Pharmacokinetic Drug-drug Interactions Research Articles

Pharmacokinetic Drug-Drug Interaction between Cilostazol and Rosuvastatin in Healthy Participants.

Cilostazol improves ischemic symptoms and prevents recurrence following cerebral infarction, and rosuvastatin reduces cholesterol levels. However, no reports exist on the pharmacokinetic interactions between these two drugs in healthy adults. This study evaluated the pharmacokinetic (PK) interactions and safety of cilostazol and rosuvastatin when co-administered to healthy male participants. A randomized, open-label, multiple-dosing, two-arm, two-period study was conducted. Arm A had 30 participants receiving 200 mg cilostazol daily and arm B had 27 participants receiving 20 mg rosuvastatin daily for 7 days. In period 2, both arms received a combination of 200 mg cilostazol and 20 mg rosuvastatin daily for 7 days following a 7-day washout period. Plasma concentrations of cilostazol, its metabolites, and rosuvastatin were quantified using liquid chromatography-tandem mass spectrometry. Fifty-seven participants were randomized, and 44 completed the study. The geometric mean ratio (GMR) and 90% confidence intervals (CI) for maximum plasma concentration at steady state (Cmax,ss) and area under the plasma concentration-time curve during the dosing interval at steady state (AUCtau,ss) indicated no significant interaction between cilostazol and rosuvastatin. Safety assessments showed comparable profiles to individual drug administration, with no significant adverse events. The repeated co-administration of cilostazol and rosuvastatin in healthy male participants resulted in minor PK interactions and exhibited a safety and tolerability profile similar to those of the individual drugs. This suggested that the combined regimen is well tolerated and does not necessitate dose adjustments. ClinicalTrials.Gov identifier no. NCT06568133.

Pharmacokinetic drug-drug interaction between first-line anti-TB and anti-diabetic drugs in patients with tuberculosis and diabetes mellitus

Pharmacokinetic drug-drug interaction between first-line anti-TB and anti-diabetic drugs in patients with tuberculosis and diabetes mellitus

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.

Prediction of Pharmacokinetic Drug-Drug Interactions Involving Anlotinib as a Victim by Using Physiologically Based Pharmacokinetic Modeling.

Anlotinib was approved as a third line therapy for advanced non-small cell lung cancer in China. However, the impact of concurrent administration of various clinical drugs on the drug-drug interaction (DDI) potential of anlotinib remains undetermined. As such, this study aims to evaluate the DDI of anlotinib as a victim by establishing a physiologically based pharmacokinetic (PBPK) model. The PBPK model of anlotinib as a victim drug was constructed and validated in the Simcyp® incorporating parameters derived from in vitro studies, pre-clinical investigations, and clinical research encompassing patients with cancer. Subsequently, plasma exposure of anlotinib in cancer patients was predicted for single- and multi-dose co-administration with typical perpetrators mentioned in Food and Drug Administration (FDA) industrial guidance. Based on predictions, the CYP3A potent inhibitor ketoconazole demonstrated the most significant DDI with anlotinib, regardless of whether anlotinib is administered as a single dose or multiple doses. Ketoconazole increased the area under the concentration-time curve (AUC) and maximum concentration (Cmax) of single-dose anlotinib to 1.41-fold and 1.08-fold, respectively. In contrast, rifampicin, a potent inducer of CYP3A enzymes, exhibited a relatively higher level of DDI, with AUCR and CmaxR values of 0.44 and 0.79, respectively. Based on the PBPK modeling, there is a low risk of DDI between anlotinib and potent CYP3A/1A2 inhibitors, but caution and enhanced monitoring for adverse reactions are advised. To mitigate the risk of anti-tumor treatment failure, it is recommended to avoid concurrent use of strong CYP3A inducers. In conclusion, our study enhances understanding of anlotinib's interaction with medications, aiding scientists, prescribers, and drug labels in gauging the expected impact of CYP3A/1A2 modulators on anlotinib's pharmacokinetics.

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.

