Drug-drug Interaction Studies Research Articles

Lack of Clinically Meaningful Effect of Cariprazine on the Pharmacokinetics of a Combined Oral Contraceptive.

Cariprazine (CAR) is a potent dopamine receptor partial agonist antipsychotic approved by the EMA and the FDA. To address the uncertainty regarding the effectiveness of hormonal contraceptives during CAR co-administration and whether a second barrier method is necessary, a drug-drug interaction study with an oral contraceptive was conducted post-approval. The phaseI, fixed-sequence multicenter study involved two periods with 24 patients with schizophrenia, aiming to evaluate the effect of CAR on the pharmacokinetics (PK) of a combined oral contraceptive (COC) containing 30μg ethinylestradiol (EE) and 150μg levonorgestrel (LNG). In periodA, a single dose of COC alone was administered on day1. In periodB, the highest therapeutic dose of 6mg CAR was administered once daily from day4, and a second dose of COC was given concomitantly on day31. Overall, CAR had no clinically meaningful effect on the PK of the COC. The terminal half-life and the time of maximum plasma concentration of EE and LNG were not altered by CAR co-administration. The highest difference observed was a decrease of 14% in the maximum plasma concentration of EE, with only slight deviation of the 90% confidence interval (CI) of the test/reference ratio (77.09-96.81) from the generally accepted bioequivalence range of 80-125%, which is not considered clinically relevant. Confidence intervals of all other exposure measures were within the 80-125% range for both EE and LNG. According to these results, hormonal contraceptives can be considered effective during CAR treatment. Trial registration number (EudraCT) 2018-003722-80.

Pharmacokinetics of Atorvastatin and Metformin after Coadministration with Islatravir in Healthy Adults.

Islatravir, a deoxyadenosine analog that inhibits HIV-1 replication by multiple mechanisms of action, including reverse transcriptase translocation inhibition, is being developed for use in HIV-1 treatment. People living with HIV often have comorbidities, such as dyslipidemia or type 2 diabetes mellitus, necessitating long-term concomitant drug therapy. This nonrandomized, two-period, fixed-sequence, open-label, phase 1, drug-drug interaction study was conducted to evaluate the effects of islatravir coadministration on atorvastatin and metformin pharmacokinetics (PK) in healthy adults. In period 1, participants received a single dose of atorvastatin 20 mg and metformin 1000 mg. After a 5-day washout, participants received atorvastatin 20 mg and metformin 1000 mg coadministered with a single oral dose of islatravir 60 mg (period2). In both periods, blood samples were collected up to 72 h post dose to characterize the plasma PK of atorvastatin and metformin. Safety was monitored throughout the study. Fourteen participants were enrolled and completed the study. Atorvastatin and metformin plasma PK were similar after administration of atorvastatin and metformin with or without islatravir. The geometric mean ratio and 90% confidence interval of the area under the concentration-time curve from time zero to infinity (AUC0-∞) for atorvastatin and metformin with or without a single oral dose of islatravir were 1.04 (1.00-1.10) and 0.87 (0.79-0.96), respectively. Coadministration of islatravir with atorvastatin and metformin was well tolerated. Overall, coadministration of atorvastatin and metformin with a single oral dose of islatravir did not have a clinically meaningful effect on the PK profiles of either drug.

Patiromer Does Not Alter Tacrolimus Pharmacokinetics in Kidney Transplant Recipients When Administered Three Hours Post-Tacrolimus.

