Skip to main content

Advertisement

SpringerLink
Log in

Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model

  • Published:
Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Abstract

Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0–24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte–Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Lugo R.A., MacLaren R., Cash J., Pribble C.G., Vernon D.D., (2001). Enteral to expedite fentanyl discontinuation and prevent opioid abstinence syndrome in the PICU. Pharmacotherapy 21:1566–1573

    Article  PubMed  CAS  Google Scholar 

  2. Tobias J.D., (2000). Tolerance, withdrawal, and physical dependency after long-term sedation and analgesia of children in the pediatric intensive care unit. Crit. Care. Med. 28:2122–2132

    Article  PubMed  CAS  Google Scholar 

  3. Tobias J.D., Schleien C.L., Haun S.E., (1990). Methadone as treatment for iatrogenic narcotic dependency in pediatric intensive care unit patients. Crit. Care. Med. 18:1292–1293

    PubMed  CAS  Google Scholar 

  4. Garrido M.J., Jiminez R., Gomez E., Calvo R., (1996). Influence of plasma-protein on analgesic effect of methadone in rats with spontaneous withdrawal. Pharm J., Pharmacol. 48:281–284

    CAS  Google Scholar 

  5. Abramson F.P., (1982). Methadone plasma protein binding: alterations in cancer and from alpha 1-acid glycoprotein. Clin. Pharmacol. Ther. 32:652–658

    Article  PubMed  CAS  Google Scholar 

  6. de Vos J.W., Geerlings P.J., van den Brink W., Ufkes J.G., van Wilgenburg H. (1995). Pharmacokinetics of methadone and its primary metabolite in 20 opiate addicts. Eur. J. Clin. Pharmacol. 48:361–366

    Article  PubMed  Google Scholar 

  7. Kharasch E.D., Hoffer C., Whittington D., Sheffels P., (2004). Role of hepatic and intestinal cytochrome P450 3A and 2B6 in the metabolism, disposition, and miotic effects of methadone. Clin. Pharmacol. Ther. 76:250–269

    Article  PubMed  CAS  Google Scholar 

  8. Wang J.S., DeVane C.L., (2003). Involvement of CYP3A4, CYP2C8, and CYP2D6 in the metabolism of (R)- and (S)-methadone in vitro. Drug Metab. Dispos. 31:742–747

    Article  PubMed  CAS  Google Scholar 

  9. Wong S.H., Wagner M.A., Jentzen J.M., Schur C., Bjerke J., Gock S.B., Chang C. C., (2003). Pharmacogenomics as an aspect of molecular autopsy for forensic pathology/toxicology: does genotyping CYP 2D6 serve as an adjunct for certifying methadone toxicity?. J. Forensic. Sci. 48:1406–1415

    PubMed  CAS  Google Scholar 

  10. Kristensen K., Blemmer T., Angelo H.R., Christrup L.L., Drenck N.E., Rasmussen S.N., Sjogren P., (1996). Stereoselective pharmacokinetics of methadone in chronic pain patients. Ther. Drug. Monit. 18:221–227

    Article  PubMed  CAS  Google Scholar 

  11. Boulton D.W., Arnaud P., DeVane C.L., (2001). Pharmacokinetics and pharmacodynamics of methadone enantiomers after a single oral dose of racemate. Clin. Pharmacol. Ther. 70:48–57

    Article  PubMed  CAS  Google Scholar 

  12. Wolff K., Hay A.W., Raistrick D., Calvert R., (1993). Steady-state pharmacokinetics of methadone in opioid addicts. Eur. J. Clin. Pharmacol. 44:189–194

    Article  PubMed  CAS  Google Scholar 

  13. Anggard E., Gunne L.M., Homstrand J., McMahon R.E., Sandberg C.G., Sullivan H.R., (1975). Disposition of methadone in methadone maintenance. Clin. Pharmacol. Ther. 17:258–266

    PubMed  CAS  Google Scholar 

  14. Inturrisi C.E., Verebely K., (1972). Disposition of methadone in man after a single oral dose. Clin. Pharmacol. Ther. 13:923–930