Physiologically based pharmacokinetic models for predicting lamotrigine exposure and dose optimization in pediatric patients receiving combination therapy with carbamazepine or valproic acid.

Lamotrigine (LTG) is an antiepileptic drug that has been used in pediatric epilepsy as a combination therapy or monotherapy after stabilization in recent years. However, there are significant drug-drug interactions (DDI) between LTG and combined drugs such as carbamazepine (CBZ) and valproic acid (VPA). It is particularly important to consider the risk of DDI in combination therapy for intractable epilepsy in pediatric patients. Therefore, it is necessary to adjust the dosage of LTG accordingly. The aim of this study was to establish and validate a pediatric physiologically based pharmacokinetic (PBPK) model for predicting LTG exposure. The model is designed to explore the potential for quantifying pharmacokinetic (PK) DDI of LTG when administered concurrently with CBZ or VPA in pediatric patients. Adult and pediatric PBPK models for LTG and VPA were developed using PK-Sim® software in combination with physiological information and drug-specific parameters, and a DDI model was developed in combination with the published CBZ model. The models were validated against available PK data. Predictive and observational results in adults, children, and the DDI model were in good agreement. The recommended doses of LTG for preschool children (2-6 years) and school-aged children (6-12 years) in the absence of drug interactions were 1.47 and 1.2 times higher than those for adults, respectively; 3.1 and 2.6 times higher than those for adults in combination with CBZ; and 0.67 and 0.57 times lower than those for adults in combination with VPA. In addition, plasma exposures in adolescents (12-18 years) were similar to those in adults at the same doses. We have successfully developed PBPK models and DDI models for LTG in adults and children, which provide a reference for rational drug use in the pediatric population.

Efficacy of ivermectin and its metabolites against Plasmodium falciparum liver stages in primary human hepatocytes.

Ivermectin, a broad-spectrum anti-parasitic drug, has been proposed as a novel vector control tool to reduce malaria transmission by mass drug administration. Ivermectin and some metabolites have mosquito-lethal effect, reducing Anopheles mosquito survival. Ivermectin inhibits liver stage development in a rodent malaria model, but no inhibition was observed in a primate malaria model or in a human malaria challenge trial. In the liver, cytochrome P450 3A4 and 3A5 enzymes metabolize ivermectin, which may impact drug efficacy. Thus, understanding ivermectin metabolism and assessing this impact on Plasmodium liver stage development is critical. Using primary human hepatocytes (PHHs), we characterized ivermectin metabolism and evaluated the efficacy of ivermectin and its primary metabolites M1 (3″-O-demethyl ivermectin) and M3 (4-hydroxymethyl ivermectin) against Plasmodium falciparum liver stages. Two different modes of ivermectin exposure were evaluated: prophylactic mode (days 0-3 post-infection) and curative mode (days 3-5 post-infection). We used two different PHH donors and modes to determine the inhibitory concentration (IC50) of ivermectin, M1, M3, and the known anti-malarial drug pyrimethamine, with IC50 values ranging from 1.391 to 14.44, 9.95-23.71, 4.767-8.384, and 0.9073-5.416 µM, respectively. In our PHH model, ivermectin and metabolites M1 and M3 demonstrated inhibitory activity against P. falciparum liver stages in curative treatment mode (days 3-5) and marginal activity in prophylactic treatment mode (days 0-3). Ivermectin had improved efficacy when co-administered with ketoconazole, a specific inhibitor of cytochrome P450 3A4 enzyme. Further studies should be performed to examine ivermectin liver stage efficacy when co-administered with CYP3A4 inhibitors and anti-malarial drugs to understand the pharmacokinetic and pharmacodynamic drug-drug interactions that enhance efficacy against human malaria parasites in vitro.

Carboxylesterase 1-Based Drug-Drug Interaction Potential of Remimazolam: In-Vitro Studies and Literature Review.

