Drug Interactions Research Articles

A practical assessment protocol for clinically relevant P-glycoprotein-mediated drug-drug interactions.

Drug-drug interactions (DDIs) may influence the effectiveness and safety of medication treatment, which may require additional monitoring, dose adjustment or avoidance of certain drugs. DDIs involving P-glycoprotein (P-gp) affect many drugs, but current official product information is often insufficient to guide the management of these DDIs in clinical practice. The aim of this paper is to describe a protocol to assess DDIs involving P-gp and to develop and implement practice recommendations for clinically relevant P-gp-mediated DDIs that affect clinical outcomes through changes in systemic drug exposure. A combined literature review and expert opinion approach will be used according to the following seven steps: set up an expert panel (step 1), establish core concepts and definitions (step 2), select potential P-gp-modulators (i.e., P-gp-inducers and -inhibitors) and P-gp-substrates to be evaluated (step 3), select and extract evidence-based data, and present findings in standardized assessment reports (step 4), discuss and adopt classifications and practice recommendations with the expert panel (step 5), publish and integrate information and alerts in clinical decision support systems (CDSS) (step 6), (re)assessments of DDIs and potential new DDIs when new information is available or when initiated by healthcare providers (step 7). The expert panel will classify potential P-gp-modulators and -substrates as clinically relevant P-gp-inducer, -inhibitor and/or -substrate and draw conclusions about which combinations of classified modulators and substrates will lead to clinically relevant DDIs. This may include the extrapolation of conclusions for DDIs where limited or no data are available, based on the pharmacological characteristics of these drugs. For (potential) DDIs that are considered to be clinically relevant, practice recommendations will be developed. This protocol describes a standardized, evidence- and expert opinion-based assessment of P-gp-mediated DDIs that affect clinical outcomes. This approach will generate alerts with practice recommendations for clinically relevant DDIs and transparent rationales for DDIs that are considered to be irrelevant. These recommendations will improve individual patient care by supporting healthcare professionals to make consistent decisions on how to manage P-gp mediated DDIs.

Clinical drug interactions between voriconazole and 38 other drugs: a retrospective analysis of adverse events.

Voriconazole (VRZ) is involved in a variety of drug‒drug interactions (DDIs), but few studies have reported adverse events (AEs) associated with the DDIs of VRZ. The primary goal of this study was to analyse the potential risk factors for AEs caused by DDIs between VRZ and other drugs via the OpenVigil FDA platform and to provide a reference for preventing VRZ DDIs and monitoring clinically related adverse drug events. A retrospective pharmacovigilance study was conducted to investigate the AEs related to DDIs between VRZ and four categories of drugs: proton pump inhibitors (PPIs), non-steroidal anti-inflammatory drugs (NSAIDs), immunosuppressants, and other antibacterial drugs. AE information for the target drugs from the first quarter of 2004 to the third quarter of 2022 was downloaded from the OpenVigil FDA data platform. Four frequency statistical models-the reporting ratio method, Ω shrinkage measure model, combination risk ratio model, and the chi-square statistics model-were used to analyse the AEs related to DDIs and evaluate the correlation and influence of sex and age between the drug(s) and the target AEs detected. A total of 38 drugs were included, with 262 AEs detected by at least one of the four models and 48 AEs detected by all four models. Some 77 detected AEs were significantly positively correlated with DDIs and were related to higher reporting rates of AEs than when used alone. Graft-versus-host disease was the AE that had the strongest correlation with the drug interaction between VRZ and immunosuppressants (tacrolimus, mycophenolate mofetil, cyclophosphamide, and cyclosporine), and multiple organ dysfunction syndrome was correlated with VRZ in combination with other antibacterial drugs (linezolid, meropenem, cefepime, and vancomycin). Significant sex and age differences in the target AEs were detected for five and nine target drugs, respectively. For VRZ in combination with linezolid, aggravated conditions and respiratory failure should be given more attention in male patients, and mycophenolate mofetil and respiratory failure in female patients. When conditions are aggravated, febrile neutropenia and septic shock should be of particular concern in patients over 18years of age who use VRZ in combination with ceftazidime, ciprofloxacin, or cytarabine. In patients aged under 18, septic shock should be considered when VRZ is used in combination with meropenem and dexamethasone. AEs related to DDIs should receive more attention when VRZ is used in combination with PPIs (renal impairment), NSAIDs (constipation and renal failure), immunosuppressants (graft versus host disease, septic shock) and other antibacterial drugs (multiple organ dysfunction syndrome, febrile neutropenia, and respiratory failure). Considering the influence of sex and age differences in VRZ DDIs, these factors need to be considered when assessing the risk of AEs in patients receiving VRZ and other drugs.

