Kinetic Analysis of Human and Canine P-Glycoprotein-Mediated Drug Transport in MDR1-MDCK Cell Model: Approaches to Reduce False-Negative Substrate Classification

Madin-Darby canine kidney (MDCK) cells transfected with the multidrug resistance 1 (MDR1) gene, MDR1-MDCK, are widely used as an in vitro model to classify compounds as human P-glycoprotein (hPgp) substrates or nonsubstrates. Because MDCK cells express endogenous canine Pgp (cPgp), which is prone to...

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Veröffentlicht in:Journal of pharmaceutical sciences 2013-09, Vol.102 (9), p.3436-3446
Hauptverfasser: Li, Jibin, Wang, Ying, Hidalgo, Ismael J.
Format: Artikel
Sprache:eng
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Zusammenfassung:Madin-Darby canine kidney (MDCK) cells transfected with the multidrug resistance 1 (MDR1) gene, MDR1-MDCK, are widely used as an in vitro model to classify compounds as human P-glycoprotein (hPgp) substrates or nonsubstrates. Because MDCK cells express endogenous canine Pgp (cPgp), which is prone to downregulation after transfection with hPgp, this situation could lead to false-negative classification of hPgp substrates. The aim of this study was to investigate factors that influence hPgp substrate classification in MDR1-MDCK model and to seek ways to reduce false classification. Three-compartment models were used to derive flux equations describing the drug transport processes; factors influencing hPgp substrate classification were evaluated by simulations. Pgp functionality was assessed by determining the bidirectional permeability of a series of test compounds. Expressions of hPgp and cPgp were measured by quantitative polymerase chain reaction (qPCR). Kinetic model analysis revealed that the current net flux ratio calculation for hPgp substrate classification is influenced by endogenous cPgp expression as well as hPgp-cPgp expression ratio; the effect was more pronounced in low hPgp-cPgp region and diminished in high ratio region. On the basis of kinetic considerations, this study provides a rational experimental approach and appropriate mathematical corrections to minimize the potential occurrence of false-negative classification of new molecular entities.
ISSN:0022-3549
1520-6017
DOI:10.1002/jps.23523