    PubMed  CAS  Google Scholar 

  15. Robinson A.E., Williams F.M., (1971). The distribution of methadone in man. J. Pharm. Pharmacol. 23:353–358

    PubMed  CAS  Google Scholar 

  16. Iribarne C., Dreano Y., Bardou L.G., Menez J.F., Berthou F., (1997). Interaction of methadone with substrates of human hepatic cytochrome P450 3A4. Toxicology 117:13–23

    Article  PubMed  CAS  Google Scholar 

  17. Lotsch J., Skarke C., Tegeder I., Geisslinger G., (2002). Drug interactions with patient-controlled analgesia. Clin. Pharmacokinet. 41:31–57

    Article  PubMed  CAS  Google Scholar 

  18. Ferrari A., Coccia C.P., Bertolini A., Sternieri E., (2004).Methadone–metabolism, and interactions. Pharmacol. Res. 50:551–559

    Article  PubMed  CAS  Google Scholar 

  19. Bruera E., Sweeney C., (2002). Methadone use in cancer patients with pain: a review. J. Palliat. Med. 5:127–138

    Article  PubMed  Google Scholar 

  20. Rachel H., Robert A., Jason W., Wayne H., and Michael F., Proceedings of the expert workshop on induction and stabilisation of patients onto methadone in Findings of an expert workshop, Adelaide, South Australia. ISBN 0642415080 (2000).

  21. Garrido M.J., Troconiz I.F.,(1999). Methadone: a review of its pharmacokinetic/ properties. J. Pharmacol. Toxicol. Methods 42:61–66

    Article  PubMed  CAS  Google Scholar 

  22. Taj R., Keenan E., O’Connor J.J., (1995). A review of patients on methadone Ir. Med. J. 88:218–219

    PubMed  CAS  Google Scholar 

  23. Gabrielsson J.L., Johansson P., Bondesson U., Paalzow L.K., (1985). Analysis of methadone disposition in the pregnant rat by means of a physiological flow model. J. Pharmacokinet. Biopharm. 13:355–372

    Article  PubMed  CAS  Google Scholar 

  24. Eap C.B., Buclin T., Baumann P., (2002). Interindividual variability of the clinical pharmacokinetics of methadone: implications for the treatment of opioid dependence. Clin. Pharmacokinet. 41:1153–1193

    Article  PubMed  CAS  Google Scholar 

  25. Walsh C.T., Levine R.R., Squires C., (1975). The gastrointestinal absorption of in the rat. Drug Metab. Dispos. 3:525–529

    PubMed  CAS  Google Scholar 

  26. Ito K., Iwatsubo T., Kanamitsu S., Ueda K., Suzuki H., Sugiyama Y., (1998). Prediction of pharmacokinetic alterations caused by drug-drug interactions: metabolic interaction in the liver. Pharmacol. Rev. 50:387–412

    PubMed  CAS  Google Scholar 

  27. Foster D.J., Somogyi A.A., Dyer K.R., White J.M., Bochner F., (2000). Steady-state pharmacokinetics of (R)- and (S)-methadone in methadone maintenance patients. Br. J. Clin. Pharmacol. 50:427–440

    Article  PubMed  CAS  Google Scholar 

  28. Foster D.J., Somogyi A.A., Bochner F., (1999). Methadone N-demethylation in human liver microsomes: lack of stereoselectivity and involvement of CYP3A4. Br. J. Clin. Pharmacol. 47:403–412

    Article  PubMed  CAS  Google Scholar 

  29. Peck D.G., Beckett W., (1976). Methadone maintenance: a review and critique. Br. J. Addict Alcohol Other Drugs 71:369–376

    PubMed  CAS  Google Scholar 

  30. Stevens J.C., Hines R.N., Gu C., Koukouritaki S.B., Manro J.R., Tandler P.J., Zaya M.J., (2003). Developmental expression of the major human hepatic CYP3A enzymes. J. Pharmacol. Exp. Ther. 307:573–582

