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Levosulpiride and omeprazole are co-prescribed for gastrointestinal disorders associated with depression and anxiety. Objective of the study was to develop a sensitive, robust and simple method for simultaneous analysis of levosulpiride and omeprazole in human plasma and applicability of the method in determination of pharmacokinetics drug-drug interaction. In the presented study, a reversed-phase HPLC-UV method was developed for the simultaneous determination of levosulpiride and omeprazole using pantoprazole as the internal standard. Experimental conditions were optimized and the developed method was validated as per standard guidelines (USP and ICH). Furthermore, the developed method was applied for evaluation of pharmacokinetics drug-drug interaction between levosulpiride (50 mg) and omeprazole (40 mg) in healthy human volunteers. Sharpsil C8 column (4.6 × 250 mm, 5 μm), Ultisil C8 column (4.6 mm × 150 mm, 5 μm) and Agilent C18 column (4.6 × 250 mm, 5 μm) were evaluated as stationary phase. The best resolution was achieved with Agilent C18 (4.6 x 250 mm, 5 μm) column and was selected for further study. The mobile phase consisted of a mixture of acetonitrile and phosphate buffer (pH 7.2) in 60:40 by volume, and was pumped at a flow rate of 1 mL/min. Detector wavelength was set at 280 nm. Levosulpiride and omeprazole were extracted from human plasma with ethyl acetate and dichloromethane (4:1, v/v). The calibration curves for both levosulpiride (5–150 ng/mL) and omeprazole (10–1500 ng/mL) were linear. The lower limit of quantification and limit of detection for levosulpiride were 5 and 2 ng/mL, while for omeprazole these were 10 and 3 ng/mL, respectively. Pharmacokinetics analysis showed that co-administration of omeprazole increased the AUC and Cmax of levosulpiride, while the clearance was reduced. Both the changes were insignificant. Similarly, no significant change in the pharmacokinetic parameters of omeprazole was observed with co-administration of levosulpiride. [ABSTRACT FROM AUTHOR]

Drug-drug interaction (DDI) is the combined effects of multiple drugs taken together, which can either enhance or reduce each other's efficacy. Thus, drug interaction analysis plays an important role in improving treatment effectiveness and patient safety. It has become a new challenge to use computational methods to accelerate drug interaction time and reduce its cost-effectiveness. The existing methods often do not fully explore the relationship between the structural information and the functional information of drug molecules, resulting in low prediction accuracy for drug interactions, poor generalization, and other issues. In this paper, we propose a novel method, which is a deep graph contrastive learning model for drug-drug interaction prediction (DeepGCL for brevity). DeepGCL incorporates a contrastive learning component to enhance the consistency of information between different views (molecular structure and interaction network), which means that the DeepGCL model predicts drug interactions by integrating molecular structure features and interaction network topology features. Experimental results show that DeepGCL achieves better performance than other methods in all datasets. Moreover, we conducted many experiments to analyze the necessity of each component of the model and the robustness of the model, which also showed promising results. The source code of DeepGCL is freely available at https://github.com/jzysj/DeepGCL. [ABSTRACT FROM AUTHOR]

Several statistical methods have been proposed to detect adverse drug reactions induced by taking two drugs together. These suspected adverse drug reactions can be discovered through post-market drug safety surveillance, which mainly relies on spontaneous reporting system database. Most previous studies have applied statistical models to real world data, but it is not clear which method outperforms the others. We aimed to assess the performance of various detection methods by implementing simulations under various conditions. We reviewed proposed approaches to detect signals indicating drug-drug interactions (DDIs) including the Ω shrinkage measure, the chi-square statistic, the proportional reporting ratio, the concomitant signal score, the additive model and the multiplicative model. Under various scenarios, we conducted a simulation study to examine the performances of the methods. We also applied the methods to Korea Adverse Event Reporting System (KAERS) data. Of the six methods considered in the simulation study, the Ω shrinkage measure and the chi-square statistic with threshold = 2 had higher sensitivity for detecting the true signals than the other methods in most scenarios while controlling the false positive rate below 0.05. When applied to the KAERS data, the two methods detected one known DDI for QT prolongation and one unknown (suspected) DDI for hyperkalemia. The performance of various signal detection methods for DDI may vary. It is recommended to use several methods together, rather than just one, to make a reasonable decision. [ABSTRACT FROM AUTHOR]

The Cytochrome P450 (CYP) enzymes metabolize a variety of drugs, which may potentially lead to toxicity or reduced efficacy when drugs are co-administered. These drug-drug interactions are often manifested by CYP3A4, the most prevalent of all CYP isozymes. We carried out multiple MD simulations employing CAVER to quantify the channels, and Hidden Markov Models (HMM) to characterize the behavior of the gating residues. We discuss channel properties, bottleneck residues with respect to their likelihood to deem the respective channel ingress or egress, gating residues regarding their open or closed states, and channel location relative to the membrane. Channels do not display coordinated motion and randomly transition between different conformations. Gateway residues also behave in a random fashion. Our findings shed light on the equilibrium behavior of the gating residues and channels in the apo state. [ABSTRACT FROM AUTHOR]

Background: Herbal supplements (HSs) are used to treat a variety of diseases and ailments. Individuals with chronic diseases are at a higher risk of having adverse events and drug interactions from the use of HSs. Aim: This study determined the beliefs, awareness, use, and factors associated with HSs usage among patients with chronic diseases in Alkharj, Saudi Arabia. Method: A cross-sectional study was conducted among patients with chronic diseases between February and June 2019. Face-to-face interviews were conducted at various out-patient clinics in different hospitals. Patients diagnosed with chronic diseases were included in the study. Data were analyzed by descriptive, comparative, and inferential statistics using SAS ver. 9.4. Results: The study participants were consisted of 533 patients, with mean age 53.6 ±12.9 years. The most prevalent chronic diseases were diabetes mellitus (67.7%), followed by hypertension (54.8%), and hyperlipidemia (53.8%). Among the studied participants, 336 (63%) had used at least one HS, whereby the most commonly used HSs were ginger (74.7%), mint (72%), and cumin (66.7%). Almost 78% of HSs users did not consult any healthcare provider about their use. HSs use varied significantly between female and male participants (p<0.05), whereby 61.5% of female participants used HSs in comparison to the male participants (38.5%). Gender (AOR 0.328; 95% CI 0.139–0.772; p = 0.0107), number of chronic diseases (AOR 1.585; 95% CI 1.084–2.318; p = 0.0312), and hyperlipidemia (AOR 2.818; 95% CI 1.507–5.269; p = 0.0.0012) were the pure factors of HSs use among the studied patients. Conclusion: The results of this study showed that HSs usage was high among patients with chronic diseases in Saudi Arabia. Concurrent usage of HSs with drugs should be well-discussed with healthcare providers to avoid potential adverse events or drug interactions especially among patients with chronic diseases. [ABSTRACT FROM AUTHOR]

Drug checking services (DCS) enable individuals to voluntarily submit a small amount of a substance for analysis, providing information about the content of the substance along with tailored harm reduction support and advice. There is some evidence suggesting that DCS may lead to behaviour and system change, with impacts for people who use drugs, staff and services, and public health structures. The evidence base is still relatively nascent, however, and several evidence gaps persist. This paper reports on qualitative interviews with forty-three participants across three Scottish cities where the implementation of community-based DCS is being planned. Participants were drawn from three groups: professional participants; people with experience of drug use; and affected family members. Findings focus on perceived harm reduction impacts of DCS delivery in Scotland, with participants highlighting the potential for drug checking to impact a number of key groups including: individual service users; harm reduction services and staff; drug market monitoring structures and networks; and wider groups of people who use and sell drugs, in shaping their interactions with the drug market. Whilst continued evaluation of individual health behaviour outcomes is crucial to building the evidence base for DCS, the findings highlight the importance of extending evaluation beyond these outcomes. This would include evaluation of processes such as: information sharing across a range of parties; engagement with harm reduction and treatment services; knowledge building; and increased drug literacy. These broader dynamics may be particularly important for evaluations of community-based DCS serving individuals at higher-risk, given the complex relationship between information provision and health behaviour change which may be mediated by mental and physical health, stigma, criminalisation and the risk environment. This paper is of international relevance and adds to existing literature on the potential impact of DCS on individuals, organisations, and public health structures. [ABSTRACT FROM AUTHOR]

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to a wide range of acute and chronic complications including long COVID, a well-known chronic sequela. Long COVID often necessitates long-term treatment, which may lead to an increased potential for drug–drug interactions (DDIs). The objective of this study was to assess potential DDIs among frequently prescribed medications in long COVID by using two electronic databases. Sixty frequently prescribed agents were selected from Thailand's National List of Essential Medicine 2022 for potential DDI analysis by Micromedex and Drugs.com. From these databases, 488 potential DDIs were identified. There were 271 and 434 DDI pairs based on Micromedex and Drugs.com, respectively. Among these DDIs, 77 pairs were labeled as contraindicated or major by both databases. The most common mechanisms for these serious interactions are cytochrome P450 (CYP) inhibition (45%), CYP induction (19%), and QT interval prolongation (7.8%). Based on Fleiss' kappa (0.073), there was only slight agreement of the DDI severity classifications between these two databases. In conclusion, a large number of potential DDIs were detected among frequently prescribed medications for long COVID. Health care providers should be aware of these DDIs, particularly those that are deemed as contraindicated or major. These DDIs are most likely to cause significant adverse events in patients with long COVID because polypharmacy is common. [ABSTRACT FROM AUTHOR]

