Alterations in the permeability of cimetidine by dietary flavonoids using an in vitro transport model, Caco-2 cell

The goal of this dissertation is to investigate the interaction between cimetidine and dietary flavonoids using the Caco-2 cell transport model. It has been shown that flavonoids can change the bioavailability of pharmaceuticals, either by inhibiting metabolizing enzymes or inhibiting the drug efflux transporters. However, the effect of dietary flavonoids in the absorption of cimetidine has not been investigated. Therefore, the hypothesis of this study is that the absorption of cimetidine is mediated by a drug efflux pump, P-glycoprotein, of which dietary flavonoids can enhance the permeability of cimetidine by reducing P-glycoprotein function. The increase in permeability of cimetidine can increase the bioavailability of cimetidine. To test the hypothesis, three objectives were proposed. The first objective was to validate the Caco-2 transport model in our laboratory. The validation was performed by measuring the electrical resistance ofthe monolayer and determining the transport of paracellular marker. Also P-glycoprotein function was determined using rhodamine 123. The second objective was to describe the transport characteristics of cimetidine in the Caco-2 cell monolayers. The permeability of cimetidine was determined at different pH environments. When the permeability of cimetidine from apical to basolateral and basolateral to apical was compared, there appeared to be an effiux mechanism involved transport of cimetidine. The permeability of cimetidine in the presence of verapamil, a P-glycoprotein competitive inhibitor, suggested that P-glycoprotein was involved in the effiux. The third objective was to study the effect of dietary flavonoids on the permeability of cimetidine in the Caco-2 cell model. In the present study, four different flavonoids, quercetin, genistein, naringenin, and xanthohumol were selected. When co-treated with flavonoid aglycones, the permeability ofcimetidine was significantly reduced in the basolateral to apical direction. However, only genistin, a glycoside of genistein, significantly reduced the efflux of cimetidine. The present studies demonstrate that some dietary flavonoids, especially aglycones, can significantly reduce the effiux of cimetidine in the Caco-2 cell monolayers. Therefore, the fiavonoids consumed in a normal diet have the potential to enhance the bioavailability of cimetidine and possibly other P-glycoprotein substrates by altering their permeability

Application of receiver operating characteristic analysis to refine the prediction of potential digoxin drug interactionss

In the 2012 Food and Drug Administration (FDA) draft guidance on drug-drug interactions (DDIs), a new molecular entity that inhibits Pglycoprotein (P-gp) may need a clinical DDI study with a P-gp substrate such as digoxin when themaximumconcentration of inhibitor at steady state divided by IC50 ([I1]/IC50) is0.1 or concentration of inhibitor based on highest approved dose dissolved in 250 ml divide by IC50 ([I2]/IC 50) is10. In this article, refined criteria are presented, determined by receiver operating characteristic analysis, using IC50 values generated by 23 laboratories. P-gp probe substrates were digoxin for polarized cell-lines and N-methyl quinidine or vinblastine for P-gp overexpressed vesicles. Inhibition of probe substrate transport was evaluated using 15 known P-gp inhibitors. Importantly, the criteria derived in this article take into account variability in IC50 values. Moreover, they are statistically derived based on the highest degree of accuracy in predicting true positive and true negative digoxin DDI results. The refined criteria of [I1]/IC50 0.03 and [I2]/IC50 45 and FDA criteria were applied to a test set of 101 in vitro-in vivo digoxin DDI pairs collated from the literature. The number of false negatives (none predicted but DDI observed) were similar, 10 and 12%, whereas the number of false positives (DDI predicted but not observed) substantially decreased from 51 to 40%, relative to the FDA criteria. On the basis of estimated overall variability in IC50 values, a theoretical 95%confidence interval calculation was developed for single laboratory IC 50 values, translating into a range of [I1]/IC50 and [I2]/IC50 values. The extent by which this range falls above the criteria is a measure of risk associated with the decision, attributable to variability in IC50 values. © 2013 by The American Society for Pharmacology

Variability in P-Glycoprotein Inhibitory Potency (IC 50

A P-glycoprotein (P-gp) IC50 working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC 50 determinations. Each laboratory followed its in-house protocol to determine in vitro IC50 values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells-Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLCPK1- MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC50 values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC50 values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC50 values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratiobased equation generally resulted in severalfold lower IC 50 values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC50 values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC 50 determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided. © 2013 by The American Society for Pharmacology

Variability in P-Glycoprotein Inhibitory Potency (IC50) Using Various in Vitro Experimental Systems: Implications for Universal Digoxin Drug- Drug Interaction Risk Assessment Decision Criterias

A P-glycoprotein (P-gp) IC(50) working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC(50) determinations. Each laboratory followed its in-house protocol to determine in vitro IC(50) values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells—Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLC-PK(1)-MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC(50) values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC(50) values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC(50) values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratio-based equation generally resulted in severalfold lower IC(50) values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC(50) values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC(50) determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided