Refining the in vitro and in vivo critical parameters for P-glycoprotein, [I]/IC50 and [I2]/IC50, that allow for the exclusion of drug candidates from clinical digoxin interaction studies.

Departments of Clinical Pharmacology, Pharmacokinetics, Groton/New London, Connecticut, Sandwich, UK.
Molecular Pharmaceutics (Impact Factor: 4.57). 12/2009; 7(2):398-411.
Source: PubMed

ABSTRACT The objective of this work was to further investigate the reasons for disconcordant clinical digoxin drug interactions (DDIs) particularly for false negative where in vitro data suggests no P-glycoprotein (P-gp) related DDI but a clinically relevant DDI is evident. Applying statistical analyses of binary classification and receiver operating characteristic (ROC), revised cutoff values for ratio of [I]/IC(50) < 0.1 and [I(2)]/IC(50) < 5 were identified to minimize the error rate, a reduction of false negative rate to 9% from 36% (based on individual ratios). The steady state total C(max) at highest dose of the inhibitor is defined as [I] and the ratio of the nominal maximal gastrointestinal concentration determined for highest dose per 250 mL volume defined [I(2)](.) We also investigated the reliability of the clinical data to see if recommendations can be made on values that would allow predictions of 25% change in digoxin exposure. The literature derived clinical digoxin interaction studies were statistically powered to detect relevant changes in exposure associated with digitalis toxicities. Our analysis identified that many co-meds administered with digoxin are cardiovascular (CV) agents. Moreover, our investigations also suggest that the presence of CV agents may alter cardiac output and/or kidney function that may act alone or are additional components to enhance digoxin exposure along with P-gp interaction. While we recommend digoxin as the probe substrate to define P-gp inhibitory potency for clinical assessment, we observed high concordance in P-gp inhibitory potency for calcein AM as a probe substrate.

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    ABSTRACT: The multidrug resistance protein 1 (MDR1) is known to limit drug brain penetration and be a key player in drug-drug interactions (DDI). Theoretical cutoffs from regulatory guidelines are used to extrapolate MDR1 interactions from in vitro to in vivo. However, these cut-offs do not account for inter-laboratory variability. Our aim was to calibrate our experimental system to allow better in vivo predictions. 166 CNS and non-CNS drugs were selected to calibrate the MDR1 transport screening assay using LLC-PK1 cells overexpressing MDR1 (L-MDR1). A threshold efflux ratio (ER) of 2 was established as one parameter to assess brain penetration in lead optimization. The inhibitory potential of 57 molecules was evaluated using IC50 values based on digoxin ER (IC50(ER)) or permeability (IC50(Papp)) in L-MDR1 cells. Published clinical data for 68 DDIs involving digoxin as the victim drug were collected. DDI risk assessments were based on intestinal concentrations ([I2]), as well as, unbound [I1u] and total plasma [I1T] concentrations. A receiver operating characteristic analysis identified an [I2]/IC50(ER) of 6.5 as the best predictor of a potential interaction with digoxin in patients. The model was further evaluated with a test set of 11 digoxin DDIs and 16 non-digoxin DDIs, resulting in only 1 false negative for each test set, no false positive among the digoxin DDIs and 2 among the non-digoxin DDIs. Future refinements might include using cerebrospinal fluid to unbound plasma concentration ratios rather than therapeutic class, better estimation of [I2] or dynamic modeling of MDR1-mediated DDIs.
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