Drug-drug interactions (DDIs) are a critical component of drug safety surveillance. Laboratory studies aimed at detecting DDIs are typically difficult, expensive, and time-consuming; therefore, developing in-silico methods is critical. Machine learning-based approaches for DDI prediction have been developed; however, in many cases, their ability to achieve high accuracy relies on data only available towards the end of the molecule lifecycle. Here, we propose a simple yet effective similarity-based method for preclinical DDI prediction where only the chemical structure is available. We test the model on new, unseen drugs. To focus on the preclinical problem setting, we conducted a retrospective analysis and tested the models on drugs that were added to a later version of the DrugBank database. We extend an existing method, adjacency matrix factorization with propagation (AMFP), to support unseen molecules by applying a new lookup mechanism to the drugs' chemical structure, lookup adjacency matrix factorization with propagation (LAMFP). We show that using an ensemble of different similarity measures improves the results. We also demonstrate that Chemprop, a message-passing neural network, can be used for DDI prediction. In computational experiments, LAMFP results in high accuracy, with an area under the receiver operating characteristic curve of 0.82 for interactions involving a new drug and an existing drug and for interactions involving only existing drugs. Moreover, LAMFP outperforms state-of-the-art, complex graph neural network DDI prediction methods. [ABSTRACT FROM AUTHOR]

Background: In Switzerland, 20,000 people are hospitalized each year as result of drug related problems (DRPs). The sources of DRPs can be related to patients' behavior (i.e., wrong administration) or to health processes (i.e., drug-drug interaction). No community pharmacy (CP) service focus on DRPs related to patients' behavior is currently recognized or remunerated in Switzerland. A medication review with follow up (MRF) has been developed to evaluate prescription and non-prescription medication. Objective: To evaluate the impact of MRF service for the identification and management DRPs associated to patients' behavior and to describe pharmaceutical interventions carried out through MRF. Methods: A pre-post intervention study with a cluster design and one intervention group will be carried out in CPs in the canton of Vaud (Switzerland) for 15 months. Volunteer pharmacists will be trained on the identification and management of DRPs related to patients' behavior. After training, they will include randomly selected adults taking four or more chronic drugs prescribed for at least three months prior to recruitment. Then, they will conduct three pharmacist-patient face-to-face consultations at 6-month intervals. Tasks will be differentiated by pharmacy technician or pharmacist to triage expired medication or to manage DRPs in a structured manner, respectively. The primary outcome is the identification of DRPs associated to patients' behavior. Secondary outcomes are to assess patients' medication knowledge, number of expired medications, interventions carried out by pharmacists and pharmacists' satisfaction. The study will begin in April 2023 in 19 to 35 pharmacies that will recruit at least 162 patients. A sub analysis will be carried out for patients with 65 years old or over. Conclusions: The MRF intervention features a training designed for an enhanced evaluation of patient's behavior towards their medication. The study will allow the assessment and management of DRPs in Swiss CPs with the support of the local health authorities and pharmacist association. Trial registration: Clinicaltrials.gov NCT05348538. [ABSTRACT FROM AUTHOR]

Introduction: Chronic kidney disease (CKD) is a significant public health challenge due to its rising incidence, mortality, and morbidity. Patients with kidney diseases often suffer from various comorbid conditions, making them susceptible to potential drug-drug interactions (pDDIs) due to polypharmacy and multiple prescribers. Inappropriate prescriptions for CKD patients and their consequences in the form of pDDIs are a major challenge in Pakistan. Aim: This study aimed to compare the incidence and associated risk factors of pDDIs among a public and private sector hospital in Khyber Pakhtunkhwa, Pakistan. Method: A retrospective cross-sectional study design was conducted to compare pDDIs among public and private sector hospitals from January 2023 to February 2023. Patients profile data for the full year starting from January 1 2022 to December 302022, was accessed All adult patients aged 18 years and above, of both genders, who currently have or have previously been diagnosed with end-stage renal disease (ESRD) were included. For assessing pDDIs, patient data was retrieved and checked using Lexicomp UpToDate® for severity and documentation of potential drug-drug interactions. Results: A total of 358 patients' data was retrieved (with n = 179 in each hospital); however, due to incomplete data, n = 4 patients were excluded from the final analysis. The prevalence of pDDIs was found to be significantly higher in private hospitals (84.7%) than in public hospitals (26.6%), with a p-value <0.001. Patients in the age category of 41–60 years (AOR = 6.2; p = 0.008) and those prescribed a higher number of drugs (AOR = 1.2; p = 0.027) were independently associated with pDDIs in private hospitals, while the higher number of prescribed drugs (AOR = 2.9; p = <0.001) was an independent risk factor for pDDIs in public hospitals. The majority of pDDIs (79.0%) were of moderate severity, and a significant number of patients (15.1%) also experienced major pDDIs, with a p-value <0.001. The majority of pDDIs had fair documentation for reliability rating in both public and private hospitals. Conclusion: The prevalence of pDDIs was higher among CKD patients at private hospitals, and most of the pDDIs were of moderate severity. A considerable number of patients also experienced major pDDIs. The risk of experiencing pDDIs was found to be higher in older patients and among those prescribed a higher number of drugs. [ABSTRACT FROM AUTHOR]

Background: Pharmacotherapy is necessary for many people with psychiatric disorders and polypharmacy is common. The psychotropic drug-drug interaction (DDI) should be concerned and efficiently monitored by a proper instrument. Objectives: This study aimed to investigate the prevalence and associated factors of psychotropic DDI and to compare the identification utility from three databases: Drugs.com®, Lexicomp®, and Epocrates®. Methods: This was a retrospective cohort design. We collected demographic and clinical data of all patients hospitalised in the psychiatric inpatient unit in 2020. Psychotropic DDI profiles were examined through three databases. Descriptive statistics were used to report comprehensiveness of each database and prevalence of psychotropic DDI. The Fleiss' kappa index would be analysed to indicate agreement strength of DDI severity classification among three databases. Results: From 149 total admissions, the psychotropic DDIs were found in 148 admissions (99.3%). Thorough the study, there were 182 of both psychotropic and other agents prescribed under 1,357 prescriptions. In total, 2,825 psychotropic DDIs were identified by using Drugs.com® 2,500 times, Epocrates® 2,269 times, and Lexicomp® 2,265 times. Interactions with clonazepam was the three most frequent agents when co-administrated with quetiapine (n = 56), risperidone (n = 36), and valproic acid and derivatives (n = 36). Serious DDIs were comparatively lower in incidence and there was no evidence of its association with reported clinical adverse consequences. The study revealed slight and fair agreement regarding severity classification among the three databases was found. DDI events detected by Drugs.com® were greatest in number, but Lexicomp® provided the broadest list of medications prescribed in our study. Conclusion: Among three databases, interactions detected by Drugs.com® were greatest in number, whereas Lexicomp® provided the broadest list of medications. Development of such databases, based on both theoretical and clinical conceptions, should be focused to balance safety of patients and weariness of healthcare providers. [ABSTRACT FROM AUTHOR]

Despite an increase in the use of targeted anticancer drugs and immunotherapy, cytotoxic anticancer drugs such as docetaxel continue to play a clinically important role. The aim of this study was to evaluate drug–drug interactions between docetaxel and coadministered medicines in patients with breast cancer a claims database. The Health Insurance Review and Assessment Service (HIRA) database (2017 to 2019) was used in this study. We evaluated the risk of neutropenia (defined using receipt of granulocyte colony-stimulating factor (G-CSF) prescriptions) under docetaxel administration or the coadministration of docetaxel and an interacting anticancer drug (predefined based on approval information obtained from the Korean Ministry of Food and Drug Safety and the Lexicomp electronic database). The propensity score matching method was applied to balance covariates in the case (patients with G-CSF prescriptions) and control (patients without G-CSF prescriptions) groups. We identified 947 female patients with breast cancer prescribed with docetaxel and excluded 321 patients based on inclusion criteria. Of the remaining 626 patients, 280 were assigned to the case group and 346 to the control group. Predefined drugs were coadministered to 71 (11.3%) patients during the 7-day period before and after the administration of docetaxel. Adjusted odds ratios (ORs) calculated using the logistic regression model applied to the propensity score matching showed no significant difference between the administration of docetaxel alone and docetaxel coadministration (adjusted OR, 2.010; 95% confidence interval, 0.906, 4.459). In conclusion, we suggest that coadministration of docetaxel and a predefined interacting drug are not associated with G-CSF prescription. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article published in PLoS ONE. The correction addresses concerns about the relationship between the published article and a previously published article that was cited in it. The two studies have different objectives but are part of the same larger project. The correction also mentions that certain data describing a group of herbal supplement users were duplicated in the figures and tables of both articles. The authors apologize for this omission and provide corrected citations for a reference in the introduction. Additionally, the Data Availability statement for the article was incorrect, and the correct data are provided in a separate file. [Extracted from the article]

Busulfan (Bu) is an alkylating agent commonly used at high doses in the preparative regimens of hematopoietic stem cell transplantation (HSCT). It has been shown that such high doses of Bu are associated with generalized seizures which are usually managed by prophylactic antiepileptic drugs (AEDs) such as valproic acid (VPA). Being a strong enzyme inhibitor, VPA may inhibit Bu metabolism and thus increase its potential toxicity. Despite its clinical relevance, the potential interaction between Bu and VPA has not yet been evaluated. The aim of the present study was to assess and evaluate the potential drug-drug interaction (DDI) between Bu and VPA. This study was carried out by incubating Bu in laboratory-prepared rat liver-subcellular fractions including S9, microsomes, and cytosol, alone or in combination with VPA. The liver fractions were prepared by differential centrifugation of the liver homogenate. Analysis of Bu was employed using a fully validated LC-MS/MS method. The validation parameters were within the proposed limits of the international standards guidelines. Bu metabolic stability was assessed by incubating Bu at a concentration of 8 μg/ml in liver fractions at 37°C. There were significant reductions in Bu levels in S9 and cytosolic fractions, whereas these levels were not significantly (P ˃ 0.05) changed in microsomes. However, in presence of VPA, Bu levels in S9 fraction remained unchanged. These results indicated, for the first time, the potential metabolic interaction of Bu and VPA being in S9 only. This could be explained by inhibiting Bu cytosolic metabolism by the interaction with VPA either by sharing the same metabolic enzyme or the required co-factor. In conclusion, the present findings suggest, for the first time, a potential DDI between Bu and VPA in vitro using rat liver fractions. Further investigations are warranted in human-derived liver fractions to confirm such an interaction. [ABSTRACT FROM AUTHOR]

