Skip to main content

Advertisement

SpringerLink
Log in

Compartmental Models for Apical Efflux by P-glycoprotein—Part 1: Evaluation of Model Complexity

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

ABSTRACT

Purpose

With the goal of quantifying P-gp transport kinetics, Part 1 of these manuscripts evaluates different compartmental models and Part 2 applies these models to kinetic data.

Methods

Models were developed to simulate the effect of apical efflux transporters on intracellular concentrations of six drugs. The effect of experimental variability on model predictions was evaluated. Several models were evaluated, and characteristics including membrane configuration, lipid content, and apical surface area (asa) were varied.

Results

Passive permeabilities from MDCK-MDR1 cells in the presence of cyclosporine gave lower model errors than from MDCK control cells. Consistent with the results in Part 2, model configuration had little impact on calculated model errors. The 5-compartment model was the simplest model that reproduced experimental lag times. Lipid content and asa had minimal effect on model errors, predicted lag times, and intracellular concentrations. Including endogenous basolateral uptake activity can decrease model errors. Models with and without explicit membrane barriers differed markedly in their predicted intracellular concentrations for basolateral drug exposure. Single point data resulted in clearances similar to time course data.

Conclusions

Compartmental models are useful to evaluate the impact of efflux transporters on intracellular concentrations. Whereas a 3-compartment model may be sufficient to predict the impact of transporters that efflux drugs from the cell, a 5-compartment model with explicit membranes may be required to predict intracellular concentrations when efflux occurs from the membrane. More complex models including additional compartments may be unnecessary.

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

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

Similar content being viewed by others

Abbreviations

3C, 5C, 6C, 7C, 9C:

3-, 5-, 6-, 7-, and 9-compartmental models respectively

6Phys, 7Phys, 9Phys:

6-, 7-, and 9-comparment models with physiologic volumes of plasma membranes

A→B:

Apical to basolateral transport

ABCB1:

ATP-binding cassette transporter B1

asa:

Apical-to-basolateral surface area ratio

B→A:

Basolateral to apical transport

Ccell,AB ratio :

The ratio on predicted intracellular concentration in the A→B direction without efflux transport to with efflux transport

Ccell,BA ratio :

The ratio on predicted intracellular concentration in the B→A direction without efflux transport to with efflux transport

CLae :

Active apical efflux clearance

CLbu :

Active basolateral uptake clearance

CLcib :

Clearance through a compound independent barrier

CLd :

Passive diffusion clearance

CLi :

Diffusion clearance into an explicit membrane compartment

CLo :

Diffusion clearance out of an explicit membrane compartment

CsA:

Cyclosporine A

ER:

Efflux ratio

Kp:

Partition constant for the drug partitioning into microsomal membranes (Kp = CLi/CLo)

MDCK:

Madin-Darby canine kidney cells

MDCK-MDR1:

MDCK cells stably transfected with human MDR1

MDR1 :

Multidrug resistance protein 1 gene

Papp :

Apparent permeability

P-gp:

P-glycoprotein

tlag :

Permeability lag time

REFERENCES

  1. Giacomini KM, Huang SM, Tweedie DJ, Benet LZ, Brouwer KL, Chu X, et al. Membrane transporters in drug development. Nat Rev Drug Discov. 2010;9(3):215–36.

    Article  CAS  PubMed  Google Scholar 

  2. Chu X, Korzekwa K, Elsby R, Fenner K, et al. Intracellular drug concentrations and transporters: measurement, modeling, and implications for the liver. Clin Pharmacol Ther. 2013;94:126–141.

    Google Scholar 

  3. Smith DA, Di L, Kerns EH. The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nat Rev Drug Discov. 2010;9(12):929–39.

    Article  CAS  PubMed  Google Scholar 

  4. Yabe Y, Galetin A, Houston JB. Kinetic characterization of rat hepatic uptake of 16 actively transported drugs. Drug Metab Dispos. 2011;39(10):1808–14.

    Article  CAS  PubMed  Google Scholar 

  5. Shitara Y, Maeda K, Ikejiri K, Yoshida K, Horie T, Sugiyama Y. Clinical significance of organic anion transporting polypeptides (OATPs) in drug disposition: their roles in the hepatic clearance and intestinal absorption. Biopharm Drug Dispos. 2013;34(1):45–78.

