Skip to main content

Advertisement

Log in

A Semi-Physiologically Based Pharmacokinetic Model Describing the Altered Metabolism of Midazolam Due to Inflammation in Mice

  • Research Paper
  • Published:
Pharmaceutical Research Aims and scope Submit manuscript

A Correction to this article was published on 25 July 2018

This article has been updated

Abstract

Purpose

To investigate influence of inflammation on metabolism and pharmacokinetics (PK) of midazolam (MDZ) and construct a semi-physiologically based pharmacokinetic (PBPK) model to predict PK in mice with inflammatory disease.

Methods

Glucose-6-phosphate isomerase (GPI)-mediated inflammation was used as a preclinical model of arthritis in DBA/1 mice. CYP3A substrate MDZ was selected to study changes in metabolism and PK during the inflammation. The semi-PBPK model was constructed using mouse physiological parameters, liver microsome metabolism, and healthy animal PK data. In addition, serum cytokine, and liver-CYP (cytochrome P450 enzymes) mRNA levels were examined.

Results

The in vitro metabolite formation rate was suppressed in liver microsomes prepared from the GPI-treated mice as compared to the healthy mice. Further, clearance of MDZ was reduced during inflammation as compared to the healthy group. Finally, the semi-PBPK model was used to predict PK of MDZ after GPI-mediated inflammation. IL-6 and TNF-α levels were elevated and liver-cyp3a11 mRNA was reduced after GPI treatment.

Conclusion

The semi-PBPK model successfully predicted PK parameters of MDZ in the disease state. The model may be applied to predict PK of other drugs under disease conditions using healthy animal PK and liver microsomal data as inputs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Change history

  • 25 July 2018

    One of the authors has his name incorrectly indexed in PubMed and SpringerLink as “Laird Forrest M” (last name “Laird Forrest”). His name should index as “Forrest M. Laird” with last name as “Forrest”.

Abbreviations

CAR:

Constitutive androstane receptor

CYP:

Cytochrome P450

DBS:

Dried blood spot

GPI:

Glucose-6-phosphate isomerase

HNF-4α:

Hepatic nuclear factor-4α

HLM:

Human liver microsomes

IV:

Intravenous

LC-MS:

Liquid Chromatography-Mass Spectrometry

MDZ:

Midazolam

MLM:

Mouse liver microsomes

NCA:

Non-compartmental analysis

NCE:

New chemical entity

PBPK:

Physiologically based pharmacokinetic

PK:

Pharmacokinetics

PO:

Oral

PXR:

Pregnane X receptor

qPCR:

Quantitative polymerase chain reaction

SCID:

Severe combined immune deficient

References

  1. Morgan E. Impact of infectious and inflammatory disease on cytochrome P450–mediated drug metabolism and pharmacokinetics. Clin Pharmacol Ther. 2009;85(4):434–8.

    Article  CAS  Google Scholar 

  2. Frye RF, Schneider VM, Frye CS, Feldman AM. Plasma levels of TNF-α and IL-6 are inversely related to cytochrome P450-dependent drug metabolism in patients with congestive heart failure. J Card Fail. 2002;8(5):315–9.

    Article  CAS  Google Scholar 

  3. Coutant D, Kulanthaivel P, Turner P, Bell R, Baldwin J, Wijayawardana S, et al. Understanding disease–drug interactions in Cancer patients: implications for dosing within the therapeutic window. Clin Pharmacol Ther. 2015;98(1):76–86.

    Article  CAS  Google Scholar 

  4. Robertson G, Liddle C, Clarke S. Inflammation and altered drug clearance in Cancer: transcriptional repression of a human CYP3A4 transgene in tumor-bearing mice. Clin Pharmacol Ther. 2008;83(6):894–7.

    Article  CAS  Google Scholar 

  5. Aitken AE, Morgan ET. Gene-specific effects of inflammatory cytokines on cytochrome P450 2C, 2B6 and 3A4 mRNA levels in human hepatocytes. Drug Metab Disposition. 2007;35(9):1687–93.

    Article  CAS  Google Scholar 

  6. Xu Y, Hijazi Y, Wolf A, Wu B, Sun YN, Zhu M. Physiologically based pharmacokinetic model to assess the influence of Blinatumomab-mediated cytokine elevations on cytochrome P450 enzyme activity. CPT: pharmacometrics & systems pharmacology. 2015;4(9):507–15.