Patients suffering from chronic diseases are more likely to experience pDDIs due to older age, prolonged treatment, severe illness and greater number of prescribed drugs. The objective of the current study was to assess the prevalence of pDDIs and risk factors associated with occurrence of pDDIs in chronic disease patients attending outpatient clinics for regular check-ups. Patients suffering from diabetes, chronic obstructive pulmonary disease (COPD), stroke and osteoporosis were included in the study. This study was a cross sectional, observational, prospective study that included 337 patients from outpatient clinics of respiratory ward, cardiac ward and orthopedic ward of Nishter Hospital Multan, Pakistan. The mean number of interactions per patient was 1.68. A greater risk for occurrence of pDDI was associated with older age ≥ 60 years (OR = 1.95, 95% CI = 1.44–2.37, p<0.001); polypharmacy (≥ 5 drugs) (OR = 3.74, 95% CI 2.32–4.54, p<0.001); overburden (OR = 2.23, 95% CI = 1.64–3.16, p<0.01); CCI score (OR = 1.28, 95% CI = 1.04–1.84, p<0.001); multiple prescribers to one patient (OR = 1.18, 95% CI = 1.06–1.41, p<0.01); and trainee practitioner (OR = 1.09, 95% CI = 1.01–1.28, p<0.01). Old age, polypharmacy, overburden healthcare system, higher comorbidity index, multiple prescribers to one patient and trainee practitioner were associated with increased risk of occurrence of pDDIs in chronic disease patients. [ABSTRACT FROM AUTHOR]

Background: Misunderstanding dosage instructions in terms of dose, frequency, duration, or any other instruction with patients on polypharmacy is a common problem that leads to the irrational use of medications. This study aimed to assess the level of misunderstanding of dosing instructions among patients with chronic diseases receiving polypharmacy at the chronic outpatient pharmacy of the University of Gondar Compressive Specialized Hospital (UoGCSH). Methods: An institutional-based cross-sectional survey was conducted from September to November 2021 at the UoGCSH chronic outpatient pharmacy in Northwest Ethiopia. Study subjects were selected by a systematic random sampling method. Drug-drug and drug-food interactions were also checked by Medscape and drug.com to evaluate the significance of interactions. Frequency, percentage, and mean standard deviation (SD) were used to describe the distributions of variables. With a statistical significance level of p < 0.05, the Chi-square test was used to assess the association of variables with the primary outcome. Results: From a total of 400 participants, more than half (59%) were females, with a mean (SD) age of 57 (±16.3) years old. The study revealed that almost half (50.8%) of the participants misunderstood at least one dosage instruction, and around two-fifths (38.5%) misunderstood the frequency of drug administration. More than 90% of patients had no understanding of drug-drug interactions (DDIs). Sex (X2 = 16.837; P<0.0001), educational level (X2 = 50.251; P < 0.0001), residence (X2 = 5.164; P < 0.023) and duration of stay on medication (X2 = 13.806; P < 0.0003) were significantly associated with misunderstanding of dosage regimen instructions. Conclusion: The study showed that a significant number of patients did not understand their medication dosage regimen instructions. To address these significant drug-related issues, healthcare providers could effectively engage in interventions such as written instructions accompanying patients and additional counseling. [ABSTRACT FROM AUTHOR]

Introduction: Patients frequently use gastric acid-reducing agents (ARAs) to treat symptoms affecting the gastrointestinal tract. Thus, the risk for drug–drug interactions (DDI) is a serious concern. This potentially makes the community pharmacist (CP) act as a primary intervention by providing the appropriate counseling and dispensing practice. Objective: To evaluate CPs' counseling and dispensing practices regarding complaints of Gastroesophageal Reflux Disease (GERD), including recommending an appropriate course of action to prevent possible DDIs. Materials and methods: A simulated patient (SP) methodology was used in this study. The community pharmacies in Ajman and Sharjah were visited by SP who's responsible for acting as a patient, and by an observer who's responsible for focusing on the interaction between the SP and the CPs without engagement. Data were recorded using a preprepared data collection form. Performance feedback was sent to the CPs after concluding all visits. Counseling and dispensing scores were classified based on the total scores to poor, inadequate, and complete. Appropriateness of the pharmacist's decision was defined as dispensing antacid and advising of separating doses apart in time. Results: A total of 150 community pharmacies was included in the data analysis. The findings of the current study demonstrated poor counseling and dispensing for the vast majority of the participants (81.3% and 67.3% of respondents, respectively). Only 4% of the CPs advised the SP to have a time interval between antacid and cefuroxime axetil. A significant difference in counseling scores was found between pharmacies located in Ajman and Sharjah (p = 0.01). Also, there was a significant difference in dispensing scores between independent and chain pharmacies (p = 0.003). Conclusions: The findings revealed inadequate counseling and dispensing practice by CPs. This study highlighted the need for continuous professional training programs to endow the CPs with the knowledge necessary for improving the CPs' counseling and dispensing practices. [ABSTRACT FROM AUTHOR]

Background: Drug-induced nephrotoxicity is a relatively common preventable cause of acute kidney injury (AKI), providing early recognition and management. The pharmacokinetics or pharmacodynamics of drug-drug interactions may lead to additive or synergistic toxicity. The influx of new medications or off-label use of medications in the critical care setting can lead to additional nephrotoxicities, often challenging to predict or detect. This study evaluates the patterns of medication utilization, their combinations, and the related associations with AKI. Methods: We utilized correlation-based network analysis (CNA) to investigate the relationship between medications or their combinations with AKI in a large cohort of critically ill patients in a tertiary medical center between 2007 and 2018. Pairwise medication-AKI correlation analysis was performed to evaluate drug synergistic or additive effects. To investigate the inherent nephrotoxicity of medications, we further analyzed medications that were not paired with any other medications within 24 hours before or after their administration time (isolated medication analysis). Results: Among 147,289 ICU admissions, we identified 244 associations among 1,555 unique medication types. In pairwise analysis, 233 significant correlations were found among 13,150,198 medication pair instances. In isolated medication analysis, ten significant AKI associations were noted. When stratified by eGFR level, substantial differences between eGFR<90 vs. eGFR≥90 patients were observed. This highlights a need to determine eGFR as a risk factor for nephrotoxicity assessment when drug interactions are considered. Conclusions: This large-scale cohort study identified an artificial intelligence model to identify patient-agnostic relationships between medication or their pairs with AKI incidence among critically ill patients. It could be used as a continuous quality assurance tool to monitor drug-associated risk nephrotoxicity. [ABSTRACT FROM AUTHOR]

Low-dose metronomic (LDM) chemotherapy is an alternative to conventional chemotherapy and is the most frequently used approach in low dose chemotherapy regimens. The selection of patients, drug dosages, and dosing intervals in LDM is empirical. In this study, we systematically examined the schedule-dependent interaction of drugs on a breast cancer cell line (BCC) cultured in chambered coverslips. The LDM studies were combined with cell staining in order to better characterize different cell states and cell death modes, including caspase-dependent apoptosis, caspase-independent cell death and autophagy-dependent cell death. Microscope images were examined using the Fiji Trainable Weka Segmentation plugin to analyse cell area in 7500 images showing different modes of cell death. Paclitaxel combined with LDM chemotherapy demonstrated a reduction in the area covered by live cells. In contrast, there was an induction of high levels of cell death due to caspase-dependent apoptosis. [ABSTRACT FROM AUTHOR]

Drug–drug interaction (DDI) prediction has received considerable attention from industry and academia. Most existing methods predict DDIs from drug attributes or relationships with neighbors, which does not guarantee that informative drug embeddings for prediction will be obtained. To address this limitation, we propose a multitype drug interaction prediction method based on the deep fusion of drug features and topological relationships, abbreviated DM-DDI. The proposed method adopts a deep fusion strategy to combine drug features and topologies to learn representative drug embeddings for DDI prediction. Specifically, a deep neural network model is first used on the drug feature matrix to extract feature information, while a graph convolutional network model is employed to capture structural information from the adjacency matrix. Then, we adopt delivery operations that allow the two models to exchange information between layers, as well as an attention mechanism for a weighted fusion of the two learned embeddings before the output layer. Finally, the unified drug embeddings for the downstream task are obtained. We conducted extensive experiments on real-world datasets, the experimental results demonstrated that DM-DDI achieved more accurate prediction results than state-of-the-art baselines. Furthermore, in two tasks that are more similar to real-world scenarios, DM-DDI outperformed other prediction methods for unknown drugs. [ABSTRACT FROM AUTHOR]