Hyperkalemia is common in kidney transplant (KTx) recipients. Patiromer, a potassium-binding polymer used to treat acute and chronic hyperkalemia, has the potential to bind charged particles in the gastrointestinal tract and thereby potentially affect the absorption of coadministered drugs. The immunosuppressive drug tacrolimus (Tac) has a narrow therapeutic window, is susceptible to drug-drug interactions (DDIs), and a potential gastrointestinal interaction with patiromer could elevate the risk of allograft rejection. We aimed to investigate the potential DDI between patiromer and Tac pharmacokinetics in KTx with hyperkalemia by sampling capillary blood using volumetric absorptive microsampling (VAMS). Thirteen KTx recipients on Tac twice daily (BID) with plasma potassium levels of >4.6 mmol/L were included. Two 12 h Tac pharmacokinetic investigations were performed with and without 8.4 mg patiromer/d for 1 wk. Oral Tac dose remained unchanged and patiromer was administered 3 h after Tac dose. Tac sampling was self-conducted using VAMS after mastering the technique. Ten patients provided 2 evaluable pharmacokinetic profiles. The Tac area under the curve (AUC)0-12 ratio (AUCTac+patiromer/AUCTac) was 0.99 (90% confidence interval [CI], 0.86-1.14), and the Cmax ratio was 1.01 (90% CI, 0.86-1.19). Tac C0 and C12 fulfilled the bioequivalence criteria with a ratio of 0.98 (90% CI, 0.90-1.07) and 0.93 (90% CI, 0.83-1.04), respectively. When administered 3 h after the Tac morning dose, patiromer has no clinically relevant impact on Tac pharmacokinetics. We demonstrate that VAMS is a well-suited sampling method to simplify the execution of DDI studies.

Effects of GLPG3970 on Sulfasalazine and Methotrexate Pharmacokinetics in Healthy Adults: Two Open-Label, Phase I, Drug-Drug Interaction Studies.

GLPG3970 is a selective salt-inducible kinase 2/3 inhibitor intended for the treatment of inflammatory diseases. In vitro studies suggest GLPG3970 strongly inhibits breast cancer resistance protein (BCRP), indicating a possible interaction with BCRP substrates such as sulfasalazine (SSZ; a probe substrate for intestinal BCRP inhibition) and methotrexate (MTX), both inflammatory disease medications. Two open-label, nonrandomized, phase I, drug-drug interaction (DDI) studies assessed the pharmacokinetics of SSZ 1,000 mg (NCT04720183) and MTX 7.5 mg (EudraCT: 2020-000391-37) with and without GLPG3970 350 mg. Healthy participants aged 18-55 years with wild-type homozygous BCRP genotype (c421C/C) received: SSZ on day (D)1, GLPG3970 + SSZ on D5, and GLPG3970 2 hours after SSZ on D9 (N = 8; SSZ/GLPG3970 DDI study); MTX on D1, GLPG3970 + MTX on D5, and GLPG3970 on D6-8 (N = 15; MTX/GLPG3970 DDI study). Primary end points were AUC and Cmax ("exposure") of SSZ and its metabolite (sulfapyridine [SPD]), SPD:SSZ AUC ratio (SSZ/GLPG3970 study), and AUC and Cmax ("exposure") of MTX (MTX/GLPG3970 study). DDIs were evaluated using the geometric mean ratio of each end point; a > 2-fold increase in SSZ or MTX exposure was deemed clinically relevant. GLPG3970 demonstrated mild inhibition of intestinal BCRP in vivo: GLPG3970 + SSZ increased SSZ exposure ~1.7-1.8-fold and decreased SPD:SSZ ratio ~ 2-fold vs. SSZ alone. GLPG3970 administered 2 hours after SSZ did not change the magnitude of the interaction. GLPG3970 + MTX had no relevant effect on MTX pharmacokinetics vs. MTX alone. Therefore, the strong in vitro BCRP inhibition was not confirmed in vivo. No safety concerns were observed when GLPG3970 was coadministered with SSZ or MTX.

Global sensitivity analysis of Open Systems Pharmacology Suite physiologically based pharmacokinetic models.