The ultra-short-acting benzodiazepine remimazolam, approved for procedural sedation and general anesthesia, is inactivated by carboxylesterase 1 (CES1). Remimazolam´s involvement in CES1-mediated drug-drug interactions (DDIs) was investigated. Possible interactions of remimazolam were studied in co-exposure experiments with eleven different drugs. Further, substrates and inhibitors of CES1, identified in the literature, were evaluated for possible in-vivo inhibition using pharmacokinetic and Ki or IC50 values. Compounds with only one published inhibitory concentration and CES1 substrates lacking inhibition data were assigned conservative Ki values. In human liver homogenates and/or blood cells, remimazolam showed no significant inhibition of esmolol and landiolol metabolism, which, in turn, at up to 98 and 169 μM, respectively, did not inhibit remimazolam hydrolysis by human liver homogenates. In human liver S9 fractions, IC50 values ranged from 0.69 μM (simvastatin) and 57 μM (diltiazem) to > 100 μM (atorvastatin) and, for the remaining test items (bupropion, carvedilol, nelfinavir, nitrendipine, and telmisartan), they ranged from 126 to 658 μM. Remifentanil was ineffective even at 1250 μM. Guidance-conforming evaluation revealed no relevant drug-drug interactions with remimazolam via CES1. The algorithm-based predictions were consistent with human study data. Among CES1 inhibitors and substrates identified in the literature, only dapsone and rufinamide were found to be possible in-vivo inhibitors of remimazolam metabolism. Data and analyses suggest a very low potential of remimazolam for pharmacokinetic DDIs mediated by CES1. The theoretical approach and compiled data are not specific to remimazolam and, hence, applicable in the evaluation of other CES1 substrates.

Clinical Trial Data-Driven Risk Assessment of Drug-Drug Interactions: A Rapid and Accurate Decision-Making Tool.

In clinical practice, the vast array of potential drug combinations necessitates swift and accurate assessments of pharmacokinetic drug-drug interactions (DDIs), along with recommendations for adjustments. Current methodologies for clinical DDI evaluations primarily rely on basic extrapolations from clinical trial data. However, these methods are limited in accuracy owing to their lack of a comprehensive consideration of various critical factors, including the inhibitory potency, dosage, and type of the inhibitor, as well as the metabolic fraction and intestinal availability of the substrate. This study aims to propose an efficient and accurate clinical pharmacokinetic-mediated DDI assessment tool, which comprehensively considers the effects of inhibitory potency and dosage of inhibitors, intestinal availability and fraction metabolized of substrates on DDI outcomes. This study focuses on DDIs caused by cytochrome P450 3A4 enzyme inhibition, utilizing extensive clinical trial data to establish a methodology to calculate the metabolic fraction and intestinal availability for substrates, as well as the concentration and inhibitory potency for inhibitors ( or ). These parameters were then used to predict the outcomes of DDIs involving 33 substrates and 20 inhibitors. We also defined the risk index for substrates and the potency index for inhibitors to establish a clinical DDI risk scale. The training set for parameter calculation consisted of 73 clinical trials. The validation set comprised 89 clinical DDI trials involving 53 drugs. which was used to evaluate the reliability of in vivo values of and , the accuracy of DDI predictions, and the false-negative rate of risk scale. First, the reliability of the in vivo and values calculated in this study was assessed using a basic static model. Compared with values obtained from other methods, this study values showed a lower geometric mean fold error and root mean square error. Additionally, incorporating these values into the physiologically based pharmacokinetic-DDI model facilitated a good fitting of the C-t curves when the substrate's metabolic enzymes are inhibited. Second, area under the curve ratio predictions of studied drugs were within a 1.5× margin of error in 81% of cases compared with clinical observations in the validation set. Last, the clinical DDI risk scale developed in this study predicted the actual risks in the validation set with only a 5.6% incidence of serious false negatives. This study offers a rapid and accurate approach for assessing the risk of pharmacokinetic-mediated DDIs in clinical practice, providing a foundation for rational combination drug use and dosage adjustments.

A phase I safety and efficacy clinical trial of plocabulin and gemcitabine in patients with advanced solid tumors.