    Article  PubMed  CAS  Google Scholar 

  31. Kuehl P., Zhang J., Lin Y., Lamba J., Assem M., Schuetz J., Watkins P.B., Daly A., Wrighton S.A., Hall S.D., Maurel P., Relling M., Brimer C., Yasuda K.,Strom R S., Thummel K., Boguski M.S., Schuetz E., (2001). Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat. Genet. 27:383–391

    Article  PubMed  CAS  Google Scholar 

  32. Nilsson M.I., Meresaar U., Anggard E., (1982). Clinical pharmacokinetics of methadone. Acta. Anaesthesiol. Scand. Suppl. 74:66–69

    Article  PubMed  CAS  Google Scholar 

  33. Charnick S.B., Kawai R., Nedelman J.R., Lemaire M., Niederberger W., Sato H., (1995). Perspectives in pharmacokinetics. Physiologically based pharmacokinetic modeling as a tool for drug development. J. Pharmacokinet. Biopharm. 23:217–229

    CAS  Google Scholar 

  34. Rowland M., Balant L., Peck C., Physiologically Based pharmacokinetics in drug development and regulatory science: a workshop report (Georgetown University, Washington, DC, May 29–30, 2002). AAPS PharmSci. 6:E6 (2004).

  35. McNamara P.J., Alcorn J., (2002).Protein binding predictions in infants. AAPS 4:E4

    Google Scholar 

  36. McCarver D.G., Hines R.N., (2002). The ontogeny of human drug-metabolizing enzymes: phase II conjugation enzymes and regulatory mechanisms. J. Pharmacol. Exp. Ther. 300:361–366

    Article  PubMed  CAS  Google Scholar 

  37. Hines R.N., McCarver D.G., (2002). The ontogeny of human drug-metabolizing enzymes: phase I oxidative enzymes. J. Pharmacol. Exp. Ther. 300:355–360

    Article  PubMed  CAS  Google Scholar 

  38. Bjorkman S., (2005). Prediction of drug disposition in infants and children by means of physiologically based pharmacokinetic (PBPK) modelling: theophylline and midazolam as model drugs. Br. J. Clin. Pharmacol. 59:691–704

    Article  PubMed  CAS  Google Scholar 

  39. Ginsberg G., Hattis D., Russ A., Sonawane B., (2004). Physiologically based (PBPK) modeling of caffeine and theophylline in neonates and adults: implications for assessing children’s risks from environmental agents. J. Toxicol. Environ. Health A 67:297–329

    Article  PubMed  CAS  Google Scholar 

  40. Price P.S., Conolly R.B., Chaisson C.F., Gross E.A., Young J.S., Mathis E.T., Tedder D.R., (2003). Modeling interindividual variation in physiological factors used in PBPK models of humans Crit. Rev. Toxicol. 33:469–503

    Article  Google Scholar 

  41. ICRP 2002 Basic anatomical and physiological data for use in radiological protection: reference values ICRP. Publication 89 (ISSN: 0146 6453).

  42. Haddad S., Restieri C., Krishnan K., (2001). Characterization of age-related changes in body weight and organ weights from birth to adolescence in humans. J. Toxicol. Health A 64:453–464

    Article  CAS  Google Scholar 

  43. Boffito M., Sciole K., Raiteri R., Bonora S., Hoggard P.G., Back D.J., Di Perri G. (2002). Alpha 1-acid glycoprotein levels in human immunodeficiency virus-infected subjects on antiretroviral regimens. Drug Metab. Dispos. 30:859–860

    Article  PubMed  CAS  Google Scholar 

  44. Hayton W.L., (2000). Maturation and growth of renal function: dosing renally cleared drugs in children. AAPS PharmSci. 2:E3

    Article  PubMed  CAS  Google Scholar 

  45. Wrighton S.A., Brian W.R., Sari M.A., Iwasaki M., Guengerich F.P., Raucy J.L., Molowa D.T., Vandenbranden M.,(1990). Studies on the expression and metabolic capabilities of human liver cytochrome P450IIIA5 (HLp3). Mol. Pharmacol. 38:207–213

