Advertisement

The AAPS Journal

, 21:20 | Cite as

Quantitative Prediction of Human Hepatic Clearance for P450 and Non-P450 Substrates from In Vivo Monkey Pharmacokinetics Study and In Vitro Metabolic Stability Tests Using Hepatocytes

  • Haruka NishimutaEmail author
  • Takao Watanabe
  • Kiyoko Bando
Research Article
  • 111 Downloads

Abstract

Accurate prediction of human pharmacokinetics for drugs remains challenging, especially for non-cytochrome P450 (P450) substrates. Hepatocytes might be suitable for predicting hepatic intrinsic clearance (CLint) of new chemical entities, because they can be applied to various compounds regardless of the metabolic enzymes. However, it was reported that hepatic CLint is underestimated in hepatocytes. The purpose of the present study was to confirm the predictability of human hepatic clearance for P450 and non-P450 substrates in hepatocytes and the utility of animal scaling factors for the prediction using hepatocytes. CLint values for 30 substrates of P450, UDP-glucuronosyltransferase, flavin-containing monooxygenase, esterases, reductases, and aldehyde oxidase in human microsomes, human S9 and human, rat, and monkey hepatocytes were estimated. Hepatocytes were incubated in serum of each species. Furthermore, CLint values in human hepatocytes were corrected with empirical, monkey, and rat scaling factors. CLint values in hepatocytes for most compounds were underestimated compared to observed values regardless of the metabolic enzyme, and the predictability was improved by using the scaling factors. The prediction using human hepatocytes corrected with monkey scaling factor showed the highest predictability for both P450 and non-P450 substrates among the predictions using liver microsomes, liver S9, and hepatocytes with or without scaling factors. CLint values by this method for 80% and 90% of all compounds were within 2- and 3-fold of observed values, respectively. This method is accurate and useful for estimating new chemical entities, with no need to care about cofactors, localization of metabolic enzymes, or protein binding in plasma and incubation mixture.

KEY WORDS

hepatic clearance in vitro-in vivo extrapolation monkey non-P450 P450 

Notes

Supplementary material

12248_2019_294_MOESM1_ESM.docx (213 kb)
ESM 1 (DOCX 212 kb)