Sensitivity analyses are important components of physiologically based pharmacokinetic (PBPK) model development and are required by regulatory agencies for PBPK submissions. They assess the impact of parametric uncertainty and variability on model estimates, aid model optimization by identifying parameters requiring calibration, and enable the testing of assumptions within PBPK models. One-at-a-time (OAT) sensitivity analyses quantify the impact on a model output in response to changes in a single parameter while holding others fixed. Global sensitivity analysis (GSA) methods provide more comprehensive assessments by accounting for changes in all uncertain or variable parameters, though at a higher computational cost. This tutorial article presents a software package for conducting both OAT and GSA of PBPK models built in the Open Systems Pharmacology (OSP) Suite. The tool is accessible through either an R script or a graphical user interface, and the outputs consist of sensitivity metrics of pharmacokinetic (PK) parameters, such as Cmax and AUC, evaluated with respect to model input parameters. Results are formatted according to regulatory standards. The OAT analysis methods comprise two-way local sensitivity analyses and probabilistic uncertainty analyses, whereas the GSA methods include the Morris, Sobol, and EFAST methods. These analyses can be conducted on single PBPK models or pairs of models for the evaluation of the sensitivity of PK parameter ratiosin drug-drug interaction studies. The practical application of the package is demonstrated through three illustrative case studies.

Drug-Drug Interaction Management with the Novel Anti-Cytomegalovirus Agents Letermovir and Maribavir: Guidance for Clinicians.

Letermovir and maribavir have demonstrated efficacy in the prevention and treatment, respectively, of immunosuppressed patients with cytomegalovirus (CMV) infection and disease. These patients often have polypharmacy making them at risk for drug-drug interactions. Both letermovir and maribavir can be perpetrators and victims of drug-drug interactions. Letermovir is a moderate inhibitor of CYP3A, CYP2C8 and OATP1B1/3, and a moderate inducer of CYP2C19. It is a substrate of UGT1A1/3, BCRP, P-gp and OATP1B1/3. Maribavir is a moderate CYP2C9 inhibitor and a substrate of CYP3A. Drug-drug interactions between these anti-CMV agents and a number of therapeutic classes, such as immunosuppressants, antifungal agents, and hemato-oncological agents, can have clinical consequences and deserve dose modification or close monitoring. In a number of examples, three-way drug interactions need to be assessed. The objective of this review is to provide clinicians with guidance for drug-drug interaction management, based on existing data from drug-drug interaction studies, and extrapolation to other relevant co-medications that have not (yet) been studied but that are frequently used in these patient populations.

Ticagrelor modestly raises plasma riboflavin concentration in humans and inhibits riboflavin transport by BCRP and MRP4.

Riboflavin (vitamin B2) has been proposed as a biomarker for breast cancer resistance protein (BCRP) activity. In recent studies in mice, cynomolgus monkeys, and humans, BCRP-inhibiting drugs increased the plasma concentration of riboflavin. We showed recently that ticagrelor inhibits BCRP and raises the plasma concentrations of the BCRP substrate rosuvastatin in healthy volunteers. In the same drug-drug interaction study, we now investigated whether ticagrelor affects the plasma concentrations of riboflavin. Intake of 90 mg ticagrelor increased the ratio between the peak plasma riboflavin concentration and the fasting riboflavin concentration before ticagrelor administration by 1.20-fold (90% confidence interval, 1.10-1.32; P = 0.006) compared to placebo. In vitro, riboflavin was transported by BCRP and multidrug-resistance-associated protein 4 (MRP4) but no clear transport was observed by MRP2, MRP3, or the P-glycoprotein. Moreover, ticagrelor inhibited the transport of riboflavin in BCRP- and MRP4-expressing membrane vesicles with unbound 50% inhibitory concentrations of 0.020 and 1.1μM, respectively. Based on vesicle and tissue protein expression data, the small intestinal MRP4-mediated efflux clearance of riboflavin (1.2-1.4 nL/min/mg) was estimated to be similar to that mediated by BCRP (0.23-1.3 nL/min/mg). As MRP4 is expressed in the basolateral membrane of enterocytes, it may facilitate the absorption of riboflavin and impair the utility of riboflavin as a biomarker of intestinal BCRP. To conclude, ticagrelor modestly raises the plasma concentration of riboflavin probably by inhibiting intestinal BCRP. Inhibition of intestinal MRP4 may have reduced the absorption of riboflavin and limited the effect of ticagrelor on riboflavin levels.

Clinical Pharmacology of Asciminib: A Review.

