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Kinetic Considerations for the Quantitative Assessment of Efflux Activity and Inhibition: Implications for Understanding and Predicting the Effects of Efflux Inhibition

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Abstract

Purpose

Unexpected and complex experimental observations related to efflux transport have been reported in the literature. This work was conducted to develop relationships for efflux activity (PSefflux) as a function of commonly studied kinetic parameters [permeability-surface area product (PS), efflux ratio (ER), degree of efflux inhibition (ϕi), 50% inhibitory concentration (IC50), and Michaelis–Menten constant (Km)].

Methods

A three-compartment model (apical, cellular, and basolateral) was used to derive flux equations relating the initial rate of flux and steady-state mass transfer in the presence or absence of active efflux. Various definitions of efflux ratio (ER) were examined in terms of permeability-surface area products. The efflux activity (PSefflux) was expressed in terms of ER and PS. The relationships between PSefflux and PS, ER, ϕi, IC50, and Km were solved mathematically. Simulations and examples from the literature were used to illustrate the resulting mathematical relationships.

Results

The relationships derived according to a three-compartment model differed fundamentally from commonly accepted approaches for determining PSefflux, ϕi, IC50 and Km. Based on the model assumptions and mathematical derivations, currently used mathematical relationships erroneously imply that efflux activity is proportional to change in PS (i.e., flux or Papp) and thus underestimate PSefflux and ϕi, and overestimate IC50 and Km.

Conclusions

An understanding of the relationship between efflux inhibition and kinetic parameters is critical for appropriate data interpretation, standardization in calculating and expressing the influence of efflux transport, and predicting the clinical significance of efflux inhibition.

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Abbreviations

ϕi :

degree of efflux inhibition

\({\text{\rm ER}}_{\alpha } \) :

asymmetry efflux ratio (PSB→A/PSA→B) or steady-state (CA/CB)

ERA :

apical efflux ratio (PS0,B→A/PSB→A) or steady-state (CA,0/CA)

ERB :

basolateral efflux ratio (PSI,A→B/PSA→B ) or steady-state (CB,I/CB)

ERC :

cellular efflux ratio (PSI,A→C/PSA→C ) or steady-state (CC,I,/CC)

[I]:

inhibitor concentration

IC50 :

50% inhibitory concentration

Ki :

inhibitor constant

Km :

Michaelis–Menten constant

PS:

observed permeability-surface area product

PS0 :

permeability–surface area product in the absence of efflux inhibition

PSI :

permeability–surface area product when efflux is completely inhibited or saturated; passive permeability-surface area product

[S]:

substrate concentration

A:

apical

B:

basolateral

C:

cellular

app:

apparent

max:

maximum

0:

absence of efflux inhibition

I:

efflux is completely inhibited or saturated

AB:

apical to basolateral; apical compartment dosed

BA:

basolateral to apical; basolateral compartment dosed

AC:

apical to cellular; apical compartment dosed

References

  1. C. J. Matheny, M. W. Lamb, K. L. R. Brouwer, and G. M. Pollack. Pharmacokinetic and pharmacodynamic implications of P-glycoprotein modulation. Pharmacotherapy, 21:778–796 (2001).

    Article  PubMed  CAS  Google Scholar 

  2. C. M. Kruijtzer, J. H. Beijnen, H. Rosing, W. W. ten Bokkel Huinink, M. Schot, R. C. Jewell, E. M. Paul, and J. H. Schellens. Increased oral bioavailability of topotecan in combination with the breast cancer resistance protein and P-glycoprotein inhibitor GF120918. J. Clin. Oncol. 20:2943–2950 (2002).

    Article  PubMed  CAS  Google Scholar 

  3. H. Thomas and H. M. Coley. Overcoming multidrug resistance in cancer: an update on the clinical strategy of inhibiting p-glycoprotein. Cancer Control 10:159–165 (2003).

    PubMed  Google Scholar 

  4. E. M. Kemper, C. Cleypool, W. Boogerd, J. H. Beijnen, and O. van Tellingen. The influence of the P-glycoprotein inhibitor zosuquidar trihydrochloride (LY335979) on the brain penetration of paclitaxel in mice. Cancer Chemother. Pharmacol. 53:173–178 (2004).

    Article  PubMed  CAS  Google Scholar 

  5. R. H. Ho and R. B. Kim. Transporters and drug therapy: implications for drug disposition and disease. Clin. Pharmacol. Ther. 78:260–277 (2005).