Pharmacist-Led Video Consultation to Identify and Mitigate Drug Interactions Among Patients Initiating Oral Anticancer Drugs.

The past decade has seen an increase in oral anticancer drug (OACD) approvals. Polypharmacy and drug-drug interactions (DDIs) likely contribute to OACD toxicity. We assessed a one-time pharmacist-led video consultation to identify DDIs. We conducted a single-arm telehealth intervention of a one-time 30-minute pharmacist-led video consultation among patients initiating OACDs. The visit focused on identifying polypharmacy and DDIs. Feasibility was defined as ≥50% completion of all study interventions. We determined the prevalence, characteristics, and severity of OACD-related potential DDIs. We also assessed the prevalence of medication list inaccuracies, polypharmacy, patient satisfaction, and patient perception of intervention acceptability, appropriateness, and feasibility. Of 58 eligible patients, 43 (74%) completed the intervention and 33 (57%) completed all evaluations. Median medication per patient was nine (range 4-21), and 98% of patients had at least five prescriptions. The median number of medication list errors was two (range 0-16), with at least one error for 76% and >1 for 52%. Pharmacists identified OACD-related interactions in 18 cases (42%), including change in drug metabolism (eight), elimination (one), and absorption (three). Interactions were classified as Lexicomp categories C (13), D (five), or X (one) requiring close monitoring or a change in treatment. All patients expressed high satisfaction with the intervention and agreed or completely agreed that it was acceptable, appropriate, and feasible. Polypharmacy, medication list errors, and DDIs are prevalent among patients initiating OACDs. A one-time remote pharmacist-led video consultation can address OACD-related DDIs, which may decrease medication complexity and improve adherence.

KAJIAN POTENSI INTERAKSI OBAT PADA PASIEN GERIATRI DENGAN GAGAL JANTUNG DI RSUD Dr. MOEWARDI SURAKARTA TAHUN 2023

Geriatric patients with heart failure generally receive more than 1 type of drug therapy, called polypharmacy, which typically involves at least four types of treatment: ACEI (Angiotensin Converting Enzyme Inhibitors), diuretics, beta blockers, and digoxin. This causes an increase in the occurrence of drug interactions. This study aims to determine the potential drug interactions that occur in geriatric patients with heart failure who undergo hospitalization at Dr. Moewardi Surakarta Hospital from January to December 2023. This study is a descriptive observational study with a cross-sectional design, and the data were collected retrospectively using a purposive sampling technique based on the medical records of geriatric patients at Dr. Moewardi Surakarta Hospital in 2023. The inclusion criteria were inpatients aged ≥55 years who were diagnosed with heart failure. The exclusion criteria were patients with incomplete or illegible medical record data or who died during treatment. Drug interaction research was conducted based on Drugs.com and Medscape. The results showed that out of the 100 patients, 98 experienced drug interactions. The incidence of drug interactions was 252 minor cases (21.65%), 818 moderate cases (69.50%), and 106 major cases (9.00%). The mechanism of drug interaction was pharmacodynamic in 919 cases (65.50%), pharmacokinetic in 213 cases (30.40%), and unknown in 44 cases (4.10%).

Ticagrelor and Statins: Dangerous Liaisons?