Asciminib is a first-in-class allosteric inhibitor of the kinase activity of BCR::ABL1, specifically targeting the ABL myristoyl pocket (STAMP). This review focuses on the pharmacokinetic (PK) and pharmacodynamic data of asciminib, which is approved at a total daily dose of 80 mg for the treatment of adult patients with chronic myeloid leukemia in chronic phase who are either resistant or intolerant to ≥ 2 tyrosine kinase inhibitors or those harboring the T315I mutation (at a dose of 200 mg twice daily). Asciminib is predicted to be almost completely absorbed from the gut, with an absolute bioavailability (F) of approximately 73%. It should be administered in a fasted state, as food (particularly high-fat meals) reduces exposure. Asciminib displays a slightly greater than dose-proportional increase in exposure, with no time-dependent changes in PK observed following repeated dosing. This drug shows low clearance (6.31 L/h), with a moderate volume of distribution (111 L) and high human plasma protein binding (97.3%). The apparent terminal elimination half-life (t1/2) across studies was estimated to be between 7 and 15h. The PK of asciminib is not substantially affected by body weight, age, gender, race, or renal or hepatic impairment. Asciminib is primarily metabolized via CYP3A4-mediated oxidation (36.0%) and UGT2B7- and UGT2B17-mediated glucuronidation (13.3% and 7.8%, respectively); biliary secretion via breast cancer resistance protein contributes to about 31.1% to total systemic clearance, which is mainly through hepatic metabolism and biliary secretion through the fecal pathway, with renal excretion playing a minor role. The potential for PK drug interaction for asciminib both as a victim and a perpetrator has been summarized here based on clinical and predicted drug-drug interaction studies. Robust exposure-response models characterized asciminib exposure-efficacy and exposure-safety relationships. In patients without the T315I mutation, the exposure-efficacy analysis of the time course of BCR::ABL1IS percentages highlighted the existence of a slightly positive, albeit not clinically significant, relationship. Higher exposure was required for efficacy in patients harboring the T315I mutation compared with those who did not. The exposure-safety relationship analysis showed no apparent association between exposure and adverse events of interest over the broad range of exposure or dose levels investigated. Asciminib has also been shown to have no clinically relevant effect on cardiac repolarization. Here, we review the clinical pharmacology data available to date for asciminib that supported its clinical development program and regulatory applications.

Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase-CYP substrates.

Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug-metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO-mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO-CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating invitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fmAO) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fmi from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fmAO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fmCYP3A4, with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach.

Single-dose and steady-state pharmacokinetics of clomipramine, yohimbine and clomipramine/yohimbine combination: A clinical drug-drug interaction study.

Clomipramine (CLOMI) has shown effectiveness in treating premature ejaculation but is linked to erectile dysfunction and reduced libido. Yohimbine (YOH), by contrast, is effective in treating erectile dysfunction and may improve libido. Combining CLOMI and YOH could potentially leverage the benefits of both drugs. This study aimed to investigate the interactions between these drugs and to evaluate their safety profile. A prospective, open-labelled, single-centre, pharmacokinetic (PK) drug-drug interaction study was performed in 15 healthy male subjects. Single-dose and steady-state PK were investigated using noncompartmental analysis after mono- and combination therapy of the 2 orally applied drugs. Plasma sampling was performed at baseline, 0.5 (YOH), 1, 1.5 (YOH), 2, 3, 4, 5, 6, 8, 12 and 24 h (CLOMI). Differences in the area under the curve after multiple dosing (MD) were determined using an equivalence boundary of 80-125%. The geometric mean ratio of the area under the curve up to 12 h for MD CLOMI (combination vs. monotherapy) was 112% (90% confidence interval: 104-120%), whereas for MD YOH this ratio was 137% (90% confidence interval: 112-168%). The study drugs were safe and well tolerated as mono- and combination therapy, with no major adverse events reported. A PK assessment of clomipramine and yohimbine indicated a clinically significant drug-drug interaction for MD YOH in combination with CLOMI. This might be explained by competitive, CLOMI-related inhibition of YOH metabolism, probably mediated by cytochrome P450 2D6. However, according to European Medicines Agency guidelines, the effect can be classified as interaction absent (<1,25 fold) or minor (>1.25-<2-fold). Given the complimentary mechanisms of action and the favourable safety profiles, the findings pave the way for future efficacy studies.

Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective.

Physiologically-based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In the current work, the ability to predict the effect of rifampin, a well-characterized strong CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models (often developed using a workflow with optimization following a strong inhibitor DDI study to gain confidence in fraction metabolized by CYP3A4, fm,CYP3A4, and fraction available after intestinal metabolism, Fg), was assessed. Substrates with a range of fm,CYP3A4 (0.086-1.0), Fg (0.11-1.0) and hepatic availability (0.09-0.96) were included. Predictions were most often accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for three challenging DDI predictions (i.e., for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, for example, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact (e.g., induction of other enzymes or P-gp) should be considered for inclusion in the model. PBPK modeling was shown to be an effective tool to predict induction DDIs with rifampin for CYP3A substrates with limited mechanistic complications, increasing confidence in the rifampin model. While this analysis focused on rifampin, the learnings may apply to other inducers.

Physiologically based pharmacokinetic modelling to predict potential drug-drug interactions of dersimelagon (MT-7117).

Dersimelagon is a novel, investigational, orally administered, selective agonist of the melanocortin-1 receptor that has demonstrated efficacy at increasing symptom-free light exposure and an acceptable safety profile in patients with protoporphyria. A phase 1 drug-drug interaction (DDI) study demonstrated that dersimelagon 300 mg has the potential for clinically relevant DDIs with drugs that are substrates for breast cancer resistance protein, such as atorvastatin and rosuvastatin. This study uses physiologically based pharmacokinetic (PBPK) modelling to further investigate the DDI effects at lower doses of dersimelagon with substrate drugs. The data from in silico, in vitro and in vivo studies were used to construct a PBPK model for dersimelagon to assess the DDI potential between dersimelagon and substrate drugs for cytochrome P450 3A, P-glycoprotein, organic anion transporting polypeptide 1B1/1B3, organic anion transporter 3 and breast cancer resistance protein, including atorvastatin and rosuvastatin. The systemic exposure of atorvastatin based on the maximum plasma concentration and area under the plasma concentration-time curve was predicted to increase 1.21-fold and 1.25-fold, respectively, if coadministered with dersimelagon 100 mg, and 1.42-fold and 1.45-fold with dersimelagon 200 mg. The systemic exposure of rosuvastatin followed trends similar to atorvastatin (1.67-fold and 1.34-fold increase in maximum plasma concentration and area under the plasma concentration-time curve, respectively, with dersimelagon 100 mg, and 2.40-fold and 1.69-fold with dersimelagon 200 mg). Overall, PBPK modelling results indicate that the simulated changes in plasma exposure of atorvastatin and rosuvastatin following coadministration with dersimelagon 100 or 200 mg are not clinically significant, but caution and appropriate clinical monitoring should be recommended.

Protocol of a drug-drug interaction study between bictegravir/emtricitabine/tenofovir alafenamide and feminizing hormones in trans women living with HIV.

Trans/transfeminine women are disproportionally affected by HIV. Concerns regarding negative drug-drug interactions (DDIs) between ART drugs and gender-affirming hormone therapy (GAHT), specifically feminizing hormone therapy (FHT), may contribute to the lower ART uptake by trans women with HIV compared with their cis counterparts. The aim of this study is to investigate the bidirectional pharmacokinetic effects of components of FHT regimens (oral oestradiol and androgen-suppressing medications) with the ART regimen (bictegravir/emtricitabine/tenofovir alafenamide [B/F/TAF)]. We present a protocol for a three-armed, parallel-group, longitudinal (6-month), DDI study. Group 1 includes 15 3trans women with HIV taking FHT and ART; group 2 includes 15 premenopausal cis women with HIV taking ART; group 3 includes 15 trans women without HIV taking FHT. Women with HIV must be on or switch to B/F/TAF at baseline and be virally suppressed for ≥3months. Trans women must be taking a stable regimen of ≥2mg daily oral oestradiol and an anti-androgen (pharmaceutical, and/or surgical, and/or medical) for ≥3months. Plasma ART drug concentrations will be sampled at Month 2 and compared between groups 1 and 2. Serum oestradiol concentrations will be sampled at baseline and Month 2 visits and compared between groups 1 and 3. The primary outcomes are B/F/TAF pharmacokinetic parameters (Cmin, Cmax and AUC) and oestradiol concentrations (Cmin, C4h, Cmax and AUC) at month 2. This study is of global importance as it provides critical information regarding safe coadministration of B/F/TAF and FHT, both of which are life-saving therapies for trans women with HIV.

