Pharmacodynamic Drug-drug Interactions Research Articles

Influence of remifentanil on the pharmacokinetics and pharmacodynamics of remimazolam in healthy volunteers

Background: Synergistic effects between opioids and remimazolam on bispectral index (BIS) and modified observer’s assessment of alertness and/or sedation (MOAAS) score were previously described. This study aimed to characterize the influence of remifentanil on the sedative properties of remimazolam as measured by MOAAS, BIS, tolerance to laryngoscopy or tetanic stimulation (TOL or TOTS) and to determine target concentrations that maximize MOAAS 2/3. Methods: A three-period, cross-over, dose-ranging clinical trial was performed in 24 healthy volunteers. In all periods, remimazolam was administered using a step-up and step-down TCI protocol (50 – 2000 ng/mL). Stable remifentanil target concentrations of 0.5 ng/mL and 0.1 to 4.0 ng/mL were maintained in periods 2 and 3, respectively. Remifentanil, remimazolam and CNS7054 (metabolite) concentrations and, MOAAS, BIS, TOL and TOTS were collected in each step of the TCI protocol. Data were analyzed using non-linear mixed-effects models, where p≤0.01 was considered significant. Results: Remifentanil reduced the apparent clearance of CNS7054 with a half-maximum inhibition at 8.0 ng/mL (95% CI 5.5 to 13.4 ng/mL). A pharmacodynamic interaction was detected on all endpoints. Simulations indicate that the probability of observing a MOAAS 2/3 is highest at remimazolam target concentration of 275, 250 or 200 ng/mL combined with 0, 0.1, or 0.5 ng/mL remifentanil resulting in probabilities of 45%, 45% and 44%, respectively. Additionally, simulations indicate that the highest probability of observing TOTS and TOL was 93.3% and 85.5%, respectively, at the highest studied target concentrations. Conclusions: A pharmacokinetic and pharmacodynamic drug-drug interaction between remimazolam and remifentanil was quantified in this clinical trial. Appropriate target concentrations for MOAAS and BIS could be estimated, but, for TOL and TOTS, the trial design did not allow to fully characterize the exposure-response relationship.

Drug-drug interactions in critically ill patients

Critically ill patients are at high risk of adverse drug-drug interactions. Pharmacodynamic drug-drug interaction may cause organ damage. Pharmacokinetic interactions are usually caused by inhibition or induction of enzymes of drug metabolism such as cytochromeP-450 isoenzymes or transporter proteins such as P‑glycoprotein. Inhibitors of such molecules can cause toxic levels of the corresponding substrates, while inducers might produce subtherapeutic concentrations. Amiodarone, macrolides, antifungal azoles, direct-acting anticoagulants, vitaminK antagonists, immunosuppressants, rifampicin, and some central nervous system (CNS)-active substances are frequently involved in drug-drug interactions. Sound risk and benefit assessment of the applied medication, therapeutic drug monitoring, the use of electronic alert systems and databases along with clinical evaluation will contribute to avoiding adverse drug-drug interactions.

Cholinesterase Inhibitor Initiation Does Not Increase the Risk of Fall-Related Injury in Older Adults Treated With Beta-Blockers: A Self-Controlled Case Series Design.

Prescribing cholinesterase inhibitors (ChEIs) concurrently with beta-blockers might cause syncope that increases the risk of fall-related injuries (FRIs). This self-controlled case series study assesses the risk of FRIs associated with initiating ChEIs while receiving beta-blockers among Medicare fee-for-service-insured nursing home (NH) residents in the United States. We identified individuals at their first dispensing of a beta-blocker between 2016 and 2019 after at least 45 days of long-stay NH residency. Individuals were followed from the first day of beta-blocker use until beta-blocker discontinuation, Medicare disenrollment, death, or study end. ChEI initiation was classified as the first 60 days of new ChEI dispensing after 45 days of no ChEI exposure. FRIs were assessed during beta-blocker use periods, and age-adjusted incidence rate ratios (IRR) for ChEI-initiation days versus other days were calculated using conditional Poisson regression models. Analyses were weighted for event-dependent observation periods due to the high risk of mortality after an FRI in this population. Subgroup analyses were conducted for several key time-fixed variables, including sex, age, ChEI type, ChEI dose, beta-blocker selectivity, and beta-blocker dose. The FRI risk after ChEI initiation was not elevated among 837 residents who experienced an FRI while using beta-blockers (IRR=0.90 [95%CLs 0.71, 1.15]). Analyses of ChEI initiation in several subgroups yielded similar results. There was no substantial difference in FRI risk when initiating ChEIs among older NH residents receiving beta-blocker therapy versus periods without ChEI initiation, suggesting that there is no clinically significant pharmacodynamic drug-drug interaction between beta-blockers and ChEIs.

