A Clinical Drug‐Drug Interaction Study Assessing a Novel Drug Transporter Phenotyping Cocktail With Adefovir, Sitagliptin, Metformin, Pitavastatin, and Digoxin

Abstract

A new probe drug cocktail containing substrates of important drug transporters was tested for mutual interactions in a clinical trial. The cocktail consisted of (predominant transporter; primary phenotyping metric): 10 mg adefovirdipivoxil (OAT1; renal clearance (CL R )), 100 mg sitagliptin (OAT3; CL R ), 500 mg metformin (several renal transporters; CL R ), 2 mg pitavastatin (OATP1B1; clearance/F), and 0.5 mg digoxin (intestinal P-gp, renal P-gp, and OATP4C1; peak plasma concentration (C max ) and CL R ). Using a randomized six-period, open change-over design, single oral doses were administrated either concomitantly or separately to 24 healthy male and female volunteers. Phenotyping metrics were evaluated by noncompartmental analysis and compared between periods by the standard average bioequivalence approach (boundaries for ratios 0.80-1.25). Primary metrics supported the absence of relevant interactions, whereas secondary metrics suggested that mainly adefovir was a victim of minor drug-drug interactions (DDIs). All drugs were well tolerated. This cocktail may be another useful tool to assess transporter-based DDIs in vivo.

Combinations of common SNPs of the transporter gene ABCB1 influence apparent bioavailability, but not renal elimination of oral digoxin

“…In this evaluation based on a detailed characterization of digoxin pharmacokinetics in healthy volunteers, ABCB1 SNP combinations had a significant albeit small influence on the (apparent) bioavailability but not on the renal elimination of the drug. This result is in line with a previous non-compartmental analysis (NCA) of one of the studies included in this population pharmacokinetic evaluation, where C max and AUC 0–24 h of digoxin were significantly higher in CGC/CGT and TTT/TTT, but not in CGC/TTT carriers, compared to CGC/CGC 52 . In contrast, in a study by Xu et al subjects carrying TTT/TTT showed a higher average C max and AUC 0–4h 31 compared to CGC/CGC in a Chinese Han population, but the observed difference was not statistically significant.…”

“…However, we cannot rule out that our limited sample size was insufficient to detect minor differences in renal clearance between groups. Also, in our previous NCA analysis, no significant difference in renal clearance was found between CGC/CGC and other SNP combination groups 52 . When digoxin was given intravenously or orally with a strong P-gp inducer, renal elimination of digoxin was not relevantly affected, but the AUC 0–144 h for both administration routes and AUC 0–3 h , C max , and bioavailability for oral administration were decreased.…”

Identification of Appropriate Endogenous Biomarker for Risk Assessment of Multidrug and Toxin Extrusion Protein‐Mediated Drug‐Drug Interactions in Healthy Volunteers

“…Dosing several probe drugs in a cocktail is a way to assess the DDI risk of multiple transporters simultaneously in the same subject. 41,42 However, equivalence of the pharmacokinetic parameters of probe drugs between single dose and simultaneous dosing as a cocktail would need to be validated prior to its use. 42 Leveraging of multiplexed endogenous biomarkers is one possible way to facilitate simultaneous DDI assessment across multiple drug transporters early in clinical development without the potential need for DDI studies with individual probes or probe drug cocktails.…”

“…In this regard, as previously described for OATP1B, it is envisioned that physiologically-based pharmacokinetic (PBPK) model-based analysis will aid the design of clinical studies. 41 A PBPK model for metformin has already been constructed and it is able to describe the metformin-cimetidine DDI involving MATE1 inhibition. 43 Likewise, the construction of PBPK models for 1-NMN and m 1 A will advance the prediction of OCT2 and MATE1/2-Kmediated DDI in drug development.…”

In vitro and in vivo methods to assess pharmacokinetic drug– drug interactions in drug discovery and development

“…The five substrates showed no interactions among each other, as the PK profiles from discrete or cocktail dosing were comparable. Clinical DDI studies with cocktail substrates reduce the number of clinical trials, speed up drug development processes and enable better ethical compliance (Trueck et al, ). Similar cocktail approaches have been reported in human with micro‐dosing and in cynomolgus monkeys for both major CYPs and transporters (Kosa et al, ; Prueksaritanont et al, ).…”