Polypharmacy is often necessary in complex, chronic, comorbid and cardiovascular patients and is a known risk factor for potential drug-drug interaction (DDI) that can cause adverse reactions (toxicity or therapeutic failure). Anti-thrombotic drugs (largely low-dose aspirin and a platelet P2Y12 receptor inhibitor) and statins are among the most co-administered drugs in cardiovascular patients. Ticagrelor is a selective antagonist of the platelet P2Y12-receptor, highly effective in inhibiting platelet aggregation and bio-transformed by the CYP3A4 and substrate of transporters, such as the breast cancer resistance protein (BCRP). Statins have different pharmacokinetic profiles; some undergo CYP3A4-mediated metabolism; rosuvastatin is primarily metabolized by the CYP2C9; and they have different affinities for drug transporters. Rhabdomyolysis is a very rare but severe adverse event, which is specific for statins which can be triggered by DDIs that increase statin's concentrations through blockade of their biotransformation and/or elimination. Large pharmacovigilance and small observational studies reported increased rhabdomyolysis in patients treated with some statins and ticagrelor but not aspirin, clopidogrel or prasugrel. Recent studies in vitro, pharmacokinetic trials and in silico drug modelling identified and validated the BCRP inhibition by ticagrelor, as a mechanism contributing to the DDI with statins, as 'victim' drugs, leading to increased rhabdomyolysis. While the clinical impact of this DDI deserves further investigation, a careful evaluation should be advised when ticagrelor is co-prescribed with some statins.

The Impact of Customized Screening Intervals on the Burden of Drug-Drug Interaction Alerts: An Interrupted Time Series Analysis.

Fixed and broad screening intervals for drug-drug interaction (DDI) alerts lead to false positive alerts, thereby contributing to alert fatigue among healthcare professionals. Hence, we aimed to investigate the impact of customized screening intervals on the daily incidence of DDI alerts. An interrupted time series analysis was performed at the University Hospitals Leuven to evaluate the impact of a pragmatic intervention on the daily incidence of DDI alerts per 100 prescriptions. The study period encompassed 100 randomly selected days between April 2021 and December 2022. Preceding the intervention, a fixed and broad screening interval of 7 days before and after prescribing an interacting drug was applied. The intervention involved implementing customized screening intervals for a subset of highly prevalent or clinically relevant DDIs into the hospital information system. Additionally, the sensitivity of the tailored approach was evaluated. During the study period, a mean of 5731 (± 2909) new prescriptions per day was generated. The daily incidence of DDI alerts significantly decreased from 9.8% (95% confidence interval (CI) 8.4;11.1) before the intervention, to 6.3% (95% CI 5.4;7.2) afterwards, p < 0.0001. This corresponded to avoiding 201 (0.035*5731) false positive DDI alerts per day. Sensitivity was not compromised by our intervention. Defining and implementing customized screening intervals was feasible and effective in reducing the DDI alert burden without compromising sensitivity.

Evaluating deep neural networks in optimizing drug discovery and precision medicine: A review

Introduction/Background: Deep neural networks have shown great promise in advancing drug discovery and precision medicine. By leveraging large amounts of complex biomedical and chemical data, deep learning approaches can identify novel targets, predict drug-target and drug-drug interactions, generate new molecular structures, and assist in personalized treatment selection and development. However, fully utilizing deep learning techniques for optimization across the drug development pipeline remains an ongoing challenge. Materials and Methods: A comprehensive literature review was conducted using major bibliographic databases including PubMed, Web of Science, and Scopus. Search terms included combinations of "deep learning", "drug discovery", "precision medicine", "biomedical data", and "neural networks". Over 200 papers published between 2010-2023 related to deep learning applications in pharmacology and genomics were identified and reviewed. Results: Deep learning has been widely applied at various stages of the drug discovery process including target identification/prioritization, lead generation/optimization, and prediction of molecular properties. Convolutional neural networks are commonly used for the representation and classification of biological sequence and image data for tasks such as gene expression analysis and pathogen detection from microscopy images. Graph neural networks effectively model compound structures and interactome networks to predict molecular bindings and disease associations. Multi-modal neural networks integrate diverse data types for personalized treatment response prediction and biomarker discovery. Challenges remain around data and model interpretation, generalization to new targets/diseases, and integration across domains. Discussion: While deep learning has shown promise, rigorous benchmarking and validation on real-world clinical endpoints are still needed to establish usefulness in decision-making. Data and model transparency must be improved to enable scientific insights. Privacy and security risks accompanying "real world" biomedical big data will require ethical practices. Standardization and sharing of resources/protocols could accelerate progress by enabling comparison of techniques. Combining deep learning with other AI paradigms like causal inference may further improve utility in drug discovery and precision healthcare. Conclusion: Deep neural networks demonstrate potential for optimizing drug development and precision medicine applications. Continued advancement relies on addressing challenges around data, models, validation, and ethics. Multi-disciplinary collaborations integrating machine learning, molecular biology, medicine, and other domains are needed to fully realize benefits to patients.