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.

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.

Detection and management of clinically relevant drug-drug interactions with direct oral anticoagulants: an intervention study in community pharmacies

IntroductionDirect oral anticoagulants (DOACs) are increasingly used and can be involved in clinically relevant drug-drug interactions (DDIs) that increase the risk of major bleeding or thromboembolism. Skilled drug interaction management is essential to ensure safe and effective use of DOACs. In this study, we aimed to investigate the impact of the detection and management of DDIs with DOACs in a real-life community pharmacy setting on the pharmacotherapy of DOAC users. MethodsWe conducted an intervention study in 201 community pharmacies in Belgium. On random days, patients purchasing DOACs or drugs known to interact with them were screened. When a DDI with the DOAC was detected, the pharmacist contacted the prescribing physician to discuss the management of the interaction. A previously developed practice-oriented DDI list accompanied by management plans for ambulatory care was used for both screening and management of the DDIs. ResultsIn total, 751 patients were included, among whom 875 DDIs were identified, primarily pharmacodynamic DDIs (95.7 %). Predominant interacting drug classes included selective serotonin or serotonin and norepinephrine reuptake inhibitors (32.9 %), antiplatelets (30.9 %), and non-steroidal anti-inflammatory drugs (28.9 %). In 43.0 % of DDIs, an intervention was decided upon. At three-month follow-up, proposed pharmacotherapy changes had been implemented in 79.1 % of these DDIs. ConclusionsThis study demonstrates that active screening and management of DDIs with DOACs in community pharmacies, in close collaboration with prescribing physicians, resulted in changes in pharmacotherapy in a substantial number of patients. This may contribute significantly to the safer utilisation of DOACs in high-risk populations.

A comprehensive review on potential drug-drug interactions of proton pump inhibitors with antidiabetic drugs metformin and DPP-4 inhibitors.

A drug interaction is a condition in which two or more drugs are taken at the same time. Type 2 diabetes mellitusis a significant contributor to polypharmacy. Proton pump inhibitors (PPIs) are often prescribed in combination with metformin or DPP-4 inhibitors (sitagliptin, saxagliptin, linagliptin, and alogliptin) or a combined dose of metformin and DPP-4 inhibitor to treat gastritis in diabetic patients. This review article mainly focused on evaluating the potential drug-drug interactions (DDIs) between PPIs (i.e. esomeprazole, lansoprazole, omeprazole, pantoprazole, and rabeprazole) with metformin and PPIs with DPP-4 inhibitors. The findings demonstrated the existence of pharmacokinetic and pharmacodynamic DDIs between the aforementioned PPIs with metformin and DPP-4 inhibitors, which could impact the biological activities (i.e., hypoglycemia) of these drugs. Moreover, this review suggested that esomeprazole could be the best drug in the PPI group to be prescribed simultaneously with metformin and DPP-4 inhibitors, as most of the antidiabetic drugs of this study did not show any interaction with esomeprazole. The findings of this study also revealed that both antidiabetic drugs and PPIs could have positive interactions as PPIs have the potential to lessen the gastrointestinal side effects of metformin and DPP-4 inhibitors. To achieve the greatest therapeutic impact with the fewest side effects, careful dose control of these drugs is required. So, more extensive research on both human and animal subjects are needed to ascertain the veracity of this hypothesis.