Plocabulin (Plo) induces depolymerization of tubulin fibers with disorganization and fragmentation of the microtubule network leading to mitosis. Plo combined with gemcitabine (Gem) showed synergistic anti-tumor activity in preclinical studies.This phase I trial evaluated the safety, pharmacokinetics (PK) and efficacy of Plo 10-min infusion plus Gem on Day 1 and 8 every 3-week in patients with advanced solid tumors.Fifty-seven patients were enrolled into 8 dose levels (DLs); 74%: females; 74%: ECOG performance status 1; median age: 62years; median number of prior lines of therapy:3. Dose-limiting toxicities (DLT) in Cycle 1 were grade (G) 3 intestinal obstruction at the maximum tolerated dose (MTD), G3 peripheral sensory neuropathy (PSN), G3 abdominal pain, and G4 thrombocytopenia (1 patient each). The highest DL (DL8: Plo 10.5mg/m2/Gem 1000mg/m2) was the MTD. Accrual into DL7 (Plo 10.0mg/m2/Gem 1000mg/m2) was stopped before it was formally defined as the recommended dose (RD). Most common treatment-related adverse events (AEs) were fatigue (56%), nausea (55%), diarrhea (31%); G3/4 hematologic toxicities comprised anemia (35%), neutropenia (27%) and thrombocytopenia (17%). No treatment-related deaths occurred. PK parameters for Gem or dFdU at all DLs were in line with reference values from the literature. Six of 46 evaluable pts were responders (overall response rate:13%). Of note, 2 partial responses (PR) and 2 stable disease (SD) ≥ 4months occurred among 13 pts with ovarian cancer.The combination of Plo and Gem is well tolerated. The MTD was Plo 10.5mg/m2/Gem 1000mg/m2. No PK drug-drug interaction was found. The most encouraging outcome occurred in ovarian cancer patients.

Pharmacokinetic drug-drug interactions: a detailed systematic review

Pharmacokinetic drug-drug interactions: a detailed systematic review

Pharmacokinetic drug-drug interactions of JBPOS0101 mediated by cytochrome P450 3A4 and UDP-glucuronosyltransferases.

JBPOS0101 is a new antiepileptic drug and is a substrate of UDP-glucuronosyltransferases (UGTs) in invitro test. Invitro experiments showed different results regarding whether JBPOS0101 induces (EC50 136 μM) or inhibits (IC50 95.4-386.5 μM) cytochrome P450 (CYP) 3A4. As co-medication of JBPOS0101 and carbamazepine (CBZ) is expected in clinical settings, drug-drug interactions (DDIs) between them should be determined. This study aimed to investigate pharmacokinetic (PK) interactions of JBPOS0101 influenced by CYP3A4 and UGTs using midazolam (MDZ) and CBZ. A two-cohort, open-label, fixed-sequence study was conducted in healthy Koreans. In cohort A, subjects received MDZ IV alone, and then JBPOS0101 were co-administered with MDZ after oral doses of JBPOS0101 for 7 days. In cohort B, multiple doses of JBPOS0101 and CBZ were administered respectively, and subjects received both together for 7 days. Serial blood samples were collected for PK analysis. When MDZ and JBPOS0101 were co-administered, the systemic exposure of MDZ decreased by 30%. Meanwhile, JBPOS0101 did not significantly changed the PK of CBZ. CBZ decreased the systemic exposure of JBPOS0101 at steady state by 40%, respectively. With IV administration of MDZ, JBPOS0101 acted as a weak inducer of hepatic CYP3A4 and decreased systemic exposure of MDZ. The ability of JBPOS0101 to similarly modulate gut CYP3A4 activity will require further evaluation. Co-administration of multiple doses of JBPOS0101 and CBZ did not significantly alter CBZ pharmacokinetics, but the clinical impact of decreased systemic exposure of JBPOS0101 by CBZ should be further considered.

A sub-pharmacological test dose does not predict individual docetaxel exposure in prostate cancer patients.