References

  1. 1.
    Obach RS. The prediction of human clearance from hepatic microsomal metabolism data. Curr Opin Drug Discov Dev 2013. 2001;4:36–44.Google Scholar
  2. 2.
    Chung WG, Park CS, Roh HK, Lee WK, Cha YN. Oxidation of ranitidine by isozymes of flavin-containing monooxygenase and cytochrome P450. Jpn J Pharmacol. 2000;84:213–20.CrossRefGoogle Scholar
  3. 3.
    Wienkers LC, Heath TG. Predicting in vivo drug interactions from in vitro drug discovery data. Nat Rev Drug Discov. 2005;4:825–33.CrossRefGoogle Scholar
  4. 4.
    Mordenti J. Pharmacokinetic scale-up: accurate prediction of human pharmacokinetic profiles from animal data. J Pharm Sci. 1985;74:1097–9.CrossRefGoogle Scholar
  5. 5.
    Ings RM. Interspecies scaling and comparisons in drug development and toxicokinetics. Xenobiotica. 1990;20:1201–31.CrossRefGoogle Scholar
  6. 6.
    Lavé T, Coassolo P, Reigner B. Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations. Clin Pharmacokinet. 1999;36:211–31.CrossRefGoogle Scholar
  7. 7.
    Houston JB. Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance. Biochem Pharmacol. 1994;47:1469–79.CrossRefGoogle Scholar
  8. 8.
    Iwatsubo T, Hirota N, Ooie T, Suzuki H, Shimada N, Chiba K, et al. Prediction of in vivo drug metabolism in the human liver from in vitro metabolism data. Pharmacol Ther. 1997;73:147–71.CrossRefGoogle Scholar
  9. 9.
    Hallifax D, Houston JB. Methodological uncertainty in quantitative prediction of human hepatic clearance from in vitro experimental systems. Curr Drug Metab. 2009;10:307–21.CrossRefGoogle Scholar
  10. 10.
    Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov. 2004;3:711–5.CrossRefGoogle Scholar
  11. 11.
    Margolis JM, Obach RS. Impact of nonspecific binding to microsomes and phospholipid on the inhibition of cytochrome P4502D6: implications for relating in vitro inhibition data to in vivo drug interactions. Drug Metab Dispos. 2003;31:606–11.CrossRefGoogle Scholar
  12. 12.
    Chiba M, Ishii Y, Sugiyama Y. Prediction of hepatic clearance in human from in vitro data for successful drug development. AAPS J. 2009;11:262–76.CrossRefGoogle Scholar
  13. 13.
    Riccardi K, Cawley S, Yates PD, Chang C, Funk C, Niosi M, et al. Plasma protein binding of challenging compounds. J Pharm Sci. 2015;104:2627–36.CrossRefGoogle Scholar
  14. 14.
    Shibata Y, Takahashi H, Ishii Y. A convenient in vitro screening method for predicting in vivo drug metabolic clearance using isolated hepatocytes suspended in serum. Drug Metab Dispos. 2000;28:1518–23.PubMedGoogle Scholar
  15. 15.
    Shibata Y, Takahashi H, Chiba M, Ishii Y. Prediction of hepatic clearance and availability by cryopreserved human hepatocytes: an application of serum incubation method. Drug Metab Dispos. 2002;30:892–6.CrossRefGoogle Scholar
  16. 16.
    Shibata Y, Kuze J, Chiba M. Utility of cryopreserved hepatocytes suspended in serum to predict hepatic clearance in dogs and monkeys. Drug Metab Pharmacokinet. 2014;29:168–76.CrossRefGoogle Scholar
  17. 17.
    Naritomi Y, Terashita S, Kimura S, Suzuki A, Kagayama A, Sugiyama Y. 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;29:1316–24.PubMedGoogle Scholar
  18. 18.
    Naritomi Y, Terashita S, Kagayama A, Sugiyama Y. Utility of hepatocytes in predicting drug metabolism: comparison of hepatic intrinsic clearance in rats and humans in vivo and in vitro. Drug Metab Dispos. 2003;31:580–8.CrossRefGoogle Scholar
  19. 19.
    Fisher MB, Campanale K, Ackermann BL, VandenBranden M, Wrighton SA. In vitro glucuronidation using human liver microsomes and the pore-forming peptide alamethicin. Drug Metab Dispos. 2000;28:560–6.PubMedGoogle Scholar
  20. 20.
    Kilford PJ, Stringer R, Sohal B, Houston JB, Galetin A. Prediction of drug clearance by glucuronidation from in vitro data: use of combined cytochrome P450 and UDP-glucuronosyltransferase cofactors in alamethicin-activated human liver microsomes. Drug Metab Dispos. 2009;37:82–9.CrossRefGoogle Scholar
  21. 21.
    Zhang Y, Yao L, Lin J, Gao H, Wilson TC, Giragossian C. Lack of appreciable species differences in nonspecific microsomal binding. J Pharm Sci. 2010;99:3620–7.CrossRefGoogle Scholar
  22. 22.