Motivation: The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem ID: CID0000005743), baricitinib(Pubchem ID: CID44205240), remdesivir (PubchemID: CID121304016) are three generic drugs that have demonstrated in-vitro high antiviral activity against SARS-CoV-2. The present study aims to widen the search and explore the anti-SARS-CoV-2 properties of these potential drugs while looking for new drug indications with optimised benefits via in-silico research. Method: Here, we designed a unique drug-similarity model to repurpose existing drugs against SARS-CoV-2, using the anti-Covid properties of dexamethasone, baricitinib, and remdesivir as references. Known chemical-chemical interactions of reference drugs help extract interactive compounds withimprovedanti-SARS-CoV-2 properties. Here, we calculated the likelihood of these drug compounds treating SARS-CoV-2 related symptoms using chemical-protein interactions between the interactive compounds of the reference drugs and SARS-CoV-2 target genes. In particular, we adopted a two-tier clustering approach to generate a drug similarity model for the final selection of potential anti-SARS-CoV-2 drug molecules. Tier-1 clustering was based on t-Distributed Stochastic Neighbor Embedding (t-SNE) and aimed to filter and discard outlier drugs. The tier-2 analysis incorporated two cluster analyses performed in parallel using Ordering Points To Identify the Clustering Structure (OPTICS) and Hierarchical Agglomerative Clustering (HAC). As a result, itidentified clusters of drugs with similar actions. In addition, we carried out a docking study for in-silico validation of top candidate drugs. Result: Our drug similarity model highlighted ten drugs, including reference drugs that can act as potential therapeutics against SARS-CoV-2. The docking results suggested that doxorubicin showed the least binding energy compared to reference drugs. Their practical utility as anti-SARS-CoV-2 drugs, either individually or in combination, warrants further investigation. [ABSTRACT FROM AUTHOR]

Polypharmacy may be considered as the customary practice to provide optimum care services to patients but inter resulted in augmented probability of multiple drug interaction. Keeping in view the importance of drug interaction possibility, this study was designed to evaluate the effect of ranitidine on pharmacokinetics of amoxicillin in the local population of Karachi, Pakistan. Amoxicillin and ranitidine are the most commonly prescribed drugs to treat duodenal ulcer caused by Helicobacter pylori. The current investigation was carried out as a single center, open label, two phase, single dose, randomized way in cross over manner to evaluate the potential of pharmacokinetic interaction among amoxicillin formulation and ranitidine in adult healthy male volunteers. Post dosing blood samples were collected at multiple time points that are 0.5, 1, 1.5, 2, 3, 4, 6, 8 and 10 hours after administering amoxicillin 250mg capsule with and without ranitidine. For estimation of amoxicillin concentration in plasma, an HPLC method was developed and validated. The solvent system consisted of 0.025M phosphate buffer: acetonitrile (94:6 v/v). C18 column was employed with a flow rate of 1.0 ml/minute and at 230nm. A linear pattern with a correlation coefficient of 0.999 in the concentration ranges of 25μg/mL to 0.097μg/mL for amoxicillin and 25μg/mL to 0.048μg/mL for ranitidine was observed. Amoxicillin retention time was about 8 minutes and ranitidine retention time was around 12 minutes. Amoxicillin levels were computed and the concentrations were applied to calculate the pharmacokinetic parameters. Pharmacokinetic parameters were estimated by Kinetica TM 4.4.1 (Thermo Electron Corp. USA). The analysis of variance (two way) and t test (two one sided) were applied on log transformed pharmacokinetic parameters of amoxicillin. The Tmax was determined between amoxicillin alone and amoxicillin with ranitidine by Friedman test. The 90% confidence interval values for Cmax(calc) (0.687–0.743) and Tmax(calc) (1.148–1.742) for amoxicillin with or without ranitidine were not found within the FDA acceptable limits of 0.8–1.25. Study demonstrated the significant reduction in peak plasma levels of amoxicillin in presence of ranitidine. It is advisable to administer both drugs with time interval to avoid such interactions and increases in the bactericidal efficacy of amoxicillin. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic, ageing populations and the increasing shortage of skilled workers pose great challenges for the delivery of supplies for people with and without care needs. The potential of drones, as unmanned air vehicles, in healthcare are huge and are discussed as an effective new way to delivery urgent medicines and medical devices, especially in rural areas. Although the advantages are obvious, perspectives of users are important particularly in the development process. Investigating human drone interaction could potentially increase usefulness and usability. The present study aims to perform a systematic scoping review on experimental studies examining the human drone interaction in deliveries of drugs and defibrillators. Methods: Two databases (MEDLINE and CINAHL) and references of identified publications were searched without narrowing the year of publication or language. Studies that investigated the human drone interaction or medical delivery with drones in an experimental manner were included (research articles). All studies that only simulated the delivery process were excluded. Results: The search revealed 83 publications with four studies being included. These studies investigated the user experience of drone delivered defibrillators, but no study was identified that investigated the human drone interaction in the delivery of drugs. Three categories of human drone interaction were identified: landing, handover, and communications. Regarding landing and handover, the most important issue was the direct physical contact with the drone while regarding communications users need clearer instructions about drone´s direction, sound and look like. Discussion: The identified studies used technology-driven approaches by investigating human drone interaction in already existing technologies. Users must become integral part of the whole development process of medical drone services to reduce concerns, and to improve security, usability and usefulness of the system. Human drone interaction should be developed according to the identified categories of human drone interaction by using demand- and technology-driven approaches. [ABSTRACT FROM AUTHOR]

Background: Polypharmacy, defined as the concurrent use of ≥5 medications, increases the risk of drug-drug and drug-disease interactions as well as non-adherence to drug therapy. This may have negative health consequences particularly among older adults due to age-related pharmacokinetic and pharmacodynamic changes. This study aims to uncover the occurrence of polypharmacy among older adults in Denmark and investigate how polypharmacy relates to mortality. Method: This nationwide register-based study included 1,338,058 adults aged 65+ years between January 2013 and December 2017 in Denmark. Polypharmacy prevalence was measured at time of inclusion while incidence and the association between polypharmacy and mortality were measured over the five-year follow-up using Cox regression. In an attempt to adjust for confounding by indication, propensity scores with overlap weighting were introduced to the regression model. Results: At time of inclusion, polypharmacy prevalence was 29% and over the five years follow-up, 47% of the remaining adults transitioned into polypharmacy. Identified risk factors included multimorbidity (2+ morbidities: HR = 3.51; 95% CI = 3.48–3.53), age (95+ years: HR = 2.85; 95% CI = 2.74–2.96), socioeconomic factors (Highest income quartile: HR = 0.81; 95% CI = 0.80–0.81), region of birth region (Non-western migrants: HR = 0.77; 95% CI = 0.75–0.79), marital status (Divorced: HR = 1.10; 95% CI = 1.10–1.12) and year of inclusion (2017: HR = 1.19; 95% CI = 1.19–1.22). Further analyses showed that polypharmacy involves many different drug cocktails with medication for the cardiovascular system (95%), blood and blood-forming organs (69%), alimentary tract and metabolism (61%) and nervous system (54%) contributing the most. After adjustment for propensity scores with OW, both polypharmacy (HR = 3.48, CI95% = 3.41–3.54) and excessive polypharmacy (HR = 3.48, CI95% = 3.43–3.53) increased the risk of death substantially. Conclusion: A considerable proportion of older adults in Denmark were exposed to polypharmacy dependent on health status, socio-economic status, and societal factors. The associated three- to four-fold mortality risk indicate a need for further exploration of the appropriateness of polypharmacy among older adults. [ABSTRACT FROM AUTHOR]

Ciprofol is a novel short-acting intravenous anaesthetic developed in China that is mainly metabolized by cytochrome P450 2B6 (CYP2B6) and uridine diphosphate glucuronosyltransferase 1A9 (UGT1A9). Currently, insufficient evidence is available to support drug‒drug interactions between ciprofol and CYP2B6 inactivators. Here, we established a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method to assess the concentration of ciprofol and investigated the effects of psoralen and clopidogrel on the metabolism of ciprofol in liver microsomes and rats. In rat and human liver microsomes, the median inhibitory concentration (IC50) values of psoralen were 63.31 μmol·L-1 and 34.05 μmol·L-1, respectively, showing mild inhibitory effects on ciprofol metabolism, whereas the IC50 values of clopidogrel were 6.380 μmol·L-1 and 2.565 μmol·L-1, respectively, with moderate inhibitory effects. SD rats were randomly divided into three groups: psoralen (27 mg·kg-1), clopidogrel (7.5 mg·kg-1), and the same volume of 0.5% carboxy methyl cellulose. After 7 days, all rats were injected with 2.4 mg·kg-1 ciprofol. Compared with the control group, the AUC and MRT values of ciprofol in the psoralen and clopidogrel groups were significantly greater, whereas the CL values were significantly lower. In addition, the durations of loss of righting reflex (LORR) in the psoralen and clopidogrel groups were 16.1% and 23.0% longer than that in the control group, respectively. In conclusion, psoralen and clopidogrel inhibit ciprofol metabolism to different degrees and prolong the duration of LORR in rats., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Mucosal-delivered drugs have to pass through the mucus layer before absorption through the epithelial cell membrane. Although there has been increasing interest in polymeric mucins, a major structural component of mucus, potentially acting as important physiological regulators of mucosal drug absorption, there are no reports that have systematically evaluated the interaction between mucins and drugs. In this study, we assessed the potential interaction between human polymeric mucins (MUC2, MUC5B, and MUC5AC) and various drugs with different chemical profiles by simple centrifugal method and fluorescence analysis. We found that paclitaxel, rifampicin, and theophylline likely induce the aggregation of MUC5B and/or MUC2. In addition, we showed that the binding affinity of drugs for polymeric mucins varied, not only between individual drugs but also among mucin subtypes. Furthermore, we demonstrated that deletion of MUC5AC and MUC5B in A549 cells increased the cytotoxic effects of cyclosporin A and paclitaxel, likely due to loss of mucin-drug interaction. In conclusion, our results indicate the necessity to determine the binding of drugs to mucins and their potential impact on the mucin network property., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kishimoto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Drug use implies important challenges related to HIV management, particularly due to an increased risk of potential interactions between antiretroviral therapy (ART) and illicit drugs (pDDIs). This study analyses the prevalence and severity of pDDIs among people living with HIV (PLHIV). It also explores their awareness of pDDIs and their beliefs about the toxicity that they may cause, as well as the impact of pDDIs on selected health variables. We conducted an on-line cross-sectional survey across 33 Spanish hospitals and NGOs to collect demographics and clinical data. pDDIs were checked against the Interaction Checker developed by Liverpool University. The sample of the present study was composed of 694 PLHIV who used illicit drugs. They represented 49.5% of the 1,401 PLHIV that participated in the survey. After excluding 38 participants due to lack of information on their ART or illicit drug use, 335 (51.1%) participants consuming drugs presented with some potentially significant pDDIs between their ART and illicit drugs, with a mean of 2.1±1.7 (1–10) pDDIs per patient. The drugs most frequently involved in pDDIs were cocaine, cannabis, MDMA and nitrates ("poppers"). The prevalence of pDDIs across ART regimens was: protease inhibitors (41.7%); integrase inhibitor-boosted regimens (32.1%), and non-nucleoside reverse transcriptase inhibitors (26.3%). An awareness of pDDIs and beliefs about their potential toxicity correlated positively with intentional non-adherence (p<0.0001). Participants with pDDIs exhibited a higher prevalence of intentional non-adherence (2.19±1.04 vs. 1.93±0.94; p = 0.001). The presence of pDDIs was not associated with poorer results in the clinical variables analysed. A significant proportion of PLHIV who use drugs experience pDDIs, thereby requiring close monitoring. pDDIs should be considered in the clinical management of HIV patients. Adequate information about pDDIs and indicators about how to manage ART when PLHIV use drugs could improve ART non-adherence. [ABSTRACT FROM AUTHOR]