Docetaxel is a cytotoxic drug used for first-line treatment of various malignancies. It has a narrow therapeutic index and shows wide interpatient variability in clearance and toxicity. Tools for individual dose optimization are needed to maximize efficacy and avoid toxicity. We performed a proof-of-concept study (EudraCT 2016-003785-77) to evaluate whether pharmacokinetics after a sub-pharmacological test dose of 1000µg docetaxel (millidose) could be used to predict therapeutic dose exposure. Thirty prostate cancer patients eligible for treatment with docetaxel as part of routine clinical care were included. An intravenous docetaxel millidose was administered 1-7 days prior to therapeutic docetaxel. After both doses plasma docetaxel concentrations were measured by ultra- high performance liquid chromatography-tandem mass spectrometry. The docetaxel clearance was estimated with non-linear mixed effects modeling. Geometric mean docetaxel clearance was 57.9L/h (GCV 78.6%) after admission of a millidose and 40.3L/h (GCV 60.7%) after admission of a therapeutic dose. The millidose and therapeutic dose in a single patient were not significantly correlated (Spearman's rho R = 0.02, P = 0.92). Docetaxel pharmacokinetics at milli- and therapeutic dose level showed insufficient correlation for individual dose optimization. However, the clearance of a docetaxel millidose and full dose are within the same order of magnitude. Therefore, docetaxel millidose pharmacokinetics could potentially facilitate prediction of docetaxel pharmacokinetics at a population level in situations where therapeutic dose levels are impractical, such as pharmacokinetic drug-drug interaction studies or pediatric studies.

THU-174 Assessment of the pharmacokinetic drug-drug interaction potential of elafibranor with atorvastatin in healthy adult male participants: an open-label phase I trial

THU-174 Assessment of the pharmacokinetic drug-drug interaction potential of elafibranor with atorvastatin in healthy adult male participants: an open-label phase I trial

Clinically important pharmacokinetic drug-drug interactions with antibacterial agents.

Antimicrobial agents are widely used, and drug interactions are challenging due to increased risk of adverse effects or reduced efficacy. Among the interactions, the most important are those affecting metabolism, although those involving drug transporters are becoming increasingly known. To make clinical decisions, it is key to know the intensity of the interaction, as well as its duration and time-dependent recovery after discontinuation of the causative agents. It is not only important to be aware of all patient treatments, but also of supplements and natural medications that may also interact. Although they can have serious consequences, most interactions can be adequately managed with a good understanding of them. Especially in patients with polipharmacy it is compulsory to check them with an electronic clinical decision support database. This article aims to conduct a narrative review focusing on the major clinically significant pharmacokinetic drug-drug interactions that can be seen in patients receiving treatment for bacterial infections.

Human Pharmacokinetic and CYP3A Drug-Drug Interaction Prediction of GDC-2394 Using Physiologically Based Pharmacokinetic Modeling and Biomarker Assessment.

Physiologically based pharmacokinetic (PBPK) modeling was used to predict the human pharmacokinetics and drug-drug interaction (DDI) of GDC-2394. PBPK models were developed using in vitro and in vivo data to reflect the oral and intravenous PK profiles of mouse, rat, dog, and monkey. The learnings from preclinical PBPK models were applied to a human PBPK model for prospective human PK predictions. The prospective human PK predictions were within 3-fold of the clinical data from the first-in-human study, which was used to optimize and validate the PBPK model and subsequently used for DDI prediction. Based on the majority of PBPK modeling scenarios using the in vitro CYP3A induction data (mRNA and activity), GDC-2394 was predicted to have no-to-weak induction potential at 900 mg twice daily (BID). Calibration of the induction mRNA and activity data allowed for the convergence of DDI predictions to a narrower range. The plasma concentrations of the 4β-hydroxycholesterol (4β-HC) were measured in the multiple ascending dose study to assess the hepatic CYP3A induction risk. There was no change in plasma 4β-HC concentrations after 7 days of GDC-2394 at 900 mg BID. A dedicated DDI study found that GDC-2394 has no induction effect on midazolam in humans, which was reflected by the totality of predicted DDI scenarios. This work demonstrates the prospective utilization of PBPK for human PK and DDI prediction in early drug development of GDC-2394. PBPK modeling accompanied with CYP3A biomarkers can serve as a strategy to support clinical pharmacology development plans. SIGNIFICANCE STATEMENT: This work presents the application of physiologically based pharmacokinetic modeling for prospective human pharmacokinetic (PK) and drug-drug interaction (DDI) prediction in early drug development. The strategy taken in this report represents a framework to incorporate various approaches including calibration of in vitro induction data and consideration of CYP3A biomarkers to inform on the overall CYP3A-related DDI risk of GDC-2394.