    Langmuir I. The adsorption of gases on plane surfaces of glass, mica and platinum. J Am Chem Soc. 1918;40:1361–403.CrossRefGoogle Scholar
  23. 23.
    Hosea NA, Collard WT, Cole S, Maurer TS, Fang RX, Jones H, et al. Prediction of human pharmacokinetics from preclinical information: comparative accuracy of quantitative prediction approaches. J Clin Pharmacol. 2009;49:513–33.CrossRefGoogle Scholar
  24. 24.
    Houston JB, Galetin A. Methods for predicting in vivo pharmacokinetics using data from in vitro assays. Curr Drug Metab. 2008;9:940–51.CrossRefGoogle Scholar
  25. 25.
    Roberts MS, Rowland M. Correlation between in-vitro microsomal enzyme activity and whole organ hepatic elimination kinetics; analysis with a dispersion model. J Pharm Pharmacol. 1986;38:177–81.CrossRefGoogle Scholar
  26. 26.
    Obach RS, Baxter JG, Liston TE, Silber BM, Jones BC, MacIntyre F, et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther. 1997;283:46–58.PubMedGoogle Scholar
  27. 27.
    Wood FL, Houston JB, Hallifax D. Clearance prediction methodology needs fundamental improvement: trends common to rat and human hepatocytes/microsomes and implications for experimental methodology. Drug Metab Dispos. 2017;45:1178–88.CrossRefGoogle Scholar
  28. 28.
    Kiang TK, Ensom MH, Chang TK. UDP-glucuronosyltransferases and clinical drug-drug interactions. Pharmacol Ther. 2005;106:97–132.CrossRefGoogle Scholar
  29. 29.
    Gill KL, Houston JB, Galetin A. Characterization of in vitro glucuronidation clearance of a range of drugs in human kidney microsomes: comparison with liver and intestinal glucuronidation and impact of albumin. Drug Metab Dispos. 2012;40:825–35.CrossRefGoogle Scholar
  30. 30.
    King C, Tang W, Ngui J, Tephly T, Braun M. Characterization of rat and human UDP-glucuronosyltransferases responsible for the in vitro glucuronidation of diclofenac. Toxicol Sci. 2001;61:49–53.CrossRefGoogle Scholar
  31. 31.
    Mano Y, Usui T, Kamimura H. The UDP-glucuronosyltransferase 2B7 isozyme is responsible for gemfibrozil glucuronidation in the human liver. Drug Metab Dispos. 2007;35:2040–4.CrossRefGoogle Scholar
  32. 32.
    Yamada A, Maeda K, Ishiguro N, Tsuda Y, Igarashi T, Ebner T, et al. The impact of pharmacogenetics of metabolic enzymes and transporters on the pharmacokinetics of telmisartan in healthy volunteers. Pharmacogenet Genomics. 2011;21:523–30.CrossRefGoogle Scholar
  33. 33.
    Overby LH, Carver GC, Philpot RM. Quantitation and kinetic properties of hepatic microsomal and recombinant flavin-containing monooxygenases 3 and 5 from humans. Chem Biol Interact. 1997;106:29–45.CrossRefGoogle Scholar
  34. 34.
    Tugnait M, Hawes EM, McKay G, Rettie AE, Haining RL, Midha KK. N-oxygenation of clozapine by flavin-containing monooxygenase. Drug Metab Dispos. 1997;25:524–7.PubMedGoogle Scholar
  35. 35.
    Williams JA, Hyland R, Jones BC, Smith DA, Hurst S, Goosen TC, et al. Drug-drug interactions for UDP-glucuronosyltransferase substrates: a pharmacokinetic explanation for typically observed low exposure (AUCi/AUC) ratios. Drug Metab Dispos. 2004;32:1201–8.CrossRefGoogle Scholar
  36. 36.
    Fukami T, Yokoi T. The emerging role of human esterases. Drug Metab Pharmacokinet. 2012;27:466–77.CrossRefGoogle Scholar
  37. 37.
    Franssen EJF, Greuter HNJM, Touw DJ, Luurtsema G, Windhorst AD, Lammertsma AA. Plasma pharmacokinetics of [11C]-flumazenil and its major metabolite [11C]-flumazenil ‘acid’. Br J Clin Pharmacol. 2002;53:554Pb.CrossRefGoogle Scholar
  38. 38.
    Lukkari E, Taavitsainen P, Juhakoski A, Pelkonen O. Cytochrome P450 specificity of metabolism and interactions of oxybutynin in human liver microsomes. Pharmacol Toxicol. 1998;82:161–6.CrossRefGoogle Scholar
  39. 39.
    Sato Y, Miyashita A, Iwatsubo T, Usui T. Conclusive identification of the oxybutynin-hydrolyzing enzyme in human liver. Drug Metab Dispos. 2012;40:902–6.CrossRefGoogle Scholar
  40. 40.
    Noetzli M, Eap CB. Pharmacodynamic, pharmacokinetic and pharmacogenetic aspects of drugs used in the treatment of Alzheimer’s disease. Clin Pharmacokinet. 2013;52:225–41.CrossRefGoogle Scholar
  41. 41.
    Satoh T, Hosokawa M. The mammalian carboxylesterases: from molecules to functions. Annu Rev Pharmacol Toxicol. 1998;38:257–88.CrossRefGoogle Scholar
  42. 42.