Introduction: The heterogeneity-specific nature of the available colorectal cancer (CRC) biomarkers is significantly contributing to the cancer-associated high mortality rate worldwide. Hence, this study was initiated to investigate a system of novel CRC biomarkers that could commonly be employed to the CRC patients and helpful to overcome the heterogenetic-specific barrier. Methods: Initially, CRC-related hub genes were extracted through PubMed based literature mining. A protein-protein interaction (PPI) network of the extracted hub genes was constructed and analyzed to identify few more closely CRC-related hub genes (real hub genes). Later, a comprehensive bioinformatics approach was applied to uncover the diagnostic and prognostic role of the identified real hub genes in CRC patients of various clinicopathological features. Results: Out of 210 collected hub genes, in total 6 genes (CXCL12, CXCL8, AGT, GNB1, GNG4, and CXCL1) were identified as the real hub genes. We further revealed that all the six real hub genes were significantly dysregulated in colon adenocarcinoma (COAD) patients of various clinicopathological features including different races, cancer stages, genders, age groups, and body weights. Additionally, the dysregulation of real hub genes has shown different abnormal correlations with many other parameters including promoter methylation, overall survival (OS), genetic alterations and copy number variations (CNVs), and CD8+T immune cells level. Finally, we identified a potential miRNA and various chemotherapeutic drugs via miRNA, and real hub genes drug interaction network that could be used in the treatment of CRC by regulating the expression of real hub genes. Conclusion: In conclusion, we have identified six real hub genes as potential biomarkers of CRC patients that could help to overcome the heterogenetic-specific barrier across different clinicopathological features. [ABSTRACT FROM AUTHOR]

Background/objectives: With an aging population suffering from increased prevalence of chronic conditions in the United States (U.S.), a large portion of these patients are on multiple medications. High-risk medications can increase the risk for drug-drug interactions and medication nonadherence. This study aims to describe the prevalence of polypharmacy and high-risk medication prescribing in U.S. physician offices. Methods: This was a cross-sectional study of the Centers for Disease Control and Prevention's National Ambulatory Medical Care Survey from 2009 to 2016. All patients over 65 years old were included. Polypharmacy was categorized as no polypharmacy (< 2 medications), minor polypharmacy (2–3 medications), moderate polypharmacy (4–5 medications), and major polypharmacy (>5 medications). Medications were further categorized into high-risk medication categories (anticholinergics, cardiovascular agents, central nervous system (CNS) medications, pain medications, and other). Comparisons between the degrees of polypharmacy were performed utilizing chi-square or Wilcoxon rank-sum tests with JMP Pro 14® (SAS Institute, Cary, NC). Results: Over 2 billion patient visits were included. Overall, Polypharmacy was common (65.1%): minor polypharmacy (16.2%), moderate polypharmacy (12.1%), and major polypharmacy (36.8%). Patients with major polypharmacy were older compared to those with moderate or minor polypharmacy (75 vs. 73 years, respectively) and were most frequently prescribed pain medications (477.3 per 1,000 total visits). NSAIDs were the most frequently prescribed, with 232.4 per 1,000 total visits resulting in one high-risk NSAID prescription, while 21.9 per 1,000 total visits resulted in two or more high-risk NSAIDs. Conclusion: Most patients over 65 years experienced some degree of polypharmacy, with many experiencing major polypharmacy. This indicates an increased need for expanded pharmacist roles through medication therapy management and safety monitoring in this patient population. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to describe the number and type of drugs used to treat depressive disorders in inpatient psychiatry and to analyse the determinants of potential drug-drug interactions (pDDI) and potentially inappropriate medication (PIM). Methods: Our study was part of a larger pharmacovigilance project funded by the German Innovation Funds. It included all inpatients with a main diagnosis in the group of depressive episodes (F32, ICD-10) or recurrent depressive disorders (F33) discharged from eight psychiatric hospitals in Germany between 1 October 2017 and 30 September 2018 or between 1 January and 31 December 2019. Results: The study included 14,418 inpatient cases. The mean number of drugs per day was 3.7 (psychotropic drugs = 1.7; others = 2.0). Thirty-one percent of cases received at least five drugs simultaneously (polypharmacy). Almost one half of all cases received a combination of multiple antidepressant drugs (24.8%, 95% CI 24.1%–25.5%) or a treatment with antidepressant drugs augmented by antipsychotic drugs (21.9%, 95% CI 21.3%–22.6%). The most frequently used antidepressants were selective serotonin reuptake inhibitors, followed by serotonin and norepinephrine reuptake inhibitors and tetracyclic antidepressants. In multivariate analyses, cases with recurrent depressive disorders and cases with severe depression were more likely to receive a combination of multiple antidepressant drugs (Odds ratio recurrent depressive disorder: 1.56, 95% CI 1.41–1.70, severe depression 1.33, 95% CI 1.18–1.48). The risk of any pDDI and PIM in elderly patients increased substantially with each additional drug (Odds Ratio: pDDI 1.32, 95% CI: 1.27–1.38, PIM 1.18, 95% CI: 1.14–1.22) and severity of disease (Odds Ratio per point on CGI-Scale: pDDI 1.29, 95% CI: 1.11–1.46, PIM 1.27, 95% CI: 1.11–1.44), respectively. Conclusion: This study identified potential sources and determinants of safety risks in pharmacotherapy of depressive disorders and provided additional data which were previously unavailable. Most inpatients with depressive disorders receive multiple psychotropic and non-psychotropic drugs and pDDI and PIM are relatively frequent. Patients with a high number of different drugs must be intensively monitored in the management of their individual drug-related risk-benefit profiles. [ABSTRACT FROM AUTHOR]

Objectives: We sought to determine the prevalence of phosphodiesterase type 5 inhibitor (PDE-5) mediated drug-drug interactions (DDIs) in males with HIV infection receiving antiretroviral therapy (ART) and identify factors associated with PDE-5-mediated DDIs. Methods: Male US Military HIV Natural History Study participants diagnosed with erectile dysfunction (ED) and having a PDE-5 inhibitor and potentially-interacting ART co-dispensed within 30 days were included. DDIs were defined according to criteria found in published guidelines and drug information resources. The primary outcome of interest was overall PDE-5 inhibitor-mediated DDI prevalence and episode duration. A secondary logistic regression analysis was performed on those with and without DDIs to identify factors associated with initial DDI episode. Results: A total of 235 male participants with ED met inclusion criteria. The majority were White (50.6%) or African American (40.4%). Median age at medication co-dispensing (45 years), duration of HIV infection (14 years), and duration of ED (1 year) did not differ between the two groups (p>0.05 for all). PDE-5 inhibitors included sildenafil (n = 124), vardenafil (n = 99), and tadalafil (n = 14). ART regimens included RTV-boosted protease inhibitors (PIs) atazanavir (n = 83) or darunavir (n = 34), and COBI-boosted elvitegravir (n = 43). Potential DDIs occurred in 181 (77.0%) participants, of whom 122 (67.4%) had multiple DDI episodes. The median DDI duration was 8 (IQR 1–12) months. In multivariate analyses, non-statistically significant higher odds of DDIs were observed with RTV-boosted PIs or PI-based ART (OR 2.13, 95% CI 0.85–5.37) and in those with a diagnosis of major depressive disorder (OR 1.74, 95% CI 0.83–3.64). Conclusions: PDE-5-mediated DDIs were observed in the majority of males with HIV infection on RTV- or COBI-boosted ART in our cohort. This study highlights the importance of assessing for DDIs among individuals on ART, especially those on boosted regimens. [ABSTRACT FROM AUTHOR]