    Article  CAS  PubMed  Google Scholar 

  6. Fridén M, Bergström F, Wan H, Rehngren M, Ahlin G, Hammarlund-Udenaes M, et al. Measurement of unbound drug exposure in brain: modeling of pH partitioning explains diverging results between the brain slice and brain homogenate methods. Drug Metab Dispos. 2011;39(3):353–62.

    Article  PubMed  Google Scholar 

  7. Guideline on the Investigation of Drug Interactions EMA Guidline: www.ema.europa.eu

  8. Drug Interaction Studies — Study Design, Data Analysis, Implications for Dosing, and Labeling Recommendations. FDA Guidance for Industry: http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/default.htm

  9. Korzekwa KR, Nagar S, Tucker J, Weiskircher EA, Bhoopathy S, Hidalgo IJ. Models to predict unbound intracellular drug concentrations in the presence of transporters. Drug Metab Dispos. 2012;40(5):865–76.

    Article  CAS  PubMed  Google Scholar 

  10. Zamek-Gliszczynski MJ, Lee CA, Poirier A., Bentz J, et al. ITC Recommendations for Transporter Kinetic Parameter Estimation and Translational Modeling of Transport-Mediated PK and DDIs in Humans. Clin Pharmacol Ther. 2013;94:64–79.

    Google Scholar 

  11. Ménochet K, Kenworthy KE, Houston JB, Galetin A. Simultaneous assessment of uptake and metabolism in rat hepatocytes: a comprehensive mechanistic model. J Pharmacol Exp Ther. 2012;341(1):2–15.

    Article  PubMed  Google Scholar 

  12. Kalvass JC, Pollack GM. Kinetic considerations for the quantitative assessment of efflux activity and inhibition: implications for understanding and predicting the effects of efflux inhibition. Pharm Res. 2007;24(2):265–76.

    Article  CAS  PubMed  Google Scholar 

  13. Agnani D, Acharya P, Martinez E, Tran TT, Abraham F, Tobin F, et al. Fitting the elementary rate constants of the P-gp transporter network in the hMDR1-MDCK confluent cell monolayer using a particle swarm algorithm. PLoS One. 2011;6(10):e25086.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  14. Sun H, Pang KS. Permeability, transport, and metabolism of solutes in Caco-2 cell monolayers: a theoretical study. Drug Metab Dispos. 2008;36(1):102–23.

    Article  CAS  PubMed  Google Scholar 

  15. Gottesman MM, Pastan I, Ambudkar SV. P-glycoprotein and multidrug resistance. Curr opinion Genet Dev. Elsevier; 1996;6(5):610–617.

    Google Scholar 

  16. Jin MS, Oldham ML, Zhang Q, Chen J. Crystal structure of the multidrug transporter P-glycoprotein from Caenorhabditis elegans. Nature Engl. 2012;490(7421):566–9.

    Article  CAS  Google Scholar 

  17. Alberts B, Johnson A, Lewis J, Raff M, Roberts K, Walter P. Intracellular Compartments and Protein Sorting. In Molecular Biology of the Cell. 4th ed. NY: Garland Science; 2002.

    Google Scholar 

  18. Austin RP, Barton P, Cockroft SL, Wenlock MC, Riley RJ. The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties. Drug Metab Dispos. 2002;30(12):1497–503.

    Article  CAS  PubMed  Google Scholar 

  19. Wang Q, Strab R, Kardos P, Ferguson C, Li J, Owen A, et al. Application and limitation of inhibitors in drug-transporter interactions studies. Int J Pharm. 2008;356(1–2):12–8.

    Article  CAS  PubMed  Google Scholar 

  20. Nagar S, Korzekwa K. Commentary: nonspecific protein binding versus membrane partitioning: It is not just Semantics. Drug Metab Dispos. 2012;40(9):1649–52.

    Article  CAS  PubMed  Google Scholar 

  21. Butor C, Davoust J. Apical to basolateral surface area ratio and polarity of MDCK cells grown on different supports. Exp Cell Res. 1992;203(1):115–27.

    Article  CAS  PubMed  Google Scholar 

  22. Corradini MG, Peleg M. Estimating non-isothermal bacterial growth in foods from isothermal experimental data. J Appl Microbiol. 2005;99(1):187–200.