The emergence of letermovir and maribavir drug-resistant mutations: from clinical trials to real-world studies.

Cytomegalovirus (CMV) infection is associated with severe clinical disease and high morbidity in immunocompromised hosts. Letermovir and maribavir, are two recently developed antiviral drugs used in the prevention and treatment of resistant and refractory CMV. Following the publication of landmark randomized trials and increased use, both clinical trial data and real-world experience has reported the development of antiviral drug resistance. The aim of this review was to comprehensively review the published literature on letermovir and maribavir drug resistance and to describe the clinical scenarios in which they may emerge. For letermovir, the most frequently detected resistance mutations occur in the UL56 gene (C325Y/W/F) and confer total resistance. Maribavir resistance mutations most often occur in the UL97 gene and resistance-associated variants (RAVs) T409M, H411Y, C480F have all been detected. The clinical context in which letermovir and maribavir resistance occurs include high viral loads at initiation, intensified immunosuppression, subtherapeutic drug exposure because of poor adherence, drug interactions, and inadequate central nervous system (CNS) penetration. Emergence of resistance mutations generally occurs within the first 3 months of initiation. The detection of letermovir and maribavir resistance mutations highlights an ongoing clinical challenge in the management of CMV.

GLP-1 RA-Semaglutide a game changer drug for management of obesity with and without Diabetes - A narrative review

Obesity is a chronic and relapsing disease marked by excessive fat accumulation that poses serious health risks, with an increasing global prevalence including in low- and middle-income countries. Obesity-related complications, including cardiovascular diseases, diabetes, and cancer, also contribute to significant healthcare costs. Management strategies involve lifestyle modifications, pharmacological interventions, and, in severe cases, surgical procedures. Semaglutide, a GLP-1 receptor agonist, has emerged as an effective treatment for both obesity and type 2 diabetes, showing significant weight loss outcomes and improvements in metabolic health across various patient groups. However, careful monitoring of adverse effects and drug interactions is crucial for optimizing therapeutic outcomes.Several novel agents are under development, with multi-hormone receptor agonists and oral formulations likely to become available in the coming years. As effective treatment options expand, cost and availability will need to be addressed to enable equitable access to treatment. Bangladesh J Medicine 2024; 35: 133-146

Administration sequences in single-day chemotherapy regimens for breast cancer: a comprehensive review from a practical perspective.

Breast cancer is one of the most prevalent malignant tumors globally, posing a severe threat to human life and health. Chemotherapy, a cornerstone in the treatment of breast cancer, often overlooks the sequence of drug administration within single-day regimens. This study aims to explore the impact of drug administration order on the efficacy and toxicity of combination chemotherapy protocols for breast cancer. Through a comprehensive review and analysis based on current evidence from evidence-based medicine, we delved into how the order of drug administration affects both efficacy and toxicity. We systematically classified and analyzed commonly used combination drug regimens, providing graded recommendations and a reasoned analysis to offer valuable references for clinical decision-making. Our findings indicate that the sequence of drug administration in complex combination chemotherapy protocols is not arbitrary but necessitates multifaceted considerations. Rational drug sequencing can maximize synergistic effects between drugs, thereby augmenting therapeutic efficacy while effectively mitigating drug-related adverse effects. Additionally, some drug labels and clinical trials have explicitly highlighted the therapeutic benefits of specific drug sequences. This study underscores the importance of considering the sequence of drug administration in clinical practice. It is recommended to prioritize the sequential drug administration according to official drug product labeling, while also considering factors such as the administration sequence from large randomized controlled trials, cell proliferation kinetics specific to cancer types, drug interactions, chronopharmacology, drug irritability, clinical experiences, and patient preferences. By taking these factors into account, the goal is to maximize treatment efficacy and minimize the occurrence of adverse reactions.