Introduction and aim: Comorbidities and comedication are common in patients with hepatitis C, which could result in a risk of drug-drug interaction. The objective of this study was to evaluate the prevalence of comorbidities, comedication and drug-drug interactions involving direct-acting antivirals in this population. Methods: Comorbidities and comedications were evaluated in a retrospective cohort of hepatitis C patients. Drug-drug interactions were estimated in real life and with simulated data on comedications following drug regimens: telaprevir; elbasvir/grazoprevir, ombitasvir/paritaprevir/r/ritonavir (2D regimen), and sofosbuvir/simeprevir, sofosbuvir/daclatasvir, sofosbuvir/ledipasvir; 2D/dasabuvir (3D regimen); glecaprevir/pibrentasvir and sofosbuvir/velpatasvir/voxilaprevir. The interactions were evaluated according to the University of Liverpool database. Statistical analysis was performed by SPSS® 18.0. Results: Data from 1433 patients with hepatitis C were evaluated. The mean patient age was 51.7 years (SD ± 10.7), and 50.6% were female. Direct-acting antivirals were prescribed for 345 (24.1%) patients, and a sustained virological response occurred in 264 (76.5%). The main comorbidities were systemic arterial hypertension [436 (30.4%)], diabetes mellitus [352 (24.6%)] and depression [130 (9.1%)]. The mean number of comorbidities was 1.52 (median [IQR] of 1.00 [1.00–2.00]). The mean number of comedications was 3.16 (median [IQR] of 3.00 [1.00–5.00]). A total of 12916 drug-drug interactions were found, of which 1.859 (14.4%) were high risk, with a mean of 1.29 ± 3.13 per patient. The 3D regimen, as well as glecaprevir/pibrentasvir and sofosbuvir/velpatasvir/voxilaprevir, presented the highest drug-drug interaction indexes. Conclusion: Comorbidities and comedications are common in patients with hepatitis C, as are drug-drug interactions. Even when second generation drugs are used, the occurrence of drug-drug interactions still presents a significant risk. [ABSTRACT FROM AUTHOR]

Despite the high prevalence of potential drug–drug interactions in pediatric intensive care units, their clinical relevance and significance are unclear. We assessed the characteristics and risk factors of clinically relevant potential drug–drug interactions to facilitate their efficient monitoring in pediatric intensive care units. This retrospective cohort study reviewed the medical records of 159 patients aged <19 years who were hospitalized in the pediatric intensive care unit at Seoul National University Hospital (Seoul, Korea) for ≥3 days between August 2019 and February 2020. Potential drug–drug interactions were screened using the Micromedex Drug-Reax® system. Clinical relevance of each potential drug–drug interaction was reported with official terminology, magnitude of severity, and causality, and the association with the patient's clinical characteristics was assessed. In total, 115 patients (72.3%) were exposed to 592 potential interactions of 258 drug pairs. In 16 patients (10.1%), 22 clinically relevant potential drug–drug interactions were identified for 19 drug pairs. Approximately 70% of the clinically relevant potential drug–drug interactions had a severity grade of ≥3. Exposure to potential drug–drug interactions was significantly associated with an increase in the number of administrated medications (6–7 medications, p = 0.006; ≥8, p<0.001) and prolonged hospital stays (1–2 weeks, p = 0.035; ≥2, p = 0.049). Moreover, clinically relevant potential drug–drug interactions were significantly associated with ≥8 prescribed drugs (p = 0.019), hospitalization for ≥2 weeks (p = 0.048), and ≥4 complex chronic conditions (p = 0.015). Most potential drug–drug interactions do not cause clinically relevant adverse outcomes in pediatric intensive care units. However, because the reactions that patients experience from clinically relevant potential drug–drug interactions are often very severe, there is a medical need to implement an appropriate monitoring system for potential drug–drug interactions according to the pediatric intensive care unit characteristics. [ABSTRACT FROM AUTHOR]

Background: The proportion of elderly people living with HIV-1 (PLHIV) is rising. In older patients, comorbidities and concomitant medications are more frequent, increasing the risk of potential drug-drug interactions (PDDIs). Data on the pharmacokinetics of ART in individuals aged ≥ 65 years of age are scarce. We compared plasma drug levels of ART, PDDIs, and side-effects in PLHIV aged ≥ 65 years of age, with controls ≤ 49 years of age. Methods: Patients ≥ 65 years of age and controls ≤ 49 years of age, all of whom were on stable treatment with atazanavir (ATV), darunavir (DRV), or efavirenz (EFV) were included cross-sectionally. Plasma drug levels of ART were analyzed, comorbidities, concomitant medication, adherence, and side-effects recorded, and PDDIs analyzed using drug interactions databases. Results: Between 2013 and 2015, we included 100 individuals ≥ 65 years of age (study group) and 99 controls (≤ 49 years of age). Steady-state DRV concentrations were significantly higher in the study group than in the control group (p = 0.047). In the ATV group there was a trend towards a significant difference (p = 0.056). No significant differences were found in the EFV arm. The DRV arm had a higher frequency of reported side-effects than the ATV and EFV arms in the study group (36.7% vs. 0% and 23.8% respectively (p = 0.014), with significant differences between DRV vs. ATV, and EFV vs. ATV). Conclusions: Higher steady-state plasma levels of DRV and ATV (but not EFV) were found in PLHIV aged ≥ 65 years of age, compared to controls ≤ 49 years of age. [ABSTRACT FROM AUTHOR]

The ability to control cellular functions can bring about many developments in basic biological research and its applications. The presence of multiple signals, internal as well as externally imposed, introduces several challenges for controlling cellular functions. Additionally the lack of clear understanding of the cellular signaling network limits our ability to infer the responses to a number of signals. This work investigates the control of Kaposi's sarcoma-associated herpesvirus reactivation upon treatment with a combination of multiple signals. We utilize mathematical model-based as well as experiment-based approaches to achieve the desired goals of maximizing virus reactivation. The results show that appropriately selected control signals can induce virus lytic gene expression about ten folds higher than a single drug; these results were validated by comparing the results of the two approaches, and experimentally using multiple assays. Additionally, we have quantitatively analyzed potential interactions between the used combinations of drugs. Some of these interactions were consistent with existing literature, and new interactions emerged and warrant further studies. The work presents a general method that can be used to quantitatively and systematically study multi-signal induced responses. It enables optimization of combinations to achieve desired responses. It also allows identifying critical nodes mediating the multi-signal induced responses. The concept and the approach used in this work will be directly applicable to other diseases such as AIDS and cancer.

Globally, usage of non-steroidal anti-inflammatory drugs (NSAIDs) in elderly with chronic pain has been reported as frequent. Though NSAIDs are fundamental in maintaining their quality of life, the risk of polypharmacy, drug interactions and adverse effects is of paramount importance as the elderly usually require multiple medications for their co-morbidities. If prescriptions are not appropriately monitored and managed, they are likely to expose patients to serious drug interactions and potentially fatal adverse effects. This study was conducted to assess the appropriateness of NSAIDs use and determine the risk of NSAIDs related potential interactions in elderly. An analytical cross-sectional study was conducted among elderly out-patients (aged 60 and above) who visited three hospitals in Asmara, Eritrea, between August 22 and September 29, 2018. A stratified random sampling design was employed and data was collected using an interview-based questionnaire and by abstracting information from patients' prescriptions and medical cards. Descriptive and analytical statistics including chi-square test and logistic regression were employed using IBM SPSS (version 22). A total of 285 respondents were enrolled in the study with similar male to female ratio. One in four of all respondents were chronic NSAIDs users and NSAIDs risk practice was reported in 24%. Using chronic NSAIDs without prophylactic gastro-protective agents, self-medication, polypharmacy and drug-drug interactions were the main problems identified. A total of 322 potential interactions in 205 patients were identified and of which, 97.2% were classified as moderate, 0.6% severe and the rest were mild. Those who involved in self-medication were more likely to be exposed to drug interactions. Diabetes (AOR = 2.39, 95% CI: 1.14, 5.02) and hypertension (AOR = 9.06, 95% CI: 4.00, 20.51) were associated with chronic NSAIDs use and incidence of potential drug interactions (AOR = 3.5, 95%CI: 1.68, 4.3; AOR = 2.81, 95%CI: 1.61, 4.9 respectively), while diabetes AOR = 4.5, 95% CI: 2.43, 8.35) and cardiac problems (AOR = 4.29, 95% CI: 1.17, 15.73) were more likely to be associated with incidence of polypharmacy. In conclusion, chronic use of NSAIDs without gastro-protective agents and therapeutic duplication of NSAIDs were commonly which requires attention from programmers, health facility managers and healthcare professionals to safeguard elderlies from preventable harm. [ABSTRACT FROM AUTHOR]

Mixtures of drugs often have greater therapeutic value than any of their constituent drugs alone, and such combination therapies are widely used to treat diseases such as cancer, malaria, and viral infections. However, developing useful drug mixtures is challenging due to complex interactions between drugs. Natural substances can be fruitful sources of useful drug mixtures because secondary metabolites produced by living organisms do not often act in isolation in vivo. In order to facilitate the study of interactions within natural substances, a new analytical method to quantify interactions using data generated in the process of bioassay-guided fractionation is presented here: the extract fractional inhibitory concentration index (EFICI). The EFICI method uses the framework of Loewe additivity to calculate fractional inhibitory concentration values by which interactions can be determined for any combination of fractions that make up a parent extract. The EFICI method was applied to data on the bioassay-guided fractionation of Lechea mucronata and Schinus terebinthifolia for growth inhibition of the pathogenic bacterium Acinetobacter baumannii. The L. mucronata extract contained synergistic interactions (EFICI = 0.4181) and the S. terebinthifolia extract was non-interactive overall (EFICI = 0.9129). Quantifying interactions in the bioassay-guided fractionation of natural substances does not require additional experiments and can be useful to guide the experimental process and to support the development of standardized extracts as botanical drugs. [ABSTRACT FROM AUTHOR]