Pharmacodynamic Drug-Drug Interactions and Bleeding Outcomes in Patients with Atrial Fibrillation Using Non-Vitamin K Antagonist Oral Anticoagulants: a Nationwide Cohort Study.

Pharmacodynamic drug-drug interactions (PD DDIs) may influence the safety of non-vitamin K antagonist oral anticoagulants (NOACs), but the extent to which PD DDIs increase bleeding risks, remains unclear. Therefore, the impact of PD DDIs on bleeding outcomes in NOAC-treated patients with atrial fibrillation (AF) was investigated. Using Belgian nationwide data, NOAC-treated AF patients were included between 2013-2019. Concomitant use of PD interacting drugs when initiating NOAC treatment was identified. Among 193,072 patients, PD DDIs were identified in 114,122 (59.1%) subjects. After multivariable adjustment, concomitant use of PD interacting drugs was associated with significantly higher risks of major or clinically-relevant non-major bleeding (adjusted hazard ratio (aHR) 1.19, 95% confidence interval (CI) (1.13-1.24)), gastrointestinal (aHR 1.12, 95%CI (1.03-1.22)), urogenital (aHR 1.21, 95%CI (1.09-1.35)) and other bleeding (aHR 1.28, 95%CI (1.20-1.36)), compared to NOAC-treated AF patients without PD interacting drug use. Increased bleeding risks were most pronounced with P2Y12 inhibitors (aHR 1.62, 95%CI (1.48-1.77)) and corticosteroids (aHR 1.53, 95%CI (1.42-1.66)), followed by selective serotonin or serotonin and norepinephrine reuptake inhibitors (SSRI/SNRI, aHR 1.26, 95%CI (1.17-1.35)), low-dose aspirin (aHR 1.14, 95%CI (1.08-1.20)) and non-steroidal anti-inflammatory drugs (NSAID, aHR 1.10, 95%CI (1.01-1.21)). Significantly higher intracranial bleeding risks in NOAC users were observed with SSRI/SNRIs (aHR 1.50, 95%CI (1.25-1.81)) and corticosteroids (aHR 1.49, 95%CI (1.21-1.84)). Concomitant use of PD interacting drugs, especially P2Y12 inhibitors and corticosteroids, was associated with higher major, gastrointestinal, urogenital, and other bleeding risks in NOAC-treated AF patients. Remarkably, higher intracranial bleeding risks were observed with SSRI/SNRIs and corticosteroids.

Pharmacokinetic and pharmacodynamic drug-drug interaction of Nomilin with atorvastatin in hyperlipidemic mice

Atorvastatin (Atv) is widely used to lower cholesterol levels and treat hyperlipidemia in clinical application. Nomilin (Nom) is a kind of limonoids, which is found and isolated from the citrus herbs of Rutaceae family, which are widely used as patent medicines, functional foods, and nutritional supplements in many countries. In previous studies, Nom has the effect of anti-obesity and curing other metabolic diseases. Nevertheless, in recent years, the drug-drug interaction (DDI) caused by the administration of drugs with synergistic effects have raised worldwide concerns. To investigate the DDI of Nom and Atv in vivo, the pharmacokinetic studies were performed with using C57BL/6 mice. The plasma concentrations of Nom and Atv were measured after oral administration of different drug combinations by a simple and sensitive UHPLC-MS/MS method. The experimental mice were randomly divided into five groups, including control group, model group, administered Nom individually group, administered Atv individually group and co-administered of Nom and Atv group. The lipid levels including total cholesterol (TC), triglycerides (TG), high density lipoproteins-cholesterol (HDL-C), low density lipoproteins-cholesterol (LDL-C) were measured for pharmacodynamic study. The hepatic microsomal Cytochrome P450 (CYP1A2, CYP2E1 and CYP3A11) activities were probed using cocktail assay. The gene and protein expressions of CYP3A11 were detected via qPCR and Western blot method. The results shown that the area under the plasma concentration-time curve (AUC) of Atv in administered Atv individually group was 69.30 ± 15.45 ng/mL × h, while that of combined Nom with Atv group was 42.37 ± 10.15 ng/mL × h (p＜0.05). The degree of reduction in lipid levels of mice treated with co-administration of Atv and Nom was less than that of mice treated with Atv alone. In addition, Nom could cause an increased hepatic microsomal CYP3A11 activity significantly, and induce the gene levels and protein expressions of CYP3A11 elevated in mice livers. In conclusion, Nom could up-regulate CYP3A11 activity, thereby impacting on the pharmacokinetic profile and pharmacodynamic effect of Atv. The findings provide more insight for the use risk of these two drugs to treat hyperlipidemia diseases.