The Management of Hematopoietic Stem Cell Transplant in People with HIV.

Hematopoietic stem cell transplant (HSCT) is now recognized as a standard treatment option for people with HIV (PWH) who develop high-risk hematologic malignancies. However, the involved polypharmacy can lead to complications from drug interactions and toxicities, affecting the efficacy and safety of chemotherapy and antiretroviral therapy (ART). Managing these patients requires a personalized approach, including the careful selection of ART based on previous therapies and potential interactions, alongside risk assessment for infections. This discussion will address the history of HSCT in PWH and management considerations for this group.

Is dabigatran a good alternative to warfarin in patients with atrial fibrillation accompanied by valvular and nonvalvular heart diseases? A systematic review and meta-analysis

Abstract Background There is ongoing discussion regarding the terminology used when atrial fibrillation (AF) is present alongside either valvular heart disease (VHD) or non-valvular heart disease (NVHD). Warfarin has been used for decades for stroke (S) and systemic embolism (SE) prophylaxis in atrial fibrillation (AF) patients. However, due to its drug and food interactions, pharmacogenetic approach via VKORC1, narrow therapeutic window, frequent monitoring, and high risk of intracranial hemorrhage (ICH), it is not preferred as a first-line anticoagulant for AF patients. Is it time to retire warfarin and replace it with dabigatran? Aim and objectives We conducted this meta-analysis to assess the effectiveness and safety of dabigatran compared to warfarin and find out how likely it could be used instead of warfarin in AF patients with VHD and NVHD. Methods PubMed, SCOPUS, Web of Science, and Cochrane CENTRAL were searched online from inception till June 2023, and eligible randomized controlled trials (RCTs) were selected. The outcomes were analyzed and calculated using the risk ratio (RR), and its confidence interval (CI) using STATA software. The Cochrane Risk of Bias 2.0 tool (ROB2) was used to assess the included studies. Results In the NVHD subgroup, dabigatran 150 mg showed a significantly low risk of S and SE (RR 0.74, 95% CI: [0.62,0.88]), ICH (RR 0.38, 95% CI: [0.26,0.56]), death (RR 0.85, 95% CI: [0.74,0.99]), and high risk of gastrointestinal bleeding (GIB) (RR 1.47, 95% CI: [1.17,1.85]) compared to Warfarin. Dabigatran 110 mg showed a low risk of ICH (RR 0.31, 95% CI: [0.21,0.47]), and no significant differences in S/SE (RR 1.02, 95% CI: [0.87,1.19]) and death (RR 0.94, 95% CI: [0.82,1.09]) compared to warfarin. In the VHD subgroup, dabigatran showed no significant differences in S/SE (RR 2.57, 95% CI: [0.57,11.56]), major bleeding (RR 1.14, 95% CI: [0.35,3.68]), and death (RR 0.35, 95% CI: [0.07,1.81]) compared to warfarin. In the catheter ablation subgroup, dabigatran showed a significant reduction only in groin hematoma (RR 0.19, 95% CI: [0.05,0.73]), compared to warfarin. Conclusion Dabigatran 150 mg was superior to warfarin in AF patients with NVHD; except with GIB; otherwise, Dabigatran 110 mg was superior only to warfarin in reducing ICH. In catheter ablation, dabigatran only reduced the groin hematoma. In AF patients with VHD, dabigatran did not show either superiority or inferiority to warfarin, further studies are needed. “Non-valvular AF” term is outdated and should be replaced with “type II VHD” to differentiate it from other valvular heart diseases that are accompanied by AF.

