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The AAPS Journal

, 21:103 | Cite as

How Transporters Have Changed Basic Pharmacokinetic Understanding

  • Leslie Z. BenetEmail author
  • Christine M. Bowman
  • Jasleen K. Sodhi
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Abstract

The emergence and continued evolution of the transporter field has caused re-evaluation and refinement of the original principles surrounding drug disposition. In this paper, we emphasize the impact that transporters can have on volume of distribution and how this can affect the other major pharmacokinetic parameters. When metabolic drug–drug interactions or pharmacogenomic variance changes the metabolism of a drug, the volume of distribution appears to be unchanged while clearance, bioavailability, and half-life are changed. When transporters are involved in the drug–drug interactions or pharmacogenomic variance, the volume of distribution can be markedly affected causing counterintuitive changes in half-life. Cases are examined where a volume of distribution change is significant enough that although clearance decreases, half-life decreases. Thus, drug dosing decisions must be made based on CL/F changes, not half-life changes, as such volume of distribution alterations will also influence the half-life results.

Key Words

clearance half-life mean residence time transporters volume of distribution 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest to disclose.

References

  1. 1.
    Benet LZ. Pharmacokinetics: basic principles and its use as a tool in drug metabolism. In: Mitchell JR, Horning MG, editors. Drug metabolism and drug toxicity. New York: Raven Press; 1984. p. 199–211.Google Scholar
  2. 2.
    Benet LZ, Sheiner LB. Introduction: pharmacokinetics: the dynamics of drug absorption, distribution, and elimination. In: Gilman AG, Goodman LS, Rall TW, Murad F, editors. The pharmacological basis of therapeutics. 7th ed. New York: Macmillan Publishing Company; 1985. Chapter 1. p. 1–34.Google Scholar
  3. 3.
    Benet LZ. Introductory lecture, “Pharmacokinetics for pharmaceutical scientists”, UCSF one week course first taught February 1986 and continuously each year since.Google Scholar
  4. 4.
    Benet LZ, Galeazzi RL. Noncompartmental determination of the volume of distribution steady-state. J Pharm Sci. 1979;68:1071–4.CrossRefPubMedGoogle Scholar
  5. 5.
    Sobol E, Bialer M. The relationships between half-life (t1/2) and mean residence time (MRT) in the two-compartment open body model. Biopharm Drug Dispos. 2004;25:157–62.CrossRefPubMedGoogle Scholar
  6. 6.
    Mager DE, Jusko WJ. General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J Pharmacokinet Pharmacodyn. 2001;28:507–32.CrossRefPubMedGoogle Scholar
  7. 7.
    Benet LZ, Bowman CM, Koleske ML, Rinaldi CL, Sodhi JK. Understanding drug–drug interaction and pharmacogenomic changes in pharmacokinetics for metabolized drugs. J Pharmacokinet Pharmacodyn. 2019;46:155–63.CrossRefPubMedGoogle Scholar
  8. 8.
    Klotz U, Avant GR, Hoyumpa A, Schenker S, Wilkinson GR. The effects of age and liver disease on the disposition and elimination of diazepam in adult man. J Clin Invest. 1975;55:347–59.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Benet LZ, Bowman CM, Liu S, Sodhi JK. The extended clearance concept following oral and intravenous dosing: theory and critical analyses. Pharm Res. 2018;35:242.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Lau YY, Huang Y, Frassetto L, Benet LZ. Effect of OATP1B transporter inhibition on the pharmacokinetics of atorvastatin in healthy volunteers. Clin Pharmacol Ther. 2007;81:194–204.CrossRefPubMedGoogle Scholar
  11. 11.
    Zheng HX, Huang Y, Frassetto LA, Benet LZ. Elucidating rifampin’s inducing and inhibiting effects on glyburide pharmacokinetics and blood glucose in healthy volunteers: unmasking the differential effects of enzyme induction and transporter inhibition for a drug and its primary metabolite. Clin Pharmacol Ther. 2009;85:78–85.CrossRefPubMedGoogle Scholar
  12. 12.
    Wu H-F, Hristeva N, Chang J, Liang X, Li R, Frassetto L, et al. Rosuvastatin pharmacokinetics in Asian and white subjects wild type for both OATP1B1 and BCRP under control and inhibited conditions. J Pharm Sci. 2017;106:2751–7.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Grover A, Benet LZ. Effects of drug transporters on volume of distribution. AAPS J. 2009;11:250–61.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Gorski JC, Jones DR, Haehner-Daniels BD, Hamman MA, O’Mara EM, Hall SD. The contribution of intestinal and hepatic CYP3A to the interaction between midazolam and clarithromycin. Clin Pharmacol Ther. 1998;64:133–43.CrossRefPubMedGoogle Scholar
  15. 15.
    Jelliffe R, Bayard D. New perspectives in clinical pharmacokinetics-1: the importance of updating the teaching in pharmacokinetics that both clearance and elimination rate constant approaches are mathematically proven equally valid. AAPS J. 2018;20:36.CrossRefPubMedGoogle Scholar
  16. 16.
    Sahin S, Benet LZ. The operational multiple dosing half-life: a key to defining drug accumulation in patients and to designing extended release dosage forms. Pharm Res. 2008;25:2869–77.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Sirianni GL, Pang KS. Organ clearance concepts: new perspectives on old principles. J Pharmacokinet Biopharm. 1997;25:449–70.CrossRefPubMedGoogle Scholar
  18. 18.
    Webborn PJH, Parker AJ, Denton RL, Riley RJ. In vitro-in vivo extrapolation of hepatic clearance involving active uptake: theoretical and experimental aspects. Xenobiotica. 2007;37:1090–109.PubMedGoogle Scholar
  19. 19.
    Camenisch G, Umehara K. Predicting human hepatic clearance from in vitro drug metabolism and transport data: a scientific and pharmaceutical perspective for assessing drug-drug interactions. Biopharm Drug Dispos. 2012;33:179–94.CrossRefPubMedGoogle Scholar
  20. 20.
    Barton HA, Lai Y, Goosen TC, Jones HM, El-Kattan AF, Gossed JR, et al. Model-based approaches to predict drug-drug interactions associated with hepatic uptake transporters: preclinical, clinical and beyond. Expert Opin Drug Metab Toxicol. 2013;9:459–72.CrossRefPubMedGoogle Scholar
  21. 21.
    Varma MV, Steyn SJ, Allerton C, El-Kattan AF. Predicting clearance mechanism in drug discovery: extended clearance classification system (ECCS). Pharm Res. 2015;32:3785–802.CrossRefPubMedGoogle Scholar
  22. 22.
    El-Kattan AF, Varma MVS. Navigating transporter sciences in pharmacokinetics characterization using the extended clearance classification system. Drug Metab Dispos. 2018;46:729–39.CrossRefPubMedGoogle Scholar
  23. 23.
    Patilea-Vrana G, Unadkat JD. Transport vs. metabolism: what determines the pharmacokinetics and pharmacodynamics of drugs? Insights from the extended clearance model. Clin Pharmacol Ther. 2016;100:413–8.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Li Z, Di L, Maurer TS. Theoretical considerations for direct translation of unbound liver-to-plasma partition coefficient from in vitro to in vivo. AAPS J. 2019;18(21):43.CrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  1. 1.Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and MedicineUniversity of California San FranciscoSan FranciscoUSA

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