    Article  CAS  PubMed  Google Scholar 

  23. Sahin S, Estudante M, Benet L. Role of P-gp on the Transport of Verapamil Across MDCK and MDR1-MDCK Cell Monolayers. AAPS Journal 9, poster T3474 (2007).

  24. Kuteykin-Teplyakov K, Luna-Tortós C, Ambroziak K, Löscher W. Differences in the expression of endogenous efflux transporters in MDR1-transfected versus wildtype cell lines affect P-glycoprotein mediated drug transport. Br J Pharmacol. 2010;160(6):1453–63.

    Article  CAS  PubMed  Google Scholar 

  25. Acharya P, O'Connor MP, Polli JW, Ayrton A, Ellens H, Bentz J. Kinetic identification of membrane transporters that assist P-glycoprotein-mediated transport of digoxin and loperamide through a confluent monolayer of MDCKII-hMDR1 cells. Drug Metab Dispos. 2008;36(2):452–60.

    Article  CAS  PubMed  Google Scholar 

  26. Schlager SI, Ohanian SH. Tumor cell lipid composition and sensitivity to humoral immune killing. II. Influence of plasma membrane and intracellular lipid and fatty acid content. J Immunol. 1980;125(2):508–17.

    CAS  PubMed  Google Scholar 

  27. Spector AA, Yorek MA. Membrane lipid composition and cellular function. J Lipid Res. 1985;26(9):1015–35.

    CAS  PubMed  Google Scholar 

  28. Carpenter HM, Hedstrom OR, Siddens LK, Duimstra JR, Cai ZW, Fisher KA, et al. Ultrastructural, protein, and lipid changes in liver associated with chlordecone treatment of mice. Fundam Appl Toxicol. 1996;34(1):157–64.

    Article  CAS  PubMed  Google Scholar 

  29. Janmey PA, Kinnunen PK. Biophysical properties of lipids and dynamic membranes. Trends Cell Biol. 2006;16(10):538–46.

    Article  CAS  PubMed  Google Scholar 

  30. 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(2):215–22.

    Article  CAS  PubMed  Google Scholar 

  31. Ose A, Kusuhara H, Endo C, Tohyama K, Miyajima M, Kitamura S, et al. Functional characterization of mouse organic anion transporting peptide 1a4 in the uptake and efflux of drugs across the blood–brain barrier. Drug Metab Dispos. 2010;38(1):168–76.

    Article  CAS  PubMed  Google Scholar 

  32. Hendrikse NH, Schinkel AH, de Vries EG, Fluks E, Van der Graaf WT, Willemsen AT, et al. Complete in vivo reversal of P-glycoprotein pump function in the blood–brain barrier visualized with positron emission tomography. Br J Pharmacol. 1998;124(7):1413–8.

    Article  CAS  PubMed  Google Scholar 

  33. Uchida Y, Ohtsuki S, Kamiie J, Terasaki T. Blood–brain barrier (BBB) pharmacoproteomics: reconstruction of in vivo brain distribution of 11 P-glycoprotein substrates based on the BBB transporter protein concentration, in vitro intrinsic transport activity, and unbound fraction in plasma and brain in mice. J Pharmacol Exp Ther. 2011;339(2):579–88.

    Article  CAS  PubMed  Google Scholar 

  34. Kalvass JC, Graff CL, Pollack GM. Use of loperamide as a phenotypic probe of mdr1a status in CF-1 mice. Pharm Res. 2004;21(10):1867–70.

    Article  CAS  PubMed  Google Scholar 

  35. Schinkel AH, Wagenaar E, Mol CA, van Deemter L. P-glycoprotein in the blood–brain barrier of mice influences the brain penetration and pharmacological activity of many drugs. J Clin Invest. 1996;97(11):2517–24.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  36. Fujino H, Yamada I, Shimada S, Kojima J. Metabolic fate of pitavastatin, a new inhibitor of HMG-CoA reductase–effect of cMOAT deficiency on hepatobiliary excretion in rats and of mdr1a/b gene disruption on tissue distribution in mice. Drug Metab Pharmacokinet Japan; 2002;17(5):449–56.