Antiviral Use in Mild-to-Moderate SARS-CoV-2 Infections during the Omicron Wave in Geriatric Patients.

(1) Background: Geriatric patients are at high risk of complications of Coronavirus disease-2019 (COVID-19) and are good candidates for antiviral drugs. (2) Methods: A retrospective study of electronic health records (EHRs) aiming to describe antiviral (nirmatrelvir and ritonavir (nirmatrelvir/r) or remdesivir) use, drug-drug interactions (DDIs) and adverse drug reactions (ADRs) in elderly patients (75 and over), hospitalized with mild-to-moderate COVID-19 between July 2022 and June 2023. (3) Results: Out of 491 patients (mean age: 86.9 years), 180 (36.7%) received nirmatrelvir/r, 78 (15.9%) received remdesivir, and 233 (47.4%) received no antiviral therapy. No association was found between the choice of antiviral and the demographic or medical data. No serious ADR was observed. Nirmatrelvir/r dosage adjustment was inadequate in 65% of patients with renal impairment. In total, 128 patients (71%) on nirmatrelvir/r had potential pharmacokinetic DDIs, with 43 resulting in a possibly related ADR. In the remdesivir group, pharmacodynamic DDIs were more frequent, with QTc prolongation risk in 56 patients (72%). Only 20 patients underwent follow-up ECG, revealing QTc prolongation in 4. (4) Conclusions: There is an underutilization of antivirals despite their justified indications. Nirmatrelvir/r dosage was rarely adjusted to renal function. Dose adjustments and closer monitoring are needed due to the high risk of drug interactions.

Pharmacokinetics and pharmacodynamics of drug‒drug interactions in hospitalized older adults treated with direct oral anticoagulants.

Polypharmacy is a frequent situation in older adults that increases the risk of drug-drug interactions (DDIs), both pharmacokinetic (PK) and pharmacodynamic (PD). Direct oral anticoagulants (DOACs) are frequently prescribed in older adults, mainly because of the high prevalence of atrial fibrillation (AF). DOACs are subject to cytochrome P450 3A4 (CYP3A4)- and/or P-glycoprotein (P-gp)-mediated PK DDIs and PD DDIs when co-administered with drugs that interfere with platelet function. The aim of our study was to assess the prevalence of DDIs involving DOACs in older adults and the associated risk factors at admission and discharge. This was a cross-sectional study conducted in an acute geriatric unit between January 1, 2018 and December 31, 2022, including patients over 75 years of age treated with DOACs at admission and/or discharge, for whom a comprehensive collection of co-medications was performed. From 909 hospitalizations collected, the prevalence of PK DDIs involving DOACs was 16.9% at admission and 20.7% at discharge, and the prevalence of PD DDIs was 20.7% at admission and 20.2% at discharge. Factors associated with DDIs were bleeding history [adjusted odds ratio (ORa) 1.74, 95% confidence interval (CI) 1.13-2.68], number of drugs > 6 (ORa 2.54, 95% CI 1.88-3.46) and reduced dose of DOACs (ORa 0.39, 95% CI 0.28-0.54) at admission and age > 87 years (ORa 0.74, 95% CI 0.55-0.99), number of drugs > 6 (ORa 2.01, 95% CI 1.48-2.72) and reduced dose of DOACs (ORa 0.41, 95% CI 0.30-0.57) at discharge. This study provides an indication of the prevalence of DDIs as well as the profile of DDIs and patients treated with DOACs.

