299CrossRefGoogle Scholar
  3. Avdeef A, Box KJ, Comer JE, Hibbert C, Tam KY (1998) pH-metric logP 10. Determination of liposomal membrane-water partition coefficients of ionizable drugs. Pharm Res 15:209–215CrossRefGoogle Scholar
  4. Barter ZE et al (2007) Scaling factors for the extrapolation of in vivo metabolic drug clearance from in vitro data: reaching a consensus on values of human microsomal protein and hepatocellularity per gram of liver. Curr Drug Metab 8:33–45CrossRefGoogle Scholar
  5. Bessems JG et al (2014) PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA–EURL ECVAM ADME workshop Regulatory. Toxicol Pharmacol 68:119–139Google Scholar
  6. Brown RP, Delp MD, Lindstedt SL, Rhomberg LR, Beliles RP (1997) Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health 13:407–484. CrossRefGoogle Scholar
  7. Chen Y, Mao J, Hop CECA (2015) physiologically based pharmacokinetic modeling to predict drug–drug interactions involving inhibitory metabolite: a case study of amiodarone drug. Metab Dispos 43:182–189. CrossRefGoogle Scholar
  8. Coecke S et al (2013) Toxicokinetics as a key to the integrated toxicity risk assessment based primarily on non-animal approaches. Toxicol In Vitro 27:1570–1577. CrossRefGoogle Scholar
  9. Dan GA et al (2018) Antiarrhythmic drugs-clinical use and clinical decision making: a consensus document from the European Heart Rhythm Association (EHRA) and European Society of Cardiology (ESC) Working Group on Cardiovascular Pharmacology, endorsed by the Heart Rhythm Society (HRS), Asia-Pacific Heart Rhythm Society (APHRS) and International Society of Cardiovascular Pharmacotherapy (ISCP) Europace: European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of. Cardiology 20:731–732. anGoogle Scholar
  10. Freedman MD, Somberg JC (1991) Pharmacology and pharmacokinetics of amiodarone. J Clin Pharmacol 31:1061–1069CrossRefGoogle Scholar
  11. Groothuis FA, Heringa MB, Nicol B, Hermens JL, Blaauboer BJ, Kramer NI (2015) Dose metric considerations in in vitro assays to improve quantitative in vitro–in vivo dose extrapolations. Toxicology 332:30–40. CrossRefGoogle Scholar
  12. Hamon J, Renner M, Jamei M, Lukas A, Kopp-Schneider A, Bois FY (2015) Quantitative in vitro to in vivo extrapolation of tissues toxicity. Toxicol In Vitro 30:203–216. CrossRefGoogle Scholar
  13. Hartung T (2010) Food for thought… on alternative methods for. chemical safety testing. Altex 27:3–14CrossRefGoogle Scholar
  14. Kannan R, Nademanee K, Hendrickson JA, Rostami HJ, Singh BN (1982) Amiodarone kinetics after oral doses. Clin Pharmacol Ther 31:438–444CrossRefGoogle Scholar
  15. Kessel M, Frank F (2007) A better prescription for drug-development financing. Nat Biotechnol 25:859. CrossRefGoogle Scholar
  16. Kramer NI, Di Consiglio E, Blaauboer BJ, Testai E (2015) Biokinetics in repeated-dosing in vitro drug toxicity studies. Toxicol In Vitro 30:217–224. CrossRefGoogle Scholar
  17. Latini R, Tognoni G, Kates RE (1984) Clinical pharmacokinetics of amiodarone. Clin Pharmacokinet 9:136–156. CrossRefGoogle Scholar
  18. Leist M, Hasiwa N, Rovida C, Daneshian M, Basketter D, Kimber I, Clewell H, Gocht T, Goldberg A, Busquet F, Rossi A-M, Schwarz M, Stephens M, Taalman R, Knudsen T, McKim J, Harris G, Pamies D, Hartung T (2014) Consensus report on the future of animal-free systemic toxicity testing. Altern Anim Exp ALTEX 31:341–356. Google Scholar
  19. Louisse J, Beekmann K, Rietjens IMCM (2017) Use of physiologically based kinetic modeling-based reverse dosimetry to predict in vivo toxicity from in vitro data. Chem Res Toxicol 30:114–125. CrossRefGoogle Scholar
  20. Lu J-T, Cai Y, Chen F, Jia W-W, Hu Z-Y, Zhao Y-S (2016) A physiologically based pharmacokinetic model of amiodarone and its metabolite desethylamiodarone in rats: pooled analysis of published data. Eur J Drug Metab Pharmacokinet 41:689–703. CrossRefGoogle Scholar
  21. Mielke H, Di Consiglio E, Kreutz R, Partosch F, Testai E, Gundert-Remy U (2017) The importance of protein binding for the in vitro-in vivo extrapolation (IVIVE)-example of ibuprofen, a highly protein-bound substance. Arch Toxicol 91:1663–1670. CrossRefGoogle Scholar
  22. Ohyama K, Nakajima M, Suzuki M, Shimada N, Yamazaki H, Yokoi T (2000) Inhibitory effects of amiodarone and its N-deethylated metabolite on human cytochrome P450 activities: prediction of in vivo drug interactions. Br J Clin Pharmacol 49:244–253CrossRefGoogle Scholar
  23. Pomponio G et al (2015) In vitro kinetics of amiodarone and its major metabolite in two human liver cell models after acute and repeated treatments. Toxicol In Vitro 30:36–51. CrossRefGoogle Scholar
  24. Pridgeon CS et al (2018) Innovative organotypic in vitro models for safety assessment: aligning with regulatory requirements and understanding models of the heart, skin, and liver as paradigms. Arch Toxicol 92:557–569. CrossRefGoogle Scholar
  25. Riva E, Gerna M, Latini R, Giani P, Volpi A, Maggioni A (1982) Pharmacokinetics of amiodarone in man. J Cardiovasc Pharmacol 4:264–269CrossRefGoogle Scholar
  26. Trivier JM, Libersa C, Belloc C, Lhermitte M (1993) Amiodarone N-deethylation in human liver microsomes: involvement of cytochrome P450 3A enzymes (first report). Life Sci 52:PL91–P96CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Engi Abdel Hady Algharably
    • 1
    • 2
    Email author
  • Reinhold Kreutz
    • 1
  • Ursula Gundert-Remy
    • 1
  1. 1.Institute of Clinical Pharmacology and Toxicology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of HealthBerlinGermany
  2. 2.Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams UniversityCairoEgypt

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