    Article  PubMed  CAS  Google Scholar 

  6. J. H. Lin. Drug–drug interaction mediated by inhibition and induction of P-glycoprotein. Adv. Drug Deliv. Rev. 55:53–81 (2003).

    Article  PubMed  CAS  Google Scholar 

  7. A. J. Sadeque, C. Wandel, H. He, S. Shah, and A. J. Wood. Increased drug delivery to the brain by P-glycoprotein inhibition. Clin. Pharmacol. Ther. 68:231–237 (2000).

    Article  PubMed  CAS  Google Scholar 

  8. Y. Adachi, H. Suzuki, and Y. Sugiyama. Comparative studies on in vitro methods for evaluating in vivo function of MDR1 P-glycoprotein. Pharm. Res. 18:1660–1668 (2001).

    Article  PubMed  CAS  Google Scholar 

  9. C. Dagenais, J. Zong, J. Ducharme, and G. M. Pollack. Effect of mdr1a P-glycoprotein gene disruption, gender, and substrate concentration on brain uptake of selected compounds. Pharm. Res. 18:957–963 (2001).

    Article  PubMed  CAS  Google Scholar 

  10. C. Chen, X. Liu, and B. J. Smith. Utility of Mdr1-gene deficient mice in assessing the impact of P-glyco-protein on pharmacokinetics and pharmacodynamics in drug discovery and development. Curr. Drug Metab. 4:272–291 (2003).

    Article  PubMed  CAS  Google Scholar 

  11. M. Yamazaki, W. E. Neway, T. Ohe, I. Chen, J. F. Rowe, J. H. Hochman, M. Chiba, and J. H. Lin. In vitro substrate identification studies for p-glycoprotein-mediated transport: species difference and predictability of in vivo results. J. Pharmacol. Exp. Ther. 296:723–735 (2001).

    PubMed  CAS  Google Scholar 

  12. T. T. Tran, A. Mittal, T. Aldinger, J. W. Polli, A. Ayrton, H. Ellens, and J. Bentz. The elementary mass action rate constants of P-gp transport for a confluent monolayer of MDCKII-hMDR1 cells. Biophys. J. 88:715–738 (2005).

    Article  PubMed  CAS  Google Scholar 

  13. J. Bentz, T. T. Tran, J. W. Polli, A. Ayrton, and H. Ellens. The steady-state Michaelis–Menten analysis of P-glycoprotein mediated transport through a confluent cell monolayer cannot predict the correct Michaelis constant Km. Pharm. Res. 22:1667–1677 (2005).

    Article  PubMed  CAS  Google Scholar 

  14. H. Kwon, R. A. Lionberger, and L. X. Yu. Impact of P-glycoprotein-mediated intestinal efflux kinetics on oral bioavailability of P-glycoprotein substrates. Mol. Pharm. 1:455–465 (2004).

    Article  PubMed  CAS  Google Scholar 

  15. W. Chen, J. Z. Yang, R. Andersen, L. H. Nielsen, and R. T. Borchardt. Evaluation of the permeation characteristics of a model opioid peptide, H-Tyr-D-Ala-Gly-Phe-D-Leu-OH (DADLE), and its cyclic prodrugs across the blood–brain barrier using an in situ perfused rat brain model. J. Pharmacol. Exp. Ther. 303:849–857 (2002).

    Article  PubMed  CAS  Google Scholar 

  16. K. M. Mahar Doan, J. E. Humphreys, L. O. Webster, S. A. Wring, L. J. Shampine, C. J. Serabjit-Singh, K. K. Adkison, and J. W. Polli. Passive permeability and P-glycoprotein-mediated efflux differentiate central nervous system (CNS) and non-CNS marketed drugs. J. Pharmacol. Exp. Ther. 303:1029–1037 (2002).

    Article  PubMed  Google Scholar 

  17. M. D. Troutman, and D. R. Thakker. Rhodamine 123 requires carrier-mediated influx for its activity as a P-glycoprotein substrate in Caco-2 cells. Pharm. Res. 20:1192–1199 (2003).

    Article  PubMed  CAS  Google Scholar 

  18. N. Petri, C. Tannergren, D. Rungstad, and H. Lennernas. Transport characteristics of fexofenadine in the Caco-2 cell model. Pharm. Res. 21:1398–1404 (2004).