Aims: This review aims to determine the prevalence of clinically manifested drug-drug interactions (DDIs) in hospitalized patients. Methods: PubMed, Scopus, Embase, Web of Science, and Lilacs databases were used to identify articles published before June 2019 that met specific inclusion criteria. The search strategy was developed using both controlled and uncontrolled vocabulary related to the following domains: "drug interactions," "clinically relevant," and "hospital." In this review, we discuss original observational studies that detected DDIs in the hospital setting, studies that provided enough data to allow us to calculate the prevalence of clinically manifested DDIs, and studies that described the drugs prescribed or provided DDI adverse reaction reports, published in either English, Portuguese, or Spanish. Results: From the initial 5,999 articles identified, 10 met the inclusion criteria. The pooled prevalence of clinically manifested DDIs was 9.2% (CI 95% 4.0–19.7). The mean number of medications per patient reported in six studies ranged from 4.0 to 9.0, with an overall average of 5.47 ± 1.77 drugs per patient. The quality of the included studies was moderate. The main methods used to identify clinically manifested DDIs were evaluating medical records and ward visits (n = 7). Micromedex® (27.7%) and Lexi-Comp® (27.7%) online reference databases were commonly used to detect DDIs and none of the studies evaluated used more than one database for this purpose. Conclusions: This systematic review showed that, despite the significant prevalence of potential DDIs reported in the literature, less than one in ten patients were exposed to a clinically manifested drug interaction. The use of causality tools to identify clinically manifested DDIs as well as clinical adoption of DDI lists based on actual adverse outcomes that can be identified through the implementation of real DDI notification systems is recommended to reduce the incidence of alert fatigue, enhance decision-making for DDI prevention or resolution, and, consequently, contribute to patient safety. [ABSTRACT FROM AUTHOR]

Background: Pharmacists have crucial role in providing drug information and medication counseling to patients. This survey aimed to benchmark the current knowledge of the pharmacists concerning food-drug interactions (FDIs) in Jordan. Methods: A cross-sectional study was conducted in Amman, the capital and largest city of Jordan, using a validated questionnaire. It was distributed to pharmacists working in community and hospital pharmacies using a convenience sampling technique. Descriptive and inferential statistics were performed in this study. Results: A total of 340 questionnaires distributed, 300 (88%) pharmacists responded. Over 50% of pharmacists claimed that they have sufficient knowledge regarding FDI. Virtually, the overall median (interquartile range) knowledge score was 18 (15–21), approximately 60%. The highest knowledge scores were for alcohol-drug interactions section (66.6%) followed by both common food-drug interactions and the timing of drug intake to food consumption sections with a score of (58.3%) for each, reflecting a suboptimal knowledge of FDIs among the pharmacists. Conclusion: Pharmacists had unsatisfactory knowledge about common FDIs, with no significant difference between hospital and community pharmacists. Therefore, more attention and efforts should be played to improve awareness about potential food-drug interactions. [ABSTRACT FROM AUTHOR]

Many drugs are promiscuous and bind to multiple targets. On the one hand, these targets may be linked to unwanted side effects, but on the other, they may achieve a combined desired effect (polypharmacology) or represent multiple diseases (drug repositioning). With the growth of 3D structures of drug-target complexes, it is today possible to study drug promiscuity at the structural level and to screen vast amounts of drug-target interactions to predict side effects, polypharmacological potential, and repositioning opportunities. Here, we pursue such an approach to identify drugs inactivating B-cells, whose dysregulation can function as a driver of autoimmune diseases. Screening over 500 kinases, we identified 22 candidate targets, whose knock out impeded the activation of B-cells. Among these 22 is the gene KDR, whose gene product VEGFR2 is a prominent cancer target with anti-VEGFR2 drugs on the market for over a decade. The main result of this paper is that structure-based drug repositioning for the identified kinase targets identified the cancer drug ibrutinib as micromolar VEGFR2 inhibitor with a very high therapeutic index in B-cell inactivation. These findings prove that ibrutinib is not only acting on the Bruton's tyrosine kinase BTK, against which it was designed. Instead, it may be a polypharmacological drug, which additionally targets angiogenesis via inhibition of VEGFR2. Therefore ibrutinib carries potential to treat other VEGFR2 associated disease. Structure-based drug repositioning explains ibrutinib's anti VEGFR2 action through the conservation of a specific pattern of interactions of the drug with BTK and VEGFR2. Overall, structure-based drug repositioning was able to predict these findings at a fraction of the time and cost of a conventional screen. [ABSTRACT FROM AUTHOR]

Therapeutic resistance plagues cancer outcomes, challenging treatment particularly in aggressive disease. A unique method to decipher drug interactions with their targets and inform therapy is to employ fluorescence-based screening tools; however, to implement productive screening assays, adequate model systems must be developed. Patient-derived pancreatic cancer models (e.g., cell culture, patient-derived xenograft mouse models, and organoids) have been traditionally utilized to predict personalized therapeutic response. However, cost, long read out times and the inability to fully recapitulate the tumor microenvironment have rendered most models incompatible with clinical decision making for pancreatic ductal adenocarcinoma (PDAC) patients. Tumor explant cultures, where patient tissue can be kept viable for up to weeks, have garnered interest as a platform for delivering personalized therapeutic prediction on a clinically relevant timeline. To fully explore this ex vivo platform, a series of studies were completed to quantitatively compare in vivo models with tumor explants, examining gemcitabine therapeutic efficacy, small molecule uptake and drug-target engagement using a novel fluorescently-labeled gemcitabine conjugate. This initial work shows promise for patient-specific therapeutic selection, where tumor explant drug distribution and response recapitulated the in vivo behavior and could provide a valuable platform for understanding mechanisms of therapeutic response and resistance. [ABSTRACT FROM AUTHOR]

The identification of potential interactions between drugs and target proteins is crucial in pharmaceutical sciences. The experimental validation of interactions in genomic drug discovery is laborious and expensive; hence, there is a need for efficient and accurate in-silico techniques which can predict potential drug-target interactions to narrow down the search space for experimental verification. In this work, we propose a new framework, namely, Multi-Graph Regularized Nuclear Norm Minimization, which predicts the interactions between drugs and target proteins from three inputs: known drug-target interaction network, similarities over drugs and those over targets. The proposed method focuses on finding a low-rank interaction matrix that is structured by the proximities of drugs and targets encoded by graphs. Previous works on Drug Target Interaction (DTI) prediction have shown that incorporating drug and target similarities helps in learning the data manifold better by preserving the local geometries of the original data. But, there is no clear consensus on which kind and what combination of similarities would best assist the prediction task. Hence, we propose to use various multiple drug-drug similarities and target-target similarities as multiple graph Laplacian (over drugs/targets) regularization terms to capture the proximities exhaustively. Extensive cross-validation experiments on four benchmark datasets using standard evaluation metrics (AUPR and AUC) show that the proposed algorithm improves the predictive performance and outperforms recent state-of-the-art computational methods by a large margin. Software is publicly available at https://github.com/aanchalMongia/MGRNNMforDTI. [ABSTRACT FROM AUTHOR]

Insomnia is one of the most common minor ailments to which patients seek advice in a community pharmacy setting. Due to the availability of a wide variety of over-the-counter (OTC) products, community pharmacists are in the front line to safe-guard patients looking for self-medication or advice for treatment of insomnia. The purpose of this study was to assess the content of community pharmacists' interactions with patients seeking advice for insomnia in Jordan. A cross-sectional study using a simulated patient methodology was conducted across a stratified convenience sample of community pharmacies in three major cities in Jordan. The visits were evaluated using pre-defined criteria adapted from published literature relating to content and counseling skills. Visits were audio-recorded using a hidden microphone and the simulated patient completed a data collection form immediately after each visit. A total of 67 community pharmacies (response rate = 93.0%) agreed to participate and were all visited once by the simulated patient. The median duration of the visit was 2 minutes (range: 0.2–4 minutes). The majority (86.6%) of visits resulted in the sale of a drug, most commonly a combination product (paracetamol and diphenhydramine) for 30 recommendations (44.8%). This was followed by a natural plant extract combination product, namely valerian and lemon balm (Melissa officinalis L.) for 23 (34.3%). Pharmacists often did not question medical history or other symptoms prior to product sale. Frequently, the recommended dose (49.3%) and administration time (38.8%) were the only information provided to the patient. No information was provided in relation to potential drug interactions or contraindications. No advice was offered on lifestyle or good sleeping hygiene. This study provided evidence that community pharmacists in Jordan in general did not offer adequate counseling for patients seeking advice for insomnia. Exploration of the reasons and factors contributing to this practice and highlighting professional opportunity and responsibility is recommended. [ABSTRACT FROM AUTHOR]

This study aimed to compare and determine the prevalence of drug–drug interaction (DDI) and bleeding rate in atrial fibrillation (AF) patients receiving anticoagulants in a clinical setting. We used large claims data of AF patients obtained from the Japan Medical Data Center. The prevalence of DDIs and cases leading to bleeding events were surveyed clinically relevant DDIs extracted from 1) reported from a spontaneous adverse event reporting system (Japanese Adverse Drug Events Report system; JADER) ≥4 patients; 2) DDIs cited in the package inserts of each anticoagulant (each combination assessed according to "Drug interaction 2015" list; 3) warfarin and quinolone antibiotics DDIs. DDIs were categorized the mechanisms for pharmacokinetic DDI (Cytochrome P450 (CYP) or transporter etc. that modulate blood concentration of anticoagulants)/pharmacodynamic DDI (combination with similar pharmacological actions) or both in the analysis for each patients' prescriptions obtained from a claims data. AF patients were compared between cases with and without bleeding after administered of anticoagulants. Bleeding was observed in 220/3290 (6.7%) AF patients. The bleeding rate in patients with both pharmacokinetic and pharmacodynamic DDI mechanisms (26.3%) was higher than that in patients with either mechanism (8.6% and 9.2%, respectively) or without DDIs (4.9%). The odds ratio for bleeding in AF patients with both of pharmacokinetic and pharmacodynamic was (7.18 [4.69–11.00], p<0.001). Our study concluded multi mechanism based DDIs leads serious outcome as compared to that of single mechanism based DDIs in AF patients. We determined the prevalence and frequency of bleeding for anticoagulant-related DDIs. To manage DDIs, both pharmacokinetic and pharmacodynamic DDI mechanisms should be closely monitored for initial symptoms of bleeding within the first 3 months. [ABSTRACT FROM AUTHOR]