The Prevalent New-User Design to Study Drug-Drug Interactions: The Example of Sulfonylureas and Warfarin Interaction on the Risk of Severe Hypoglycemia.

The optimal design for pharmacoepidemiologic drug-drug interactions (DDIs) studies is unclear. Using the association between concomitant use of sulfonylureas and warfarin and the risk of severe hypoglycemia as a case study, a DDI with little or no clinical impact, we tested whether the prevalent new-user design can be applied in the area. Among all patients initiating sulfonylureas in the UK's Clinical Practice Research Datalink (1998-2020), we identified those adding-on warfarin while on a sulfonylurea. For each co-exposed patient, we defined a prescription-based exposure set including other sulfonylurea users not adding-on warfarin (comparators). Within each exposure set, we matched each co-exposed patient to five comparators on time-conditional propensity scores (TCPS) and followed them using an as-treated approach. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of severe hypoglycemia associated with concomitant use of sulfonylureas and warfarin compared to use of sulfonylureas alone. Sensitivity analyses addressed the impact of different potential sources of bias. The study cohort included 17 890 patients co-exposed to sulfonylureas and warfarin and 88 749 matched comparators. After TCPS matching, patient characteristics were well-balanced between groups. Compared to use of sulfonylureas alone, concomitant use of sulfonylureas and warfarin was not associated with the risk of severe hypoglycemia (HR, 1.04; 95% CI, 0.92-1.17). Sensitivity analyses were consistent with the primary analysis (HRs ranging from 1.01 to 1.15, all not statistically significant). Our study suggests that the prevalent new-user design could be used for the assessment of clinical effects of DDIs.

Drug Interactions between Androgen Receptor Axis-Targeted Therapies and Antithrombotic Therapies in Prostate Cancer: Delphi Consensus.

Background/Objectives: Abiraterone acetate, apalutamide, darolutamide, and enzalutamide, which make up the androgen receptor axis-targeted therapies (ARATs) drug class, are commonly used in the management of prostate cancer. Many patients on ARATs also receive oral antithrombotic therapy (i.e., anticoagulants or antiplatelets). The concomitant use of ARATs and antithrombotic therapies creates the potential for clinically relevant drug-drug interactions, but the literature regarding the actual consequences of these interactions, and guidance for co-prescribing, is limited. We assembled a multidisciplinary panel of experts and provided them with clinical information derived from a comprehensive literature review regarding the drug-drug interactions between ARATs and antithrombotic therapies. Methods: A three-stage modified electronic Delphi process was used to gather and consolidate opinions from the panel. Each stage consisted of up to three rounds of voting to achieve consensus on which ARAT/antithrombotic therapy drug pairs warrant attention, the possible clinical consequences of drug-drug interactions, and suggested actions for management. Results: The panel achieved consensus to avoid 11 ARAT/antithrombotic therapy drug pairs and modify therapy for eight pairs. Assessments relied heavily on pharmacokinetic data and extrapolation from drug-drug interaction studies of similarly metabolized drugs. Conclusions: This e-Delphi process highlights the need for further research into the clinical impact of ARAT/antithrombotic drug interactions. Nonetheless, the suggested actions aim to provide clinicians with a practical framework for therapeutic decision making.