    Article  PubMed  CAS  Google Scholar 

  19. M. E. Taub, L. Podila, D. Ely, and I. Almeida. Functional assessment of multiple P-glycoprotein (P-gp) probe substrates: influence of cell line and modulator concentration on P-gp activity. Drug Metab. Dispos. 33:1679–1687 (2005).

    Article  PubMed  CAS  Google Scholar 

  20. C. Dagenais, C. L. Graff, and G. M. Pollack. Variable modulation of opioid brain uptake by P-glycoprotein in mice. Biochem. Pharmacol. 67:269–276 (2004).

    Article  PubMed  CAS  Google Scholar 

  21. H. Kusuhara and Y. Sugiyama. Efflux transport systems for drugs at the blood-brain barrier and blood-cerebrospinal fluid barrier (Pt. 2). Drug Discov. Today 6:206–212 (2001).

    Article  PubMed  CAS  Google Scholar 

  22. M. Rowland and S. B. Matin. Kinetics of drug–drug interactions. J. Pharmacokinet. Biopharm. 1:553–567 (1973).

    Article  CAS  Google Scholar 

  23. A. Balakrishnam and J. E. Polli. Bias in estimation of transporter kinetic parameters: interplay of transporter expression level and substrate affinity. J. Clin. Pharmacol. 45:1087 (2005).

    Google Scholar 

  24. M. Muszkat, D. Kurnik, G. G. Sofowora, J. P. Donahue, G. R. Wilkinson, and A. J. Wood. Tariquidar (TAR, XR-9576) selectively inhibits P-glycoprotein (P-GP) in T-lymphocytes compared to that in the blood–brain barrier (BBB). Clin. Pharmacol. Ther. 77:39 (2005).

    Article  Google Scholar 

  25. T. Hulgan, J. P. Donahue, C. Hawkins, D. Unutmaz, R. T. D’Aquila, S. Raffanti, F. Nicotera, P. Rebeiro, H. Erdem, M. Rueff, and D. W. Haas. Implications of T-cell P-glycoprotein activity during HIV-1 infection and its therapy. J. Acquir. Immune Defic. Syndr. 34:119–126 (2003).

    Article  PubMed  CAS  Google Scholar 

  26. J. C. Kalvass, C. L. Graff, and G. M. Pollack. Use of loperamide as a phenotypic probe of mdr1a status in CF-1 mice. Pharm. Res. 21:1867–1870 (2004).

    Article  PubMed  CAS  Google Scholar 

  27. K. Yasuda, L. B. Lan, D. Sanglard, K. Furuya, J. D. Schuetz, and E. G. Schuetz. Interaction of cytochrome P450 3A inhibitors with P-glycoprotein. J. Pharmacol. Exp. Ther. 303:323–332 (2002).

    Article  PubMed  CAS  Google Scholar 

  28. B. Bauer, D. S. Miller, and G. Fricker. Compound profiling for P-glycoprotein at the blood–brain barrier using a microplate screening system. Pharm. Res. 20:1170–1176 (2003).

    Article  PubMed  CAS  Google Scholar 

  29. M. Barecki-Roach, E. J. Wang, and W. W. Johnson. Many P-glycoprotein substrates do not inhibit the transport process across cell membranes. Xenobiotica 33:131–140 (2003).

    Article  PubMed  CAS  Google Scholar 

  30. J. Zong and G. M. Pollack. Modulation of P-glycoprotein transport activity in the mouse blood–brain barrier by rifampin. J. Pharmacol. Exp. Ther. 306:556–562 (2003).

    Article  PubMed  CAS  Google Scholar 

  31. C. Wandel, R. Kim, M. Wood, and A. Wood. Interaction of morphine, fentanyl, sufentanil, alfentanil, and loperamide with the efflux drug transporter P-glycoprotein. Anesthesiology 96:913–920 (2002).

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We gratefully thank Maciej Zamek-Gliszczynski, Rong Zhao, and Beverly Mowrey for critically reading the manuscript. This work was supported by NIH GM61191 and Pfizer Inc. J. Cory Kalvass was supported by a predoctoral fellowship in pharmacokinetics and drug disposition from the Eli Lilly and Company Foundation.

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Correspondence to Gary M. Pollack.

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Kalvass, J.C., Pollack, G.M. Kinetic Considerations for the Quantitative Assessment of Efflux Activity and Inhibition: Implications for Understanding and Predicting the Effects of Efflux Inhibition. Pharm Res 24, 265–276 (2007). https://doi.org/10.1007/s11095-006-9135-x

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  • DOI: https://doi.org/10.1007/s11095-006-9135-x

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