A mechanistic assessment of the nature of pharmacodynamic drug-drug interaction in vivo and in vitro.

Combination pharmacotherapy is becoming increasingly necessary because most diseases are pathophysiologically controlled at the subcellular level by target proteins in a combinatorial manner. We demonstrate the application of the stimulus-response mechanistic model in characterising the drug and physiological properties of pharmacodynamic drug-drug interactions (PDDI) using previously published in vitro and in vivo drug combination experiments. The in vitro experiment tested the effect of a combination of SCH66336 and 4-HPR on the survival of in squamous cell carcinoma cell lines, while the in vivo experiment tested the effect of a combination of cetuximab and cisplatin on tumour growth inhibition in female xenograft mice. The model adequately described both experiments, quantified both system and drug properties and predicted the nature of the PDDI mechanism. Strong baseline signals of 7.35 and 610 unitsexisted in the in vitro and in vivo experiments respectively. An overall synergistic relationship (interaction index = 1.03E-8) was detected in the in vitro experiment. In the in vivo model, the overall interaction index was 70,139.45 implying an antagonistic interaction between the cisplatin and the cetuximab signals.

Revealing the dynamic landscape of drug-drug interactions through network analysis.

Introduction: The landscape of drug-drug interactions (DDIs) has evolved significantly over the past 60years, necessitating a retrospective analysis to identify research trends and under-explored areas. While methodologies like bibliometric analysis provide valuable quantitative perspectives on DDI research, they have not successfully delineated the complex interrelations between drugs. Understanding these intricate relationships is essential for deciphering the evolving architecture and progressive transformation of DDI research structures over time. We utilize network analysis to unearth the multifaceted relationships between drugs, offering a richer, more nuanced comprehension of shifts in research focus within the DDI landscape. Methods: This groundbreaking investigation employs natural language processing, techniques, specifically Named Entity Recognition (NER) via ScispaCy, and the information extraction model, SciFive, to extract pharmacokinetic (PK) and pharmacodynamic (PD) DDI evidence from PubMed articles spanning January 1962 to July 2023. It reveals key trends and patterns through an innovative network analysis approach. Static network analysis is deployed to discern structural patterns in DDI research, while evolving network analysis is employed to monitor changes in the DDI research trend structures over time. Results: Our compelling results shed light on the scale-free characteristics of pharmacokinetic, pharmacodynamic, and their combined networks, exhibiting power law exponent values of 2.5, 2.82, and 2.46, respectively. In these networks, a select few drugs serve as central hubs, engaging in extensive interactions with a multitude of other drugs. Interestingly, the networks conform to a densification power law, illustrating that the number of DDIs grows exponentially as new drugs are added to the DDI network. Notably, we discovered that drugs connected in PK and PD networks predominantly belong to the same categories defined by the Anatomical Therapeutic Chemical (ATC) classification system, with fewer interactions observed between drugs from different categories. Discussion: The finding suggests that PK and PD DDIs between drugs from different ATC categories have not been studied as extensively as those between drugs within the same categories. By unearthing these hidden patterns, our study paves the way for a deeper understanding of the DDI landscape, providing valuable information for future DDI research, clinical practice, and drug development focus areas.

Hydrocodone, Oxycodone, and Morphine Metabolism and Drug-Drug Interactions.