    CAS  Google Scholar 

  7. Martignoni M, Groothuis GM, de Kanter R. Species differences between mouse, rat, dog, monkey and human CYP-mediated drug metabolism, inhibition and induction. Expert Opin Drug Metab Toxicol. 2006;2(6):875–94.

    Article  CAS  Google Scholar 

  8. Matsumoto I, Zhang H, Yasukochi T, Iwanami K, Tanaka Y, Inoue A, et al. Therapeutic effects of antibodies to tumor necrosis factor-alpha, interleukin-6 and cytotoxic T-lymphocyte antigen 4 immunoglobulin in mice with glucose-6-phosphate isomerase induced arthritis. Arthritis Res Ther. 2008;10(3):R66.

    Article  Google Scholar 

  9. Palmqvist N, Siller M, Klint C, Sjödin A. A human and animal model-based approach to investigating the anti-inflammatory profile and potential of the 5-HT 2B receptor antagonist AM1030. J Inflamm. 2016;13(1):20.

    Article  Google Scholar 

  10. Gandhi A, Guo T, Shah P, Moorthy B, Chow DL, Hu M, et al. CYP3A-dependent drug metabolism is reduced in bacterial inflammation in mice. Br J Pharmacol. 2012;166(7):2176–87.

    Article  CAS  Google Scholar 

  11. Kato R, Yamashita S, Moriguchi J, Nakagawa M, Tsukura Y, Uchida K, et al. Changes of midazolam pharmacokinetics in Wistar rats treated with lipopolysaccharide: relationship between total CYP and CYP3A2. Innate Immun. 2008;14(5):291–7.

    Article  CAS  Google Scholar 

  12. Kajikawa N, Doi M, Kusaba J-i, Aiba T. Effect of carrageenan-induced acute peripheral inflammation on the pharmacokinetics and hepatic metabolism of midazolam in rats. Drug Metab Pharmacokinet. 2014;29(5):400–6.

    Article  Google Scholar 

  13. Perloff MD, von Moltke LL, Cotreau MM, Greenblatt DJ. Unchanged cytochrome P450 3A (CYP3A) expression and metabolism of midazolam, triazolam, and dexamethasone in mdr (−/−) mouse liver microsomes. Biochem Pharmacol. 1999;57(11):1227–32.

    Article  CAS  Google Scholar 

  14. Samuelsson K, Pickup K, Sarda S, Swales JG, Morikawa Y, Schulz-Utermoehl T, et al. Pharmacokinetics and metabolism of midazolam in chimeric mice with humanised livers. Xenobiotica. 2012;42(11):1128–37.

    Article  CAS  Google Scholar 

  15. Patki KC, von Moltke LL, Greenblatt DJ. In vitro metabolism of midazolam, triazolam, nifedipine, and testosterone by human liver microsomes and recombinant cytochromes p450: role of cyp3a4 and cyp3a5. Drug Metab Disposition. 2003;31(7):938–44.

    Article  CAS  Google Scholar 

  16. Bockermann R, Schubert D, Kamradt T, Holmdahl R. Induction of a B-cell-dependent chronic arthritis with glucose-6-phosphate isomerase. Arthrit Res Ther. 2005;7(6):R1316–R24.

    Article  CAS  Google Scholar 

  17. Kamath S, Kummerow F, Narayan KA. A simple procedure for the isolation of rat liver microsomes. FEBS Lett. 1971;17(1):90–2.

    Article  CAS  Google Scholar 

  18. Elovaara E, Mikkola J, Luukkanen L, Antonio L, Fournel-Gigleux S, Burchell B, et al. Assessment of catechol induction and glucuronidation in rat liver microsomes. Drug Metab Disposition. 2004;32(12):1426–33.

    Article  CAS  Google Scholar 

  19. Smith PK, Krohn RI, Hermanson G, Mallia A, Gartner F, Provenzano M, et al. Measurement of protein using bicinchoninic acid. Anal Biochem. 1985;150(1):76–85.

    Article  CAS  Google Scholar 

  20. Granvil CP, Yu A-M, Elizondo G, Akiyama TE, Cheung C, Feigenbaum L, et al. Expression of the human CYP3A4 gene in the small intestine of transgenic mice: in vitro metabolism and pharmacokinetics of midazolam. Drug Metab Disposition. 2003;31(5):548–58.

    Article  CAS  Google Scholar 

  21. Kuze J, Mutoh T, Takenaka T, Morisaki K, Nakura H, Hanioka N, et al. Separate evaluation of intestinal and hepatic metabolism of three benzodiazepines in rats with cannulated portal and jugular veins: comparison with the profile in non-cannulated mice. Xenobiotica. 2009;39(11):871–80.