Geometry Optimization, Molecular Docking and ADMET Studies of Echimidine Molecule

Plants are an important food group that has been used as a source of nutrition and healing from past to present. Plants contain secondary metabolites that are still under investigation in drug development studies. Alkaloids, which are secondary metabolites, have antioxidant and antibacterial properties as well as therapeutic potential in various diseases such as Alzheimer's disease. Acetylcholinesterase (AChE) inhibitors come to the fore in the treatment strategy of Alzheimer's disease. Echimidine, a pyrrolizidine alkaloid, is an important compound known to be active in AChE inhibition. Molecular docking method has an important place in elucidating biochemical processes by examining the interactions of drugs or drug candidates with the receptors targeted for the disease. Additionally, information on the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drug candidate molecules is important in drug development studies. In this study, echimidine molecule was optimized, the molecular docking study was carried out with AChE and the interaction types, binding profile, and binding affinity of echimidine was determined. ADMET analysis of echimidine was also realized to estimate its drug potential. With this study, geometry optimization of the molecule, elucidation of its interactions with AChE, and prediction of its pharmacokinetic properties were achieved for the first time.

Safety and efficacy of CyTisine for smoking cessation in a hOSPital context (CITOSP): study protocol for a prospective observational study.

Tobacco addiction is the primary preventable factor contributing to global mortality, and nicotine is one of the substances with the greatest potential for addiction. With a strong affinity for the α4β2 subtype receptor, cytisine (CYT) functions as a partial agonist of the acetylcholine nicotinic cholinergic receptor. It counteracts the effects of nicotine without causing any withdrawal symptoms. These features, combined with its limited mild adverse effects and minimal drug-drug interactions, make cytisine a cost-effective treatment for smoking cessation. The current protocol describes a prospective observational study on the safety and efficacy of CYT administered to inpatient smokers of the Integrated University Hospital of Verona (IUHVR), Veneto (Italy). This is a monocentric, observational, and prospective study on both sex smokers over the age of 18 years admitted to the IUHVR who meet the criteria for recruitment and have given their consent. Eligible participants will be assigned to the CYT intervention based on the West dosing schedule and will be followed up for 12 months from treatment initiation. Evaluation of safety, efficacy, and compliance will be assessed at 7 and 25 days, with follow-up at 3, 6, and 12 months from the start of the treatment (quit day). During each visit, any adverse events or adverse reactions reported by patients following the intake of CYT will be evaluated. This study will contribute, for the first time, to the knowledge about the use of CYT for smoking cessation in a hospital setting.

Exploring the Potential of Saffron as a Therapeutic Agent in Depression Treatment: A Comparative Review.

Depression is a significant mental health challenge globally. While traditional antidepressants are effective, they often have unwanted side effects. Saffron, a natural spice derived from Crocus sativus L., has emerged as a potential alternative therapy for depression. Researchers have found that its components such as crocin, crocetin, and safranal have been found to mitigate depressive symptoms through neurotransmitter regulation, anti-inflammatory effects, and neuroprotection. Clinical trials suggest that the effectiveness of saffron in treating mild to moderate depression is comparable to that of standard medications, and animal studies support these results, showing behavioral improvements with saffron treatment. Saffron is particularly appealing due to its safety and lower incidence of side effects, making it suitable for those sensitive to conventional drugs. Additionally, its antioxidant properties may offer further health benefits. However, challenges such as determining the appropriate dosage, prohibitive cost, and the limited availability of quality saffron need to be addressed. Most research on saffron's efficacy is short-term; thus, long-term studies are essential to understand its full therapeutic potential and ongoing antidepressant effects. While saffron is safe in terms of its culinary value, higher therapeutic doses require careful monitoring for drug interactions and side effects. In summary, saffron represents a promising direction in depression treatment, with benefits potentially matching those of standard treatments and a better safety profile. However, further research is necessary to establish clear guidelines for its use, optimize dosing, and assess long-term outcomes. Saffron offers a natural treatment path for depression, but its use must be controlled and supported by scientific evidence.