Introduction: Sustained virologic response (SVR) rates in patients with hepatitis C virus (HCV) monoinfection and human immunodeficiency virus (HIV)/HCV coinfection treated with direct acting antiviral (DAA) therapy are similar in clinical trials. The objective of this study was to examine differences in patient characteristics, drug-drug interactions, and treatment pathways between these groups in a real-world clinical setting. Methods: We performed an ambispective review of patients prescribed DAA therapy between September 2015 and April 2018 at a tertiary academic center. The primary endpoint was time from a decision to treat to treatment initiation. Secondary endpoints included patient characteristics; frequency and type of DAA medication interactions; frequency, type, and timing of antiretroviral therapy (ART) changes; and treatment outcomes. Results: Three hundred and twelve patients were included. Almost half (43%) were HIV/HCV coinfected. Patients with HIV/HCV coinfection were more likely to be African American (p<0.001), have a diagnosed psychiatric disorder (p<0.001) and have a higher pill burden (p = 0.014). Patients with HIV/HCV coinfection were more likely to report an alcohol abuse history (p<0.001), injection drug use history (p<0.024), or active use of illicit substances (p = 0.019). In a multivariable regression model assessing the primary endpoint, time to treatment initiation was increased in patients requiring a change in ART therapy (OR = 9.2, p < 0.001) or a non-ART medication adjustment (OR = 2.4, p = 0.003), and in patients with Medicaid (OR = 6.7, p < 0.001). After controlling for all these factors, HIV/HCV coinfection still significantly impacted time to treatment initiation (OR = 1.7, p = 0.020). The groups had similar rates of drug interaction frequency, treatment completion, observed SVR, and side effects. Conclusions: Patients with HIV/HCV coinfection are more likely to have a variety of factors that add complexities to HCV treatment. In addition to these challenges, patients with HIV/HCV coinfection experience a longer time to treatment initiation while patients with HCV monoinfection were more frequently lost to care. Care delivery models may incorporate this data to improve patient engagement, access, and outcomes. [ABSTRACT FROM AUTHOR]

Background: Drug-drug interactions (DDIs) are one of the most common drug-related problems. Recently, electronic databases have drug interaction tools to search for potential DDIs, for example, Micromedex and Drugs.com. However, Micromedex and Drugs.com have different abilities in detecting potential DDIs, and this might cause misinformation to occur between patients and health care providers. Methods and findings: The aim of this study was to compare the ability of Micromedex and Drugs.com to detect potential DDIs with metabolic syndrome medications using the drug list from the U-central database, King Chulalongkorn Memorial Hospital in April 2019. There were 90 available drugs for the treatment of the metabolic syndrome and its associated complications, but six were not found in the Micromedex and Drugs.com databases; therefore, only 84 items were used in the present study. There were 1,285 potential DDI pairs found by the two databases. Micromedex reported DDIs of 724 pairs, while, Drugs.com reported 1,122 pairs. For the severity of the potential DDI reports, the same severity occurred between the two databases of 481 pairs (37.43%) and a different severity for 804 pairs (62.57%). Conclusion: Drugs.com had a higher sensitivity to detect potential DDIs by approximately 1.5-fold, but Micromedex supplied more informative documentation for the severity classification. Therefore, pharmacists should use at least two databases to evaluate potential DDIs and determine the appropriate drug regimens for physician communications and patient consultations. [ABSTRACT FROM AUTHOR]

Effects of steady-state rifabutin on the pharmacokinetics of steady-state maraviroc were investigated in fourteen healthy adult female and male volunteers. Maraviroc 300 mg twice daily (BID) was given orally with food for fifteen days. On day six, rifabutin 300 mg once daily (QD, P.O.) was added to the regimen. Formal pharmacokinetic (PK) sampling was performed on days five and fifteen. Individual plasma drug concentration-time data for maraviroc, and rifabutin on day fifteen, were obtained using validated High Performance Liquid Chromatography (HPLC) tandem Mass Spectrometry (MS/MS). Rifabutin steady state exposure was comparable to data in the literature. Maraviroc area under the curve (AUC) and minimum plasma concentration (Clast or Cmin) were reduced by 17% and 30% respectively when co-administered with rifabutin. No unexpected or serious adverse eventsoccurred. Based on the reduced exposure of maraviroc observed in this study, increasing the dose of maraviroc may be studied to normalize its moderately reduced exposure following rifabutin co-administration, a moderate inducer of CYP3A4. [ABSTRACT FROM AUTHOR]

Recent experimental work has revealed unusual features of the effect of certain drugs on cardiac inwardly rectifying potassium currents, including the constitutively active and acetylcholine-induced components of acetylcholine-sensitive current (IKAch). These unusual features have included alternating susceptibility of the current components to activation and inhibition induced by ethanol or nicotine applied at various concentrations, and significant correlation between the drug effect and the current magnitude measured under drug-free conditions. To explain these complex drug effects, we have developed a new type of quantitative model to offer a possible interpretation of the effect of ethanol and nicotine on the IKAch channels. The model is based on a description of IKAch as a sum of particular currents related to the populations of channels formed by identical assemblies of different α-subunits. Assuming two different channel populations in agreement with the two reported functional IKAch-channels (GIRK1/4 and GIRK4), the model was able to simulate all the above-mentioned characteristic features of drug-channel interactions and also the dispersion of the current measured in different cells. The formulation of our model equations allows the model to be incorporated easily into the existing integrative models of electrical activity of cardiac cells involving quantitative description of IKAch. We suppose that the model could also help make sense of certain observations related to the channels that do not show inward rectification. This new ionic channel model, based on a concept we call population type, may allow for the interpretation of complex interactions of drugs with ionic channels of various types, which cannot be done using the ionic channel models available so far. [ABSTRACT FROM AUTHOR]

Antimicrobial drug concentrations in the gastrointestinal tract likely drive antimicrobial resistance in enteric bacteria. Our objective was to determine the concentration of ceftiofur and its metabolites in the gastrointestinal tract of steers treated with ceftiofur crystalline-free acid (CCFA) or ceftiofur hydrochloride (CHCL), determine the effect of these drugs on the minimum inhibitory concentration (MIC) of fecal Escherichia coli, and evaluate shifts in the microbiome. Steers were administered either a single dose (6.6 mg/kg) of CCFA or 2.2 mg/kg of CHCL every 24 hours for 3 days. Ceftiofur and its metabolites were measured in the plasma, interstitium, ileum and colon. The concentration and MIC of fecal E. coli and the fecal microbiota composition were assessed after treatment. The maximum concentration of ceftiofur was higher in all sampled locations of steers treated with CHCL. Measurable drug persisted longer in the intestine of CCFA-treated steers. There was a significant decrease in E. coli concentration (P = 0.002) within 24 hours that persisted for 2 weeks after CCFA treatment. In CHCL-treated steers, the mean MIC of ceftiofur in E. coli peaked at 48 hours (mean MIC = 20.45 ug/ml, 95% CI = 10.29–40.63 ug/ml), and in CCFA-treated steers, mean MIC peaked at 96 hours (mean MIC = 10.68 ug/ml, 95% CI = 5.47–20.85 ug/ml). Shifts in the microbiome of steers in both groups were due to reductions in Firmicutes and increases in Bacteroidetes. CCFA leads to prolonged, low intestinal drug concentrations, and is associated with decreased E. coli concentration, an increased MIC of ceftiofur in E. coli at specific time points, and shifts in the fecal microbiota. CHCL led to higher intestinal drug concentrations over a shorter duration. Effects on E. coli concentration and the microbiome were smaller in this group, but the increase in the MIC of ceftiofur in fecal E. coli was similar. [ABSTRACT FROM AUTHOR]

Background: Several studies have examined the risk and health outcomes related to polypharmacy among the elderly. However, information regarding polypharmacy among pediatric patients is lacking. Objective: The aim of this study was to investigate the prevalence of polypharmacy and its related factors among the pediatric population of South Korea. Methods: We used national claim data from the Health Insurance Review and Assessment Service—Pediatric Patients Sample (HIRA-PPS) in Korea originating from 2012 through 2016. Polypharmacy was defined as a daily average of two or more drugs used yearly. Complex chronic conditions (CCCs) were examined to evaluate concomitant chronic diseases in pediatric patients. Age-specific contraindications and potential drug-drug interactions were assessed according to criteria established by the Korea Institute of Drug Safety & Risk Management (KIDS). Descriptive statistics and logistic regression were conducted to analyze the status of polypharmacy and its associated risk factors in pediatric patients. Results: The 5-year prevalence of pediatric polypharmacy in pediatric patients was 3.7%. The prevalence of polypharmacy was much higher in younger pediatric patients: 9.5% for patients between the ages of 1–7 years, 0.9% for ages 6–11 years, and 1.1% for ages 12–19 years. Pediatric patients with CCCs, Medical Aid benefits, or a hospital admission history had a significantly higher prevalence of polypharmacy when compared to their counterparts without those conditions. The most commonly prescribed drugs were respiratory agents (29%) followed by anti-allergic drugs (18.7%), central nervous system agents (15.9%), antibiotics (10.1%), and gastrointestinal drugs (7.7%). There was a positive correlation between the daily average number of inappropriate prescriptions and the degree of polypharmacy, especially in pediatric patients between the ages of 1–7 years. Contraindications and potential drug-drug interactions occurred in 11.0% and 10.1% of patients exposed to polypharmacy, respectively. Conclusions: One in ten pediatric patients under the age of 7 years was prescribed two or more concurrent drugs on average per day. Furthermore, pediatric patients exposed to polypharmacy showed an increased risk of inappropriate drug use. The implementation of a medication review system that considers pediatric patient polypharmacy exposure would reduce inappropriate drug use and prevent unwanted adverse outcomes. [ABSTRACT FROM AUTHOR]