    Article  CAS  Google Scholar 

  22. Zhang W, Han F, Guo P, Zhao H, Lin ZJ, Huang M-Q, et al. Simultaneous determination of tolbutamide, omeprazole, midazolam and dextromethorphan in human plasma by LC–MS/MS—A high throughput approach to evaluate drug–drug interactions. J Chromatogr B. 2010;878(15):1169–77.

    Article  CAS  Google Scholar 

  23. Davies B, Morris T. Physiological parameters in laboratory animals and humans. Pharm Res. 1993;10(7):1093–5.

    Article  CAS  Google Scholar 

  24. Brown RP, Delp MD, Lindstedt SL, Rhomberg LR, Beliles RP. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol Ind Health. 1997;13(4):407–84.

    Article  CAS  Google Scholar 

  25. Kirman C, Hays S, Aylward L, Suh M, Harris M, Thompson C, et al. Physiologically based pharmacokinetic model for rats and mice orally exposed to chromium. Chem Biol Interact. 2012;200(1):45–64.

    Article  CAS  Google Scholar 

  26. Masyuk TV, Ritman EL, LaRusso NF. Hepatic artery and portal vein remodeling in rat liver: vascular response to selective cholangiocyte proliferation. Am J Pathol. 2003;162(4):1175–82.

    Article  Google Scholar 

  27. Kuze J, Mutoh T, Takenaka T, Oda N, Hanioka N, Narimatsu S. Evaluation of animal models for intestinal first-pass metabolism of drug candidates to be metabolized by CYP3A enzymes via in vivo and in vitro oxidation of midazolam and triazolam. Xenobiotica. 2013;43(7):598–606.

    Article  CAS  Google Scholar 

  28. Barter ZE, Bayliss MK, Beaune PH, Boobis AR, Carlile DJ, Edwards RJ, et al. Scaling factors for the extrapolation of in vivo metabolic drug clearance from in vitro data: reaching a consensus on values of human micro-somal protein and hepatocellularity per gram of liver. Curr Drug Metab. 2007;8(1):33–45.

    Article  CAS  Google Scholar 

  29. Cubitt HE, Houston JB, Galetin A. Prediction of human drug clearance by multiple metabolic pathways: integration of hepatic and intestinal microsomal and cytosolic data. Drug Metab Disposition. 2011;39(5):864–73.

    Article  CAS  Google Scholar 

  30. Zhang X, Quinney SK, Gorski JC, Jones DR, Hall SD. Semiphysiologically based pharmacokinetic models for the inhibition of midazolam clearance by diltiazem and its major metabolite. Drug Metab Disposition. 2009;37(8):1587–97.

    Article  CAS  Google Scholar 

  31. Yang J, Jamei M, Yeo KR, Tucker GT, Rostami-Hodjegan A. Prediction of intestinal first-pass drug metabolism. Curr Drug Metab. 2007;8(7):676–84.

    Article  CAS  Google Scholar 

  32. Cleton A, Mazee D, Voskuyl R, Danhof M. Rate of change of blood concentrations is a major determinant of the pharmacodynamics of midazolam in rats. Br J Pharmacol. 1999;127(1):227–35.

    Article  CAS  Google Scholar 

  33. Wang J, Xia S, Xue W, Wang D, Sai Y, Liu L, et al. A semi-physiologically-based pharmacokinetic model characterizing mechanism-based auto-inhibition to predict stereoselective pharmacokinetics of verapamil and its metabolite norverapamil in human. Eur J Pharm Sci. 2013;50(3):290–302.

    Article  CAS  Google Scholar 

  34. Chowdhury F, Williams A, Johnson P. Validation and comparison of two multiplex technologies, Luminex® and mesoscale discovery, for human cytokine profiling. J Immunol Methods. 2009;340(1):55–64.

    Article  CAS  Google Scholar 

  35. Lu J, Goldsmith M-R, Grulke CM, Chang DT, Brooks RD, Leonard JA, et al. Developing a physiologically-based pharmacokinetic model knowledgebase in support of provisional model construction. PLoS Comput Biol. 2016;12(2):e1004495.

    Article  Google Scholar 

  36. Czerwiński M, Kazmi F, Parkinson A, Buckley DB. Anti-CD28 monoclonal antibody-stimulated cytokines released from blood suppress CYP1A2, CYP2B6 and CYP3A4 in human hepatocytes in vitro. Drug Metab Disposition. 2015;43(1):42–52.