Risk of Enzyme- and Transporter-mediated Drug Interactions With Drugs Approved by the US Food and Drug Administration in 2022: A Detailed Analysis of In Vitro and Clinical Data Available in New Drug Application Reviews

PurposeThis analysis aimed to provide mechanistic understanding and clinical relevance of pharmacokinetic drug-drug interactions (DDIs) associated with drugs approved by the Food and Drug Administration in 2022. MethodsDrug metabolism, transport, and DDI data available in New Drug Applications (NDAs) of small molecular drugs approved (n = 22) was analyzed. The mechanism and clinical magnitude of these interactions were characterized based on in vitro, in silico, and clinical data. FindingsAs victims, 10 drugs were identified as clinical substrates. Of these, 7 drugs were substrates of CYP3A, including the sensitive substrates daridorexant and mitapivat. As perpetrators, 3 drugs (adagrasib, lenacapavir, and vonoprazan) were clinical inhibitors of CYP enzymes, and 2 drugs (mavacamten and mitapivat) showed induction. Regarding transporter data, abrocitinib and deucravacitinib were found to be substrates of OAT3 and P-gp/BCRP, respectively, and 4 drugs (abrocitinib, adagrasib, lenacapavir, and oteseconazole) were found to inhibit P-gp and/or BCRP. As expected, all clinical DDIs with AUC changes ≥ 2-fold triggered label recommendations. Over half of DDIs with an AUC change < 2 also had label recommendations, pertaining most often to the concomitant use of drugs with a narrow therapeutic index. Overall, CYP3A played a major role in the drug disposition of the drugs approved in 2022, mediating all strong drug interactions. ImplicationsThe mechanistic information obtained from studying these new therapeutics with marker compounds can be extrapolated to common concomitant medications sharing the same pharmacokinetic properties, enhancing the safe and effective administration of these products in situations of polytherapy.

Zibotentan Can Be Co-administered with Contraceptives Containing Ethinyl Estradiol and Levonorgestrel: A Pharmacokinetic Drug-Drug Interaction Study.

The endothelin A receptor antagonist zibotentan, combined with the sodium-glucose co-transporter-2 inhibitor dapagliflozin, is being investigated for the treatment of chronic kidney disease with high proteinuria. To allow women of childbearing potential access to this treatment, highly effective contraception is required and drug interactions compromising contraception reliability must be avoided. This study investigated the risk of pharmacokinetic (PK) interaction between zibotentan and the contraceptives ethinyl estradiol and levonorgestrel. A single-sequence, within-participant comparison study was conducted in 24 healthy women of non-childbearing potential, comparing the PK of ethinyl estradiol/levonorgestrel alone and with zibotentan. Single oral doses of 0.06 mg ethinyl estradiol/0.3 mg levonorgestrel were administered on Days 1 and 15; zibotentan 10 mg was dosed orally, once-daily through Days 6-19. PK profiles were determined and ethinyl estradiol/levonorgestrel PK was compared between Day 1 and 15 based on geometric least-squares mean ratios of PK parameters, including maximum observed concentration (Cmax) and area under the plasma concentration-time curve from zero to infinity (AUCinf). Co-administration with zibotentan did not affect ethinyl estradiol PK (geometric mean ratio [90% confidence interval] Cmax 1.05 [0.99-1.11], AUCinf 1.00 [0.96-1.05]), while a weak interaction (increased exposure) was observed for levonorgestrel (Cmax 1.12 [1.02-1.23], AUCinf 1.30 [1.21-1.39]), which was regarded as without clinical relevance. Plasma exposure of ethinyl estradiol/levonorgestrel was not reduced by multiple-dose zibotentan. In conclusion, contraception containing ethinyl estradiol/levonorgestrel is regarded possible under zibotentan-containing treatments. This expands choices for women of childbearing potential, supporting diversity in the ZENITH High Proteinuria trial.