Mechanistic kinetic modeling generates system-independent P-glycoprotein mediated transport elementary rate constants for inhibition and, in combination with 3D SIM microscopy, elucidates the importance of microvilli morphology on P-glycoprotein mediated efflux activity

ABSTRACT

Introduction: In vitro transporter kinetics are typically analyzed by steady-state Michaelis-Menten approximations. However, no clear evidence exists that these approximations, applied to multiple transporters in biological membranes, yield system-independent mechanistic parameters needed for reliable in vivo hypothesis generation and testing.

Areas covered: The classical mass action model has been developed for P-glycoprotein (P-gp) mediated transport across confluent polarized cell monolayers. Numerical integration of the mass action equations for transport using a stable global optimization program yields fitted elementary rate constants that are system-independent. The efflux active P-gp was defined by the rate at which P-gp delivers drugs to the apical chamber, since as much as 90% of drugs effluxed by P-gp partition back into nearby microvilli prior to reaching the apical chamber. The efflux active P-gp concentration was 10-fold smaller than the total expressed P-gp for Caco-2 cells, due to their microvilli membrane morphology. The mechanistic insights from this analysis are readily extrapolated to P-gp mediated transport in vivo.

Expert opinion: In vitro system-independent elementary rate constants for transporters are essential for the generation and validation of robust mechanistic PBPK models. Our modeling approach and programs have broad application potential. They can be used for any drug transporter with minor adaptations.

KEYWORDS:

• Mechanistic PBPK modeling
• 3D structured illumination microscopy (3D SIM)
• microvilli morphology
• P-glycoprotein transport
• global optimization
• structural mass action kinetic model

Article Highlights

• The structural mass action kinetic model for P-gp, and its substrate associated uptake transporters, is the classical law of mass action using all relevant membrane structure parameters. No steady-state approximations are used. It yields system-independent elementary kinetic constants using a global optimization fitting routine.

• The model quantifies efflux active P-gp (whose effluxed drug reaches the apical chamber) as a mass action kinetic variable, rather than total plasma membrane P-gp measured by LC-MS/MS, most of whose effluxed drug does not usually reach the apical chamber.

• A comparison of the levels of efflux active and total P-gp in Caco-2 and MDCKII cells has shown that not all P-gp contributes to efflux to the apical chamber. For the Caco-2 cells, only 10% of total P-gp on the apical membrane surface actually contributed to transport into the apical chamber. For MDCKII-hMDR1-NKI cells 60% percent of total P-gp contributed to efflux into the apical chamber.

• 3D structured illumination fluorescence microscopy (3D SIM) was used to demonstrate the importance of microvilli morphology in determining the fraction of total P-gp that is efflux active.

• Our modeling has been extensively validated and the system-independent elementary rate constants and their derivatives, e.g. Ki, should be directly translatable to in vivo for use in mechanistic PBPK models without the need of scaling factors. Since many compounds are substrates or inhibitors of multiple transporters, the true value for mechanistic PBPK modeling can only be fully demonstrated when in vitro mechanistic kinetic parameters are generated for all transporters kinetically relevant to the compound in question.

• The same kinetic equations written for the in vitro system can be incorporated into in vivo PBPK models, allowing for the calibration of efflux active P-gp and expression levels of substrate associated uptake transporters, and guide in vivo mechanistic in vivo hypothesis generation, as has been demonstrated for several distinct in vitro systems.

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Acknowledgments

We thank Dr. Michael O’Connor for expert advice on statistical analysis (Drexel University, Philadelphia, PA) and Dr. Annie Lumen (National Center for Toxicological Research/FDA, AK, USA) for critical reading of this manuscript.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was funded by Drexel University Fund PI O/H Share J. Bentz [#140136-3650-4999] Department of Biology (Drexel University).