Awareness of drug interactions involving opioids is critical for patient treatment as they are common therapeutics used in numerous care settings, including both chronic and disease-related pain. Not only do opioids have narrow therapeutic indexes and are extensively used, but they have the potential to cause severe toxicity. Opioids are the classical pain treatment for patients who suffer from moderate to severe pain. More importantly, opioids are often prescribed in combination with multiple other drugs, especially in patient populations who typically are prescribed a large drug regimen. This review focuses on the current knowledge of common opioid drug-drug interactions (DDIs), focusing specifically on hydrocodone, oxycodone, and morphine DDIs. The DDIs covered in this review include pharmacokinetic DDI arising from enzyme inhibition or induction, primarily due to inhibition of cytochrome p450 enzymes (CYPs). However, opioids such as morphine are metabolized by uridine-5'-diphosphoglucuronosyltransferases (UGTs), principally UGT2B7, and glucuronidation is another important pathway for opioid-drug interactions. This review also covers several pharmacodynamic DDI studies as well as the basics of CYP and UGT metabolism, including detailed opioid metabolism and the potential involvement of metabolizing enzyme gene variation in DDI. Based upon the current literature, further studies are needed to fully investigate and describe the DDI potential with opioids in pain and related disease settings to improve clinical outcomes for patients. SIGNIFICANCE STATEMENT: A review of the literature focusing on drug-drug interactions involving opioids is important because they can be toxic and potentially lethal, occurring through pharmacodynamic interactions as well as pharmacokinetic interactions occurring through inhibition or induction of drug metabolism.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions: Research Methods and Applications.

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

Pharmacokinetic and Pharmacodynamic Drug-Drug Interactions between Evogliptin and Empagliflozin or Dapagliflozin in Healthy Male Volunteers.

Evogliptin is a novel dipeptidyl peptidase-4 inhibitor (DPP4i) for glycemic control in patients with type 2 diabetes mellitus(T2DM). This study evaluated the pharmacokinetic (PK) and pharmacodynamic (PD) interactions between evogliptin and sodium glucose cotransporter-2 inhibitors (SGLT2i) in healthy volunteers since combination therapy of DPP4i and SGLT2i has been considered as effective option for T2DM treatment. A randomized, open-label, multiple-dose, two-arm, three-period, three treatments, two-sequence crossover study was conducted in healthy Korean volunteers. In arm 1, subjects were administered 5 mg of evogliptin once daily for 7 days (EV), 25 mg of empagliflozin once daily for 5 days (EP), and the combination once daily for 5 days (EV+EP). In arm 2, subjects were administered 5 mg of evogliptin once daily for 7 days (EV), 10 mg of dapagliflozin once daily for 5 days (DP), and the combination once daily for 5 days (EV+DP). Serial blood samples were collected for PK analysis, and oral glucose tolerance tests were conducted for PD analysis. In each arm, a total of 18 subjects completed the study. All adverse events were mild with no serious adverse events. The geometric mean ratio and confidence interval of the main PK parameters (Cmax,ss and AUCτ,ss ) between EV and either EP or DP alone were not significantly altered by co-administration. Administration of EV+EP or EV+DP did not result in significant PD changes, as determined by the glucose-lowering effect. Administration of EV+EP or EV+DP had no significant effects on the PK profiles of each drug. All treatments were well-tolerated.

Evaluation of the potential herb-drug interaction between Bojungikki-tang and PD-L1 immunotherapy in a syngeneic mouse model.

Atezolizumab (a PD-L1 inhibitor) has shown remarkable efficacy and tolerability in various cancer types. Despite its efficacy and safety, atezolizumab monotherapy has limitations, such as acquired resistance and adverse events. Bojungikki-tang (BJIKT) is an herbal decoction widely prescribed in Asian countries and used to treat cancer-related symptoms including fatigue, appetite loss, gastrointestinal disorders, and other side effects from cancer therapy. Due to its immunomodulatory effects, Bojungikki-tang has been investigated as a combined treatment with anticancer agents. We evaluated the potential drug-drug interaction (DDI) between Bojungikki-tang and the anti-PD-L1 antibody based on the Food and Drug Administration (FDA) guidelines. In the study, we conducted an in vivo drug-drug interaction study using a syngeneic mouse model of CMT-167 in C57BL/6. We then determined the antibody concentrations to evaluate the pharmacokinetic (PK) drug-drug interaction and measured variable biomarkers related to therapeutic efficacy and immune response. The pharmacodynamic (PD) drug-drug interaction study investigated changes in response between anti-PD-L1 antibody monotherapy and combination therapy. Using the pharmacokinetic and pharmacodynamic data, we conducted a statistical analysis to assess drug-drug interaction potential. In the presence of Bojungikki-tang, the pharmacokinetic characteristics of the anti-PD-L1 antibody were not changed. This study suggested that combination treatment with Bojungikki-tang and atezolizumab is a safe treatment option for non-small cell lung cancer. Clinical studies are warranted to confirm this finding.