    Article  Google Scholar 

  37. Dickmann LJ, Patel SK, Rock DA, Wienkers LC, Slatter JG. Effects of interleukin-6 (IL-6) and an anti-IL-6 monoclonal antibody on drug-metabolizing enzymes in human hepatocyte culture. Drug Metab Disposition. 2011;39(8):1415–22.

    Article  CAS  Google Scholar 

  38. Machavaram K, Almond L, Rostami-Hodjegan A, Gardner I, Jamei M, Tay S, et al. A physiologically based pharmacokinetic modeling approach to predict disease–drug interactions: suppression of CYP3A by IL-6. Clin Pharmacol Ther. 2013;94(2):260–8.

    Article  CAS  Google Scholar 

  39. Charles P, Elliott MJ, Davis D, Potter A, Kalden JR, Antoni C, et al. Regulation of cytokines, cytokine inhibitors, and acute-phase proteins following anti-TNF-α therapy in rheumatoid arthritis. J Immunol. 1999;163(3):1521–8.

    CAS  PubMed  Google Scholar 

  40. Lee J-I, Zhang L, Men AY, Kenna LA, Huang S-M. CYP-mediated therapeutic protein-drug interactions. Clin Pharmacokinet. 2010;49(5):295–310.

    Article  CAS  Google Scholar 

  41. De Vries J, Rudi J, Walter-Sack I, Conradi R. The determination of total and unbound midazolam in human plasma. A comparison of high performance liquid chromatography, gas chromatography and gas chromatography/mass spectrometry. Biomed Chromatogr. 1990;4(1):28–33.

    Article  Google Scholar 

  42. Reed MD, Myers CM, Blumer JL. Influence of midazolam on the protein binding of ketorolac. Curr Ther Res. 2001;62(8):558–65.

    Article  CAS  Google Scholar 

  43. Higai K, Azuma Y, Aoki Y, Matsumoto K. Altered glycosylation of α 1-acid glycoprotein in patients with inflammation and diabetes mellitus. Clin Chim Acta. 2003;329(1):117–25.

    Article  CAS  Google Scholar 

  44. Piafsky KM, Borgå O, Odar-Cederlöf I, Johansson C, Sjöqvist F. Increased plasma protein binding of propranolol and chlorpromazine mediated by disease-induced elevations of plasma α1 acid glycoprotein. N Engl J Med. 1978;299(26):1435–9.

    Article  CAS  Google Scholar 

  45. Heizmann P, Ziegler W. Excretion and metabolism of 14C-midazolam in humans following oral dosing. Arzneimittelforschung. 1981;31(12a):2220–3.

    CAS  PubMed  Google Scholar 

  46. Woo GK, Williams T, Kolis S, Warinsky D, Sasso G, Schwartz M. Biotransformation of [14C] midazolam in the rat in vitro and in vivo. Xenobiotica. 1981;11(6):373–84.

    Article  CAS  Google Scholar 

  47. Thummel KE, O'shea D, Paine MF, Shen DD, Kunze KL, Perkins JD, et al. Oral first-pass elimination of midazolam involves both gastrointestinal and hepatic CYP3A-mediated metabolism. Clin Pharmacol Ther. 1996;59(5):491–502.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors acknowledge Michael Mohutsky for help with the in vitro metabolism work, Tom Kern (Covance Inc.) for conducting in vivo pharmacokinetic experiments, George Searfoss for CYP mRNA measurements, Bridget Morse for suggestions regarding the semi-PBPK model, and Daniel Mudra for critically reading the manuscript and providing suggestions. Eli Lilly provided support for an internship by NV and funded laboratory and animal studies. NV and MLF were partially supported by a grant from NIH (R01CA173292, PI: Forrest) during analysis and development of the model. NV was partially supported by a Higuchi Fellowship and the Department of Pharmaceutical Chemistry, The University of Kansas.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Laird Forrest.

Ethics declarations

Conflict of Interest

None to declare.

Electronic supplementary material

ESM 1

(DOCX 2719 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Varkhede, N., Patel, N., Chang, W. et al. A Semi-Physiologically Based Pharmacokinetic Model Describing the Altered Metabolism of Midazolam Due to Inflammation in Mice. Pharm Res 35, 162 (2018). https://doi.org/10.1007/s11095-018-2447-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11095-018-2447-9

Key words

Navigation