Metabolite Measurement in Index Substrate Drug Interaction Studies: A Review of the Literature and Recent New Drug Application Reviews.

Index substrates are used to understand the processes involved in pharmacokinetic (PK) drug-drug interactions (DDIs). The aim of this analysis is to review metabolite measurement in clinical DDI studies, focusing on index substrates for cytochrome P450 (CYP) enzymes, including CYP1A2 (caffeine), CYP2B6 (bupropion), CYP2C8 (repaglinide), CYP2C9 ((S)-warfarin, flurbiprofen), CYP2C19 (omeprazole), CYP2D6 (desipramine, dextromethorphan, nebivolol), and CYP3A (midazolam, triazolam). All data used in this evaluation were obtained from the Certara Drug Interaction Database. Clinical index substrate DDI studies with PK data for at least one metabolite, available from literature and recent new drug application reviews, were reviewed. Further, for positive DDI studies, a correlation analysis was performed between changes in plasma exposure of index substrates and their marker metabolites. A total of 3261 individual index DDI studies were available, with 45% measuring at least one metabolite. The occurrence of metabolite measurement in clinical DDI studies varied widely between index substrates and enzymes. For substrates such as caffeine, bupropion, omeprazole, and dextromethorphan, the use of the metabolite/parent area under the curve ratio can provide greater sensitivity to DDI or reduce intrasubject variability. In some cases (e.g., omeprazole, repaglinide), the inclusion of metabolite measurement can provide mechanistic insights to understand complex interactions.

Drug-drug interactions of icenticaftor (QBW251) with a 5-probe cytochrome P450 cocktail and oral contraceptives.

A drug-drug interaction (DDI) study was conducted to evaluate the effect of icenticaftor (QBW251) on the pharmacokinetics (PK) of a 5-probe cytochrome P450 (CYP) substrate cocktail, guided by invitro studies in human hepatocytes and liver microsomes. Another DDI study investigated the effect of icenticaftor on the PK and pharmacodynamics (PD) of a monophasic oral contraceptive (OC) containing ethinyl estradiol (EE) and levonorgestrel (LVG) in premenopausal healthy female subjects. The static-mechanistic DDI assessment indicated that icenticaftor may moderately induce the metabolic clearance of co-medications metabolized by CYP3A4 (area under the concentration-time curve [AUC] ratio: 0.47) and potentially CYP2C; icenticaftor may also weakly inhibit the metabolic clearance of co-medications metabolized by CYP1A2 and CYP3A4 (AUC ratio: 1.35 and 1.86, respectively) and moderately inhibit CYP2B6 (AUC ratio: 2.11). In the CYP substrate cocktail DDI study, icenticaftor 300 mg twice daily (b.i.d.) moderately inhibited CYP1A2 (AUC ratio: 3.35) and CYP2C19 (AUC ratio: 2.70). As expected from the results of the invitro studies, weak induction was observed for CYP3A4 (AUC ratio: 0.51) and CYP2C8 (AUC ratio: 0.66). In the OC DDI study, co-administration of icenticaftor 450 mg b.i.d. with monophasic OC containing 30-μg EE and 150-μg LVG once daily reduced the plasma exposure of both components by approximately 50% and led to increased levels of follicle-stimulating hormone and luteinizing hormone. These results provide valuable guidance for the use of icenticaftor in patients taking concomitant medications that are substrates of CYP enzymes or patients using OCs.

Value of Assessing 1-Hydroxymidazolam in Drug-Drug Interaction Studies with Midazolam as a Substrate of Cytochrome P450 3A.