Assessment of the Potential for Drug–Drug Interactions Between INP104 and Gepants for Migraine Management Using a Model-based Approach (P12-12.008)

Assessment of the Potential for Drug–Drug Interactions Between INP104 and Gepants for Migraine Management Using a Model-based Approach (P12-12.008)

Incidence of drug-drug interactions of QT-prolonging drugs in an onco-hematological outpatient

Abstract Background Oral anticancer therapy is increasingly integrated into the care of patients (pts) with cancer. Recognition and management of pharmacodynamic drug-drug interactions is critical to provide efficacious and safe anticancer treatment. Purpose We aimed to gain insight into the real-world prevalence of potentially significant drug-drug interactions of QT-prolonging with oral antineoplastic agents used in an Oncohematological Hospital Methods We performed a prospective observational study in an oncohematological hospital between October 2020 and June 2021. Consecutive pts diagnosed with an oncohematological neoplasia and who were evaluated before start treatment with an oral anticancer drug or suport treatment (antibiotics, antivirals) were included. Cancer treatment data were obtained from our prescription software System. Demographic data and concomitant medication were obtained from our electronic medical record software. Micromedex was used to find potencial QT-prolonging interactions between anticancer drugs and chronic medication, and were classified as major or moderate. Results Oncohematological treatment was started in 1.217 pts during the study period. A total of 266 potential drug-drug interactions were detected in 171 patients (14.5%). A total of 46 drug-drug interactions of QT-prolonging (17.3%) were detected in 37 pts (21.6%), 22 men and 15 women, with a median age of 66.6 (range 40.9–87.3). Twenty-one (45.7%) and 25 (56.3%) drug interactions of QT-prolonging were classified as major and moderate, respectively, with a median interaction per pts 1.24 (1–3). The 3 most common cancers were: Renal carcinoma in 12 pts (32.4%), non-small cell lung carcinoma in 9 pts (24.7%) and prostate carcinoma in 4 pts (10.8%). The most commonly detected interacting drugs were sunitinib 12 pts (26.1%), osimertinib 10 pts (21.7%), and cabozantinib 5 pts (10.9%) among oncohematological drugs, and citalopram 8 (17.4%), quetiapine 6 (13%) and tramadol 5 (10.8%) among concomitant drugs. Conclusion Drug-drug interactions can play a significant role in drugs' cardiac safety in oncohematological pts, specially in renal, lung and prostate cancers, with more than one potential interacting drug or at least one major interaction. Cardiac monitorizacion should be considered when potential drug drug interaction is detected. Funding Acknowledgement Type of funding sources: None.

1595P QTc-prolonging drug-drug interactions related to CDK4/6 inhibitors

The cyclin-dependent kinases (CDK)4/6 inhibitors abemaciclib, palbociclib and ribociclib are approved for the treatment of hormone receptor-positive metastatic breast cancer. These drugs are equally effective according to literature, however, ribociclib is associated with concentration-dependent QTc-prolongation. This complicates ribociclibs use in patients, as pharmacokinetic and pharmacodynamic drug-drug interactions (DDIs) resulting in QTc-prolongation might occur with concomitant medications.

Application of physiologically-based pharmacokinetic/pharmacodynamic models to evaluate the interaction between nifedipine and apatinib.