Mapping data-driven strategies in improving health care and patient satisfaction

Health services involve data analytics, central to healthcare service delivery, research, and planning. Based on the literature, this specific article seeks to enlighten the reader about data analytics in health services by discussing its advantages, shortcomings, and issues that come with it. Section one mapping outlines how data analytics optimizes the results of health service delivery through risk factor definition, disease detection, and case-by-case management. It helps inform disease trajectory, determine drug interaction, monitor disease, support decision-making, and enhance service delivery quality. The research also examines data analysis in health services, medicine, and pharmaceuticals. Several big data analytics applications have been identified as relevant to drug development, personalized medication, and specialized trials. Evaluations that rely on biomarkers differentiate between patients who are convenient for specific therapies, improving the patient's status and developing health care services. The third section also stresses the role of data analytics in enhancing efficiency and profitability. They involve detecting fraud, abuse, and unnecessary medical activities, creating savings and better financial returns. Data analytics also leads to identifying high-cost patients and ways of managing healthcare costs, increasing revenues and profitability. The fourth section discusses how big data complements traditional public health surveillance and outbreak platforms. It facilitates collecting data, analyzing different sources, and identifying special patterns or outliers to detect the outbreak early enough, contain it, or allocate resources to control it. It anticipates and addresses the dangers to the public's well-being and effectively controls episodes of infectious diseases. However, some key issues are associated with data analytics implementation, such as data quality, governance, privacy, bias, integration, expertise, and ethics, among others. Therefore, solving these challenges to achieve the optimum shifting of health service paradigms through data analytics in inpatient treatment, organizational management, and affordability is imperative.

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.

Interaction of 6-Thioguanine with Aluminum Metal-Organic Framework Assisted by Mechano-Chemistry, In Vitro Delayed Drug Release, and Time-Dependent Toxicity to Leukemia Cells.

6-thioguanine (6-TG) is an antimetabolite drug of purine structure, approved by the FDA for the treatment of acute myeloid lesukemia, and it is of interest in treating other diseases. The interaction of drugs with matrices is of interest to achieving a delayed, sustained, and local release. The interaction of 6-TG with an aluminum metal-organic framework (Al-MOF) DUT-4 is studied using a novel experimental approach, namely, mechano-chemistry by liquid-assisted grinding (LAG). The bonding of 6-TG to the DUT-4 matrix in the composite (6-TG)(DUT-4) was studied using ATR-FTIR spectroscopy and XRD. This interaction involves amino groups and C and N atoms of the heterocyclic ring of 6-TG, as well as the carboxylate COO- and (Al)O-H groups of the matrix, indicating the formation of the complex. Next, an in vitro delayed release of 6-TG was studied from composite powder versus pure 6-TG in phosphate buffered saline (PBS) at 37 °C. Herein, an automated drug dissolution apparatus with an autosampler was utilized, and the molar concentration of the released 6-TG was determined using an HPLC-UV analysis. Pure 6-TG shows a quick (<300 min) dissolution, while the composite gives the dissolution of non-bonded 6-TG, followed by a significantly (factor 6) slower release of the bonded drug. Each step of the release follows the kinetic pseudo-first-order rate law with distinct rate constants. Then, a pharmaceutical shaped body was prepared from the composite, and it yields a significantly delayed release of 6-TG for up to 10 days; a sustained release is observed with the 6-TG concentration being within the therapeutically relevant window. Finally, the composite shows a time-dependent (up to 9 days) stronger inhibition of leukemia MV-4-11 cell colonies than 6-TG.

Therapeutic Potential of Momordicine I from Momordica charantia: Cardiovascular Benefits and Mechanisms.