The purpose of this overview was to perform an exploratory analysis of in-house drug-drug interaction (DDI) studies conducted with investigational drugs and oral midazolam to assess the value of measuring 1-OH-midazolam (1-OHM) in such studies. The perpetrator effect of the investigational drugs on cytochrome P450 3A (CYP3A) was assessed by analyzing both midazolam and 1-OHM in plasma and evaluating their pharmacokinetic parameters. Given the almost exclusive metabolism of the parent drug by CYP3A to the main metabolite 1-OHM, an increase in midazolam and a decrease in 1-OHM exposure in the case of CYP3A inhibition caused by a perpetrator drug would be expected. The opposite would be anticipated in the case of CYP3A induction. For this analysis, the perpetrator potential of eight different investigational drugs was incorporated. Among the 10 studies included, the identified CYP3A inhibitors (n = 4) and inducers (n = 1) were classified based on the data generated with midazolam per se, with 1-OHM levels not contributing to the interpretation of the data as they did not corroborate the findings of the parent compound. Therefore, it was concluded that continued analysis of 1-OHM in plasma may be questionable as it does not add value to the interpretation of the results when performing CYP3A DDI studies with an investigational drug as a perpetrator.

A phase I drug-drug interaction study to assess the effect of futibatinib on P-gp and BCRP substrates and of P-gp inhibition on the pharmacokinetics of futibatinib.

Futibatinib, an inhibitor of fibroblast growth factor receptor 1-4, is approved for the treatment of patients with advanced cholangiocarcinoma with FGFR2 fusions/rearrangements. In this phase I drug-drug interaction study, the effects of futibatinib on P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) substrates, and of P-gp inhibition on futibatinib pharmacokinetics (PK) were investigated in healthy adults aged 18-55 years. In part 1, 20 participants received digoxin (P-gp substrate) and rosuvastatin (BCRP substrate). Following a ≥10-day washout, futibatinib was administered for 7 days, with digoxin and rosuvastatin coadministered on the third day. In part 2, 24 participants received futibatinib. Following a ≥3-day washout, quinidine (P-gp inhibitor) was administered for 4 days, with futibatinib coadministered on day 4. Blood samples were collected predose and for 24 (futibatinib), 72 (rosuvastatin), and 120 h (digoxin) postdose. Urine samples (digoxin) were collected predose and for 120 h postdose. PK parameters were compared between treatments using analysis of variance. Coadministration with futibatinib had no effect on the PK of digoxin and rosuvastatin, and coadministration with quinidine had minimal effects on the PK of futibatinib. Differences in Cmax and AUC with and without futibatinib and quinidine, respectively, were <20%. The most common treatment-emergent adverse events were diarrhea (80%) and increased blood phosphorous (75%) in part 1 and prolonged electrocardiogram QT interval (38%) in part 2. The data show that futibatinib has no clinically meaningful effects on the PK of P-gp or BCRP substrates and that the effect of P-gp inhibition on futibatinib PK is not clinically relevant.

Inhibition of P-Glycoprotein Asymmetrically Alters the In Vivo Exposure Profile of SGC003F: A Novel Guanylate Cyclase Stimulator.

As a novel guanylate cyclase stimulator, SGC003F is being developed for the treatment of heart failure with a reduced ejection fraction (HFrEF). This study aimed to assess the effect of P-glycoprotein (P-gp) inhibition on SGC003F exposure in vivo, comparing plasma and tissue levels, and evaluating the role of P-gp in the small intestine, blood-brain barrier (BBB), and kidney in impacting the tissue exposure. Tariquidar, a P-gp inhibitor, was added to monolayer transport assays to observe the changes in the transmembrane characteristics of SGC003F. Rats were given SGC003F with tariquidar via various routes to measure plasma, tissue, urine, and fecal concentrations. The inclusion of tariquidar significantly altered the pharmacokinetics of SGC003F. In LLC-PK1-MDR1 cells, tariquidar reduced the efflux ratio of SGC003F from 6.56 to 1.28. In rats, it enhanced the plasma AUC by 3.05 or 1.61 times, increased the Cmax by 2.13 or 1.07 times, and notably improved bioavailability from 46.4% to 95%. Additionally, co-administration with tariquidar led to a decrease in fecal excretion and an increase in tissue exposure, with only a moderate effect on the partition ratios in the small intestine and brain. P-gp inhibition impacts SGC003F exposure, with plasma levels not fully reflecting tissue levels. P-gp in the small intestine and BBB affects SGC003F's pharmacokinetics, warranting further clinical drug-drug interaction (DDI) studies.