    Article  CAS  Google Scholar 

  37. Schinkel AH, Wagenaar E, van Deemter L, Mol CA, Borst P. Absence of the mdr1a P-Glycoprotein in mice affects tissue distribution and pharmacokinetics of dexamethasone, digoxin, and cyclosporin A. J Clin Invest. 1995;96(4):1698–705.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. van Asperen J, Schinkel AH, Beijnen JH, Nooijen WJ, Borst P, van Tellingen O. Altered pharmacokinetics of vinblastine in Mdr1a P-glycoprotein-deficient Mice. J Natl Cancer Inst. 1996;88(14):994–9.

    Article  PubMed  Google Scholar 

  39. Jonker JW, Wagenaar E, van Deemter L, Gottschlich R, Bender HM, Dasenbrock J, et al. Role of blood–brain barrier P-glycoprotein in limiting brain accumulation and sedative side-effects of asimadoline, a peripherally acting analgaesic drug. Br J Pharmacol. 1999;127(1):43–50.

    Article  CAS  PubMed  Google Scholar 

  40. Salama NN, Kelly EJ, Bui T, Ho RJ. The impact of pharmacologic and genetic knockout of P-glycoprotein on nelfinavir levels in the brain and other tissues in mice. J Pharm Sci. 2005;94(6):1216–25.

    Article  CAS  PubMed  Google Scholar 

  41. Geyer J, Gavrilova O, Petzinger E. Brain penetration of ivermectin and selamectin in mdr1a, b P-glycoprotein- and bcrp- deficient knockout mice. J Vet Pharmacol Ther. 2009;32(1):87–96.

    Article  CAS  PubMed  Google Scholar 

  42. Sasabe H, Kato Y, Suzuki T, Itose M, Miyamoto G, Sugiyama Y. Differential involvement of multidrug resistance-associated protein 1 and P-glycoprotein in tissue distribution and excretion of grepafloxacin in mice. J Pharmacol Exp Ther. 2004;310(2):648–55.

    Article  CAS  PubMed  Google Scholar 

  43. Yokogawa K, Takahashi M, Tamai I, Konishi H, Nomura M, Moritani S, et al. P-glycoprotein-dependent disposition kinetics of tacrolimus: studies in mdr1a knockout mice. Pharm Res. 1999;16(8):1213–8.

    Article  CAS  PubMed  Google Scholar 

  44. Leusch A, Volz A, Müller G, Wagner A, Sauer A, Greischel A, et al. Altered drug disposition of the platelet activating factor antagonist apafant in mdr1a knockout mice. Eur J Pharm Sci. 2002;16(3):119–28.

    Article  CAS  PubMed  Google Scholar 

  45. Desrayaud S, De Lange EC, Lemaire M, Bruelisauer A, De Boer AG, Breimer DD. Effect of the Mdr1a P-glycoprotein gene disruption on the tissue distribution of SDZ PSC 833, a multidrug resistance-reversing agent, in mice. J Pharmacol Exp Ther. 1998;285(2):438–43.

    CAS  PubMed  Google Scholar 

Download references

ACKNOWLEDGMENTS AND DISCLOSURES

The authors (KK and SN) acknowledge support from National Institute of General Medical Sciences (grant R01GM104178). The authors acknowledge the technical assistance of Ms. Obioma Chikwendu with microsomal partitioning studies.

Author information

Authors and Affiliations

  1. Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N Broad Street, Philadelphia, Pennsylvania, 19140, USA

    Swati Nagar, Jalia Tucker & Ken Korzekwa

  2. Absorption Systems, L.P., Exton, Pennsylvania, USA

    Erica A. Weiskircher, Siddhartha Bhoopathy & Ismael J. Hidalgo

Authors
  1. Swati Nagar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jalia Tucker
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erica A. Weiskircher
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Siddhartha Bhoopathy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ismael J. Hidalgo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ken Korzekwa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ken Korzekwa.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 49.6 kb)

ESM 2

(11.4 MB)

High resolution image (JPEG 162 kb)

ESM 3

(11.4 MB)

High resolution image (JPEG 259 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nagar, S., Tucker, J., Weiskircher, E.A. et al. Compartmental Models for Apical Efflux by P-glycoprotein—Part 1: Evaluation of Model Complexity. Pharm Res 31, 347–359 (2014). https://doi.org/10.1007/s11095-013-1164-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11095-013-1164-7

KEY WORDS

Search

Navigation