    Maser E. Xenobiotic carbonyl reduction and physiological steroid oxidoreduction. The pluripotency of several hydroxysteroid dehydrogenases. Biochem Pharmacol. 1995;49:421–40.CrossRefGoogle Scholar
  43. 43.
    Oppermann UC, Maser E. Molecular and structural aspects of xenobiotic carbonyl metabolizing enzymes. Role of reductases and dehydrogenases in xenobiotic phase I reactions. Toxicology. 2000;144:71–81.CrossRefGoogle Scholar
  44. 44.
    Parkinson A. An overview of current cytochrome P450 technology for assessing the safety and efficacy of new materials. Toxicol Pathol. 1996;24:48–57.CrossRefGoogle Scholar
  45. 45.
    Rosemond MJ, Walsh JS. Human carbonyl reduction pathways and a strategy for their study in vitro. Drug Metab Rev. 2004;36:335–61.CrossRefGoogle Scholar
  46. 46.
    Kudo S, Ishizaki T. Pharmacokinetics of haloperidol: an update. Clin Pharmacokinet. 1999;37:435–56.CrossRefGoogle Scholar
  47. 47.
    Dawson M, Braithwaite PA, Roberts MS, Watson TR. The pharmacokinetics and bioavailability of a tracer dose of [3H]-mebendazole in man. Br J Clin Pharmacol. 1985;19:79–86.CrossRefGoogle Scholar
  48. 48.
    Nishimuta H, Nakagawa T, Nomura N, Yabuki M. Significance of reductive metabolism in human intestine and quantitative prediction of intestinal first-pass metabolism by cytosolic reductive enzymes. Drug Metab Dispos. 2013;41:1104–11.CrossRefGoogle Scholar
  49. 49.
    Persson B, Heykants J, Hedner T. Clinical pharmacokinetics of ketanserin. Clin Pharmacokinet. 1991;20:263–79.CrossRefGoogle Scholar
  50. 50.
    Mazur CS, Kenneke JF, Goldsmith MR, Brown C. Contrasting influence of NADPH and a NADPH-regenerating system on the metabolism of carbonyl-containing compounds in hepatic microsomes. Drug Metab Dispos. 2009;37:1801–5.CrossRefGoogle Scholar
  51. 51.
    Pryde DC, Dalvie D, Hu Q, Jones P, Obach RS, Tran TD. Aldehyde oxidase: an enzyme of emerging importance in drug discovery. J Med Chem. 2010;53:8441–60.CrossRefGoogle Scholar
  52. 52.
    Jones JP, Korzekwa KR. Predicting intrinsic clearance for drugs and drug candidates metabolized by aldehyde oxidase. Mol Pharm. 2013;10:1262–8.CrossRefGoogle Scholar
  53. 53.
    Beedham C, Miceli JJ, Obach RS. Ziprasidone metabolism, aldehyde oxidase, and clinical implications. J Clin Psychopharmacol. 2003;23:229–32.PubMedGoogle Scholar
  54. 54.
    Miao Z, Kamel A, Prakash C. Characterization of a novel metabolite intermediate of ziprasidone in hepatic cytosolic fractions of rat, dog, and human by ESI-MS/MS, hydrogen/deuterium exchange, and chemical derivatization. Drug Metab Dispos. 2005;33:879–83.CrossRefGoogle Scholar
  55. 55.
    Lake BG, Ball SE, Kao J, Renwick AB, Price RJ, Scatina JA. Metabolism of zaleplon by human liver: evidence for involvement of aldehyde oxidase. Xenobiotica. 2002;32:835–47.CrossRefGoogle Scholar
  56. 56.
    Zientek M, Jiang Y, Youdim K, Obach RS. In vitro-in vivo correlation for intrinsic clearance for drugs metabolized by human aldehyde oxidase. Drug Metab Dispos. 2010;38:1322–7.CrossRefGoogle Scholar
  57. 57.
    Akabane T, Gerst N, Masters JN, Tamura K. A quantitative approach to hepatic clearance prediction of metabolism by aldehyde oxidase using custom pooled hepatocytes. Xenobiotica. 2012;42:863–71.CrossRefGoogle Scholar
  58. 58.
    Uchimura T, Kato M, Saito T, Kinoshita H. Prediction of human blood-to-plasma drug concentration ratio. Biopharm Drug Dispos. 2010;31:286–97.PubMedGoogle Scholar
  59. 59.
    Watanabe T, Kusuhara H, Maeda K, Kanamaru H, Saito Y, Hu Z, et al. Investigation of the rate-determining process in the hepatic elimination of HMG-CoA reductase inhibitors in rats and humans. Drug Metab Dispos. 2010;38:215–22.CrossRefGoogle Scholar
  60. 60.
    Izumi S, Nozaki Y, Komori T, Takenaka O, Maeda K, Kusuhara H, et al. Comparison of the predictability of human hepatic clearance for organic anion transporting polypeptide substrate drugs between different in vitro-in vivo extrapolation approaches. J Pharm Sci. 2017;106:2678–87.CrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  • Haruka Nishimuta
    • 1
    Email author
  • Takao Watanabe
    • 1
  • Kiyoko Bando
    • 1
  1. 1.Preclinical Research UnitSumitomo Dainippon Pharma Co., Ltd.OsakaJapan

Personalised recommendations