Momordica charantia (bitter melon), a traditional medicinal plant, has been demonstrated to have potential in managing diabetes, gastrointestinal problems, and infections. Among its bioactive compounds, momordicine I, a cucurbitane-type triterpenoid, has attracted attention due to its substantial biological activities. Preclinical studies have indicated that momordicine I possesses antihypertensive, anti-inflammatory, antihypertrophic, antifibrotic, and antioxidative properties, indicating its potential as a therapeutic agent for cardiovascular diseases. Its mechanisms of action include modulating insulin signaling, inhibiting inflammatory pathways, and inducing apoptosis in cancer cells. The proposed mechanistic pathways through which momordicine I exerts its cardiovascular benefits are via the modulation of nitric oxide, angiotensin-converting enzymes, phosphoinositide 3-kinase (PI3K)/ protein kinase B (Akt), oxidative stress, apoptosis and inflammatory pathways. Furthermore, the anti-inflammatory effects of momordicine I are pivotal. Momordicine I might reduce inflammation through the following mechanisms: inhibiting pro-inflammatory cytokines, reducing adhesion molecules expression, suppressing NF-κB activation, modulating the Nrf2 pathway and suppressing c-Met/STAT3 pathway. However, its therapeutic use requires the careful consideration of potential side effects, contraindications, and drug interactions. Future research should focus on elucidating the precise mechanisms of momordicine I, validating its efficacy and safety through clinical trials, and exploring its pharmacokinetics. If proven effective, momordicine I could considerably affect clinical cardiology by acting as a novel adjunct or alternative therapy for cardiovascular diseases. To date, no review article has been published on the role of bitter-melon bioactive metabolites in cardiovascular prevention and therapy. The present work constitutes a comprehensive, up-to-date review of the literature, which highlights the promising therapeutic potential of momordicine I on the cardiovascular system and discusses future research recommendations.

A Simple Eco-Friendly HPLC-PDA Method for the Simultaneous Determination of Paclitaxel and Seliciclib in Plasma Samples for Assessing Their Pharmacodynamics and Pharmacokinetics in Combination Therapy for Uterine Sarcoma.

Background/Objectives: Uterine sarcoma, a rare cancer originating in the smooth muscle of the uterus, exhibits high rates of recurrence and metastasis. It represents one of the most challenging types of cancer due to its chemorefractory nature, showing little response to conventional chemotherapy methods and displaying a relative survival rate of 30-40%. A potentially promising approach for treating uterine sarcoma involves combination therapy with paclitaxel (PAC), a microtubule-targeting agent, and seliciclib (SEL), a cyclin-dependent kinase inhibitor. SEL has been identified as a drug that can enhance the effectiveness of PAC through synergistic effects. To further refine this treatment strategy, an efficient analytical tool capable of simultaneously measuring the concentrations of PAC and SEL in blood plasma is needed. This tool would make it easier to study the pharmacokinetic interactions of potential drugs and assist in monitoring therapy when administering this combination treatment. Regrettably, a method meeting these specific requirements has not been documented in the existing literature. Methods: This article introduces the first HPLC technique employing a PDA detector to concurrently measure PAC and SEL levels in plasma. The methodology underwent validation in accordance with the ICH standards for validating bioanalytical methods. Results: The method exhibited linearity in the concentrations ranging from 0.8 to 100 µg mL-1 for both PAC and SEL. The limits of quantification were determined and found to be 1.34 and 1.25 µg mL-1 for PAC and SEL, respectively. All the other validation criteria conformed to the ICH validation standards. The HPLC-PDA method was successfully employed to quantify both PAC and SEL in plasma samples with a high level of reliability (in terms of accuracy and precision). The eco-friendliness of the approach was verified using three thorough assessments. This technique serves as a valuable asset in establishing the correct dosage and administration schedule for the combined treatment involving PAC and SEL, ensuring the desired therapeutic effects and safety in managing uterine sarcoma. Conclusions: The proposed HPLC-PDA method is the first reliable and eco-friendly method developed to simultaneously determine PAC and SEL in high-throughput plasma samples in clinical laboratories.