Aim: It has been found that the co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. But, whether this pharmacokinetic drug-drug interaction (DDI) between nifedipine and apatinib could enhance the antihypertensive effect of nifedipine, causing sever changes of blood pressure was unknown. Therefore, the aim of the present study was to conduct the pharmacokinetic/pharmacodynamic (PK/PD) modelling to evaluate the effect of pharmacokinetic changes on the antihypertensive effect of nifedipine. Thus, the results could guide the co-administration of these two drugs in clinic. Methods: A physiologically-based pharmacokinetic (PBPK) model was first developed for nifedipine. The pharmacokinetic DDI between nifedipine and apatinib was evaluated. Then the verified PBPK models were linked to a PD model for investigating whether the exposure changes of nifedipine could cause severe changes in blood pressure. Furthermore, the changes in blood pressure caused by combination with apatinib were also assessed in patients with hepatic impairment via the PBPK/PD models. Results: The predicted area under plasma concentration-time profile (AUC), maximum concentration (Cmax), area under effect-time profile (AUE), and maximum reduction in systolic blood pressure (Rmax) are all within 0.5–2.0-fold of the observed data, indicating that the PBPK/PD models for nifedipine are successfully established. The increases of predicted AUC and Cmax of nifedipine in the presence of apatinib are 1.73 and 1.41-fold, respectively. Co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. However, the predicted AUE and Rmax changes of nifedipine in the presence to the absence of apatinib in cancer patients as well as in patients with hepatic impairment are all within 1.25-fold. The results indicate that the exposure changes of nifedipine caused by combination of apatinib has little effect on the changes of systolic blood pressure both in cancer patients and patients with hepatic impairment. Conclusion: The pharmacokinetic changes of nifedipine caused by co-administration with apatinib has little impact on the antihypertensive effect of nifedipine. Apatinib is unlikely to cause severe pharmacodynamic DDI via inhibition of CYP3A4. It is suggested that nifedipine could be used in combination with apatinib without dose adjustment in clinic.

Prevalence of Pharmacologic Treatments for Chronic Obstructive Pulmonary Disease in Relation of Diagnosis of Dementia Among Nursing Homes Residents.

Chronic obstructive pulmonary disease (COPD) is a chronic disease affecting millions of older adults. We investigated the prevalence of nursing home (NH) residents with COPD and their pharmacologic treatment in relation to the diagnosis of dementia and the prevalence of potentially severe drug-drug interactions (DDIs) of COPD medications with drugs prescribed to treat comorbidities. Retrospective cross-sectional multicentre study. Individuals living in long-term care NHs. This cross-sectional cohort study was conducted in a sample of Italian long-term care NHs located throughout the country. Information on drug prescriptions, diseases, and sociodemographic characteristics was collected using medical records between 2018 and 2020. Potentially severe DDIs were analyzed using INTERCheck, developed by the Istituto di Ricerche Farmacologiche Mario Negri IRCCS. Among the 2604 residents living in 27 NHs (mean age 86.4 ± 8.5years; women 1995, 76.6%; number of drugs 7.3 ± 3.6), 306 had a diagnosis of COPD (11.8%) and 84 (27.5%) of them were treated with at least 1 medication for COPD (27.5%). Those without dementia had a higher prevalence of drugs for COPD than those with dementia (48% vs 20%, P < .0001). The most used classes for COPD were adrenergics in combination with corticosteroids (16.7%) and inhalant anticholinergics (14.7%). Among those receiving medications for COPD, 45 had at least 1 potentially severe DDI with medications for comorbidities (53.6%) and most of them were associated with an increased risk of QTc prolongation, as beta2 agonists with diuretics, antipsychotics or antidepressants. Most NH residents with COPD did not receive any medication for this disease despite the potential benefits. Residents with dementia received fewer COPD medications probably because of their compromised physical and cognitive status. One-half of the NH residents taking medication for COPD were exposed to an increased risk of QTc prolongation and torsades de pointe because of pharmacodynamic DDIs with medication for comorbidities. Close monitoring of electrocardiograms for NH residents with COPD is recommended.