Variability in P-glycoprotein inhibitory potency (IC₅₀) using various in vitro experimental systems: implications for universal digoxin drug-drug interaction risk assessment decision criteria

Abstract

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 IC₅₀ 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 (LLC-PK1-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 ratio-based equation generally resulted in severalfold lower IC₅₀ 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 IC₅₀ 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.

Fig. 1.

Flowchart illustrating the process of data generation and analysis by the P-gp inhibition working group. Since one of the 16 compounds (captopril) did not inhibit P-gp in any of the systems used it was not included in the analysis of P-gp IC₅₀ variability. Therefore the variability analysis was performed on 15 compounds.

Fig. 2.

Inhibition of digoxin transport. The symbols in (A), (B), (C), and (D) are triplicate data points of inhibition of B>A digoxin transport by increasing concentrations of carvedilol (Caco-2 cells), troglitazone (Caco-2 cells), ranolazine (LLC-PK₁-MDR1 cells), and verapamil (MDCKII-MDR1 cells), respectively. The line is the 3-parameter logistic fit to the data.

Fig. 3.

Example data set illustrating the impact of the selected regression model (2- or 4-parameter logistic fit) on the resulting IC₅₀ value. Symbols represent experimental data, lines represent nonlinear regression results for 2-parameter [(A), (C), (E)] or 4-parameter [(B), (D), (F)] fits. (A) and (B) show inhibition of B>A digoxin transport by increasing concentrations of verapamil (MDCKII-MDR1 cells) with t_αβ (2p*3p) = 18.6 and t_ββ (2p*3p) = 18.6. (C) and (D) show inhibition of B>A digoxin transport by increasing concentrations of diltiazem (Caco-2 cells) with t_αβ (2p*3p)=5.5 and t_ββ (2p*3p)=5.4. (E) and (F) show inhibition of vinblastine uptake by increasing concentrations of quinidine (vesicles) with t_αβ (2p*3p) = 4.9 and t_ββ (2p*3p) = 4.2.

Fig. 4.

IC₅₀ values for 15 compounds in the four experimental systems. For cell-based data, IC₅₀ values were based on eqs. A1, B1, C1, and D to calculate P-gp transport activity. The numbers on the x-axis refer to inhibitors as follows: amiodarone (1), carvedilol (2), diltiazem (3), felodipine (4), isradipine (5), mibefradil (6), nicardipine (7), nifedipine (8), nitrendipine (9), quinidine (10), ranolazine (11), sertraline (12), telmisartan (13), troglitazone (14), and verapamil (15). Captopril was not included because it did not inhibit P-gp in any of the systems used. Blue diamonds, cell eq. A1, green squares cell eq. B1, red triangles, cell eq. C1, black circles, cell eq. D1, black stars, vesicles. Note: each of the inhibitors has a different number of IC₅₀ values for each of the four experimental systems and for each of the four data transformation equations applied to the cell-based data. As seen in the Supplemental Data, a considerable amount of data is missing due to unacceptable t-statistics.

Fig. 5.

Comparisons between IC₅₀ values for eqs. A1 and A2 [(A): since IC₅₀ values were not fitted for eq. A2, interpolated values are used for comparison with eq. A1), A1 and C1 (B), B1 and D (C) and A1 and B1 (D). The blue circles represent IC₅₀ values obtained using Caco-2 cells, the red squares MDCKII-MDR1 cells, and the red triangles LLC-PK₁-MDR1.

Fig. 6.

Variability plot of cell line-derived Ln IC₅₀ values calculated for transport inhibition in the A>B direction (A) and of cell line and vesicle-derived Ln IC₅₀ values for transport inhibition in the B>A (or in the case of vesicles B>A equivalent) direction (B). All IC₅₀ values were calculated by eq. 2.2. Each of the data points in the graphs represents a ln IC₅₀ value. The range of values within each system is represented by the blue outline. The range of values within each laboratory is represented by the red outline. The large blue rectangles represent the variability across systems and the small red rectangles represent variability across laboratories.

Fig. 7.

Principal component analysis. Closed blue circles, Caco-2; closed red squares, MDCKII-MDR1; open red triangles, LLC-PK₁-MDR1; open blue stars, vesicles. Laboratory numbers (also shown in Tables 1–4) are associated with each data point in the graph. Axis 1 represents the average log₁₀{IC₅₀} value for the eight inhibitors in group 1 (Table 9) multiplied by their eigenvalues. Axis 2 represents the second largest variance in the IC₅₀ values which depends largely on mibefradil and nicardipine (Table 10).