    PubMed  CAS  Google Scholar 

  46. Sung C.Y., Way E.L., (1953). The metabolic fate of the optical isomers of methadone. J. Pharmacol. Exp. Ther. 109:244–254

    PubMed  CAS  Google Scholar 

  47. Levitt D.G., Schnider T.W., (2005). Human physiologically based pharmacokinetic model for propofol. BMC Anesthesiol. 5:4

    Article  PubMed  CAS  Google Scholar 

  48. Farrar D., Allen B., Crump K., Shipp A., (1989). Evaluation of uncertainty in input parameters to pharmacokinetic models and the resulting uncertainty in output. Toxicol. Lett. 49:371–385

    Article  PubMed  CAS  Google Scholar 

  49. Loimer N., Schmid R., (1992). The use of plasma levels to optimize methadone treatment. Drug Alcohol Depen. 30:241–246

    Article  CAS  Google Scholar 

  50. Sprenger K.B., Huber K., Kratz W., Henze E., (1987). Nomograms for the of patient’s plasma volume in plasma exchange therapy from height, weight, and J. Clin. Apher. 3:185–190

    Article  CAS  Google Scholar 

  51. Linderkamp O., Versmold H.T., Riegel K.P., Betke K., (1977). Estimation and of blood volume in infants and children. Eur. J. Pediatr. 125:227–234

    Article  PubMed  CAS  Google Scholar 

  52. Gray D.S., Fujioka K., (1991). Use of relative weight and Body Mass Index for the determination of adiposity. J. Clin. Epidemiol. 44:545–550

    Article  PubMed  CAS  Google Scholar 

  53. Clarys J.P., Martin A.D., Drinkwater D.T., (1984). Gross tissue weights in the human body by cadaver dissection. Hum. Biol. 56:459–473

    PubMed  CAS  Google Scholar 

  54. Ogiu N., Nakamura Y., Ijiri I., Hiraiwa K., Ogiu T., (1997). A statistical analysis of the internal organ weights of normal Japanese people. Health. Phys. 72:368–383

    Article  PubMed  CAS  Google Scholar 

  55. Bailey B.J., Briars G.L., (1996). Estimating the surface area of the human body. Stat. Med. 15:1325–1332

    Article  PubMed  CAS  Google Scholar 

  56. Noda T., Todani T., Watanabe Y., Yamamoto S., (1997). Liver volume in children measured by computed tomography. Pediatr. Radiol. 27:250–252

    Article  PubMed  CAS  Google Scholar 

  57. Watanabe Y., Todani T., Noda T., Yamamoto S., (1997). Standard splenic volume in children and young adults measured from CT images. Surg. Today 27:726–728

    Article  PubMed  CAS  Google Scholar 

  58. Kasiske B.L., Umen A.J., (1986). The influence of age, sex, race, and body habitus on kidney weight in humans. Arch Pathol. Lab. Med. 110:55–60

    PubMed  CAS  Google Scholar 

  59. Dekaban A.S., (1978). Changes in brain weights during the span of human life: relation of brain weights to body heights and body weights. Ann. Neurol. 4:345–356

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physiology, Medical College of Wisconsin, Biotechnology and Bioengineering Center, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA

    Feng Yang & Daniel A. Beard

  2. Department of Computer Science, University of Montana, Missoula, MT, 59812-5256, USA

    Xianping Tong

  3. Departments of Pediatrics and Pharmacology/Toxicology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53326, USA

    D. Gail. McCarver & Ronald N. Hines

Authors
  1. Feng Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xianping Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D. Gail. McCarver
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ronald N. Hines
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Daniel A. Beard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniel A. Beard.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yang, F., Tong, X., McCarver, D.G. et al. Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model. J Pharmacokinet Pharmacodyn 33, 485–518 (2006). https://doi.org/10.1007/s10928-006-9018-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-006-9018-0

Keywords

Search

Navigation