Association between the number of coadministered P-glycoprotein inhibitors and serum digoxin levels in patients on therapeutic drug monitoring

BACKGROUND: The ABC transporter P-glycoprotein (P-gp) is recognized as a site for drug-drug interactions and provides a mechanistic explanation for clinically relevant pharmacokinetic interactions with digoxin. The question of whether several P-gp inhibitors may have additive effects has not yet been addressed. METHODS: We evaluated the effects on serum concentrations of digoxin (S-digoxin) in 618 patients undergoing therapeutic drug monitoring. P-gp inhibitors were classified as Class I, with a known effect on digoxin kinetics, or Class II, showing inhibition in vitro but no documented effect on digoxin kinetics in humans. Mean S-digoxin values were compared between groups of patients with different numbers of coadministered P-gp inhibitors by a univariate and a multivariate model, including the potential covariates age, sex, digoxin dose and total number of prescribed drugs. RESULTS: A large proportion (47%) of the digoxin patients undergoing therapeutic drug monitoring had one or more P-gp inhibitor prescribed. In both univariate and multivariate analysis, S-digoxin increased in a stepwise fashion according to the number of coadministered P-gp inhibitors (all P values < 0.01 compared with no P-gp inhibitor). In multivariate analysis, S-digoxin levels were 1.26 ± 0.04, 1.51 ± 0.05, 1.59 ± 0.08 and 2.00 ± 0.25 nmol/L for zero, one, two and three P-gp inhibitors, respectively. The results were even more pronounced when we analyzed only Class I P-gp inhibitors (1.65 ± 0.07 for one and 1.83 ± 0.07 nmol/L for two). CONCLUSIONS: Polypharmacy may lead to multiple drug-drug interactions at the same site, in this case P-gp. The S-digoxin levels increased in a stepwise fashion with an increasing number of coadministered P-gp inhibitors in patients taking P-gp inhibitors and digoxin concomitantly. As coadministration of digoxin and P-gp inhibitors is common, it is important to increase awareness about P-gp interactions among prescribing clinicians

Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening