Potential Drug-disease Interactions Research Articles

ENHANCING DRUG DISCOVERY THROUGH A META-PATH BASED OVERSAMPLING APPROACH FOR IMBALANCED DATA

This study proposes a new method to improve the efficiency of drug discovery by repurposing existing drugs, aiming to reduce the time and costs associated with traditional drug development processes, which can span 10 to 15 years and cost billions of dollars. Current approaches focus on leveraging heterogeneous data, such as drug-protein and disease-protein interactions, to construct complex networks that link drugs, proteins, and diseases. However, a significant challenge is the imbalance in data, where numerous unconfirmed potential drug-disease interactions (the majority class) outnumber approved drugs (the minority class), severely impacting the predictive performance of machine learning models. Previous attempts to address this issue have shown limited success. This study introduces a novel approach that integrates meta-paths in heterogeneous information networks with data balancing techniques to tackle this imbalance. Experimental results demonstrate that the proposed method enhances model performance and reliability in identifying new relationships between drugs and diseases. This research represents a promising advancement by leveraging network-based strategies and data balancing techniques to facilitate the rediscovery of drug applications, thereby potentially revolutionizing the pharmaceutical industry’s approach to drug development.

Network Pharmacology Analysis of the Therapeutic Potential of Colchicine in Acute Lung Injury.

This study employed integrated network pharmacology approach to explore the mechanisms underlying the protective effect of colchicine against acute lung injury (ALI). We analyzed the expression profiles from 13 patients with sepsis-related ALI and 21 controls to identify differentially expressed genes and key modules. ALI-related genes were curated using databases such as DisGeNET, Therapeutic Target, and Comparative Toxicogenomics Database to curate ALI-related genes. Drug target fishing for colchicine was conducted using the DrugBank, BATMAN-TCM, STITCH, and SwissTargetPrediction. Potential drug-disease interactions were determined by intersecting ALI-associated genes with colchicine target genes. We performed comprehensive pathway and process enrichment analyses on these genes. A protein-protein interaction network was constructed, and topological analysis was executed. Additionally, an ALI mouse model was established to evaluate the effect of colchicine on CXCL12 and CXCR4 levels through western blot analysis. Analysis revealed 23 potential colchicine-ALI interaction genes from the intersection of 253 ALI-associated genes and 389 colchicine targets. Functional enrichment analysis highlighted several inflammation-related pathways, such as cytokine-mediated signaling pathway, CXCR chemokine receptor binding, NF-kappa B signaling pathway, TNF signaling pathway, and IL-17 signaling pathway. The protein-protein interaction network demonstrated complex interactions for CXCL12 and CXCR4 among other candidate genes, with significant topological interaction degrees. In vivo studies showed that colchicine significantly reduced elevated CXCL12 and CXCR4 levels in ALI mice. Our findings suggest that colchicine's therapeutic effect on ALI might derive from its anti-inflammatory properties. Further research is needed to explore the specific mechanisms of colchicine's interaction with sepsis-induced ALI.

Reimagining old drugs with new tricks: Mechanisms, strategies and notable success stories in drug repurposing for neurological diseases.

Recent evolution in drug repurposing has brought new anticipation, especially in the conflict against neurodegenerative diseases (NDDs). The traditional approach to developing novel drugs for these complex disorders is laborious, time-consuming, and often abortive. However, drug reprofiling which is the implementation of illuminating novel therapeutic applications of existing approved drugs, has shown potential as a promising strategy to accelerate the hunt for therapeutics. The advancement of computational approaches and artificial intelligence has expedited drug repurposing. These progressive technologies have enabled scientists to analyse extensive datasets and predict potential drug-disease interactions. By prospecting into the existing pharmacological knowledge, scientists can recognise potential therapeutic candidates for reprofiling, saving precious time and resources. Preclinical models have also played a pivotal role in this field, confirming the effectiveness and mechanisms of action of repurposed drugs. Several studies have occurred in recent years, including the discovery of available drugs that demonstrate significant protective effects in NDDs, relieve debilitating symptoms, or slow down the progression of the disease. These findings highlight the potential of repurposed drugs to change the landscape of NDD treatment. Here, we present an overview of recent developments and major advances in drug repurposing intending to provide an in-depth analysis of traditional drug discovery and the strategies, approaches and technologies that have contributed to drug repositioning. In addition, this chapter attempts to highlight successful case studies of drug repositioning in various therapeutic areas related to NDDs and explore the clinical trials, challenges and limitations faced by researchers in the field. Finally, the importance of drug repositioning in drug discovery and development and its potential to address discontented medical needs is also highlighted.

Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms.

Potential medication errors and related adverse drug events (ADE) pose major challenges in clinical medicine. Clinical decision support systems (CDSSs) help identify preventable prescription errors leading to ADEs but are typically characterized by high sensitivity and low specificity, resulting in poor acceptance and alert-overriding. With this cross-sectional study we aimed to analyze CDSS performance, and to identify factors that may increase CDSS specificity. Clinical pharmacology services evaluated current pharmacotherapy of 314 patients during hospitalization across three units of two Swiss tertiary care hospitals. We used two CDSSs (pharmaVISTA and MediQ), primarily for the evaluation of drug-drug interactions (DDI). Additionally, we evaluated potential drug-disease, drug-age, drug-food, and drug-gene interactions. Recommendations for change of therapy were forwarded without delay to treating physicians. Among 314 patients, automated analyses by both CDSSs produced an average of 15.5 alerts per patient. In contrast, additional expert evaluation resulted in only 0.8 recommendations per patient to change pharmacotherapy. For clinical pharmacology experts, co-factors such as comorbidities and laboratory results were decisive for the classification of CDSS alerts as clinically relevant in individual patients in about 70% of all decisions. Such co-factors should therefore be used for the development of multidimensional CDSS alert algorithms with improved specificity. In combination with local expert services, this poses a promising approach to improve drug safety in clinical practice.

An explainable framework for drug repositioning from disease information network

Exploring efficient and high-accuracy computational drug repositioning methods has become a popular and attractive topic in drug development. This technology can systematically identify potential drug-disease interactions, which could greatly alleviate the pressures from the high cost and long period taken by traditional drug research and discovery. However, plenty of current computational drug repositioning approaches lack interpretability in predicting drug-disease associations, which will not be friendly to their subsequent in-depth research.To this end, we hereby propose a novel computational framework, called EDEN, for exploring explainable drug repositioning from the disease information network (DIN). EDEN is a graph neural network framework that learns the local semantics and global structure of the DIN, and models the drug-disease associations into the DIN by maximizing the mutual information of both and an end-to-end manner. In this way, the learned biomedical entity and link embeddings are enabled to retain the ability to drug repositioning with the semantical structure of external knowledge, thereby making interpretation possible. Meanwhile, we also propose a matching score based on the final embeddings to generate the predictive drug repositioning explanation. Empirical results on the real-world dataset show that EDEN outperforms other state-of-the-art baselines on most of the metrics. Further studies reveal the effectiveness of the explainability of our approach.

COVID-19 and cardiovascular disease: from basic mechanisms to clinical perspectives.

Coronavirus disease 2019 (COVID-19), caused by a strain of coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic that has affected the lives of billions of individuals. Extensive studies have revealed that SARS-CoV-2 shares many biological features with SARS-CoV, the zoonotic virus that caused the 2002 outbreak of severe acute respiratory syndrome, including the system of cell entry, which is triggered by binding of the viral spike protein to angiotensin-converting enzyme 2. Clinical studies have also reported an association between COVID-19 and cardiovascular disease. Pre-existing cardiovascular disease seems to be linked with worse outcomes and increased risk of death in patients with COVID-19, whereas COVID-19 itself can also induce myocardial injury, arrhythmia, acute coronary syndrome and venous thromboembolism. Potential drug–disease interactions affecting patients with COVID-19 and comorbid cardiovascular diseases are also becoming a serious concern. In this Review, we summarize the current understanding of COVID-19 from basic mechanisms to clinical perspectives, focusing on the interaction between COVID-19 and the cardiovascular system. By combining our knowledge of the biological features of the virus with clinical findings, we can improve our understanding of the potential mechanisms underlying COVID-19, paving the way towards the development of preventative and therapeutic solutions.

Therapeutic burden in interstitial lung disease: Lessons to learn.

Patients with interstitial lung disease (ILD) are often prescribed disease-targeted and symptomatic therapies, both of which can cause significant treatment burden due to polypharmacy and drug-disease interactions. This study aimed to evaluate medication regimen complexity before and after introduction of ILD-specific therapies. Potential drug-disease interactions were evaluated for patients who were prescribed prednisolone. In this study, 214 patients with ILD were assessed for demographic information, co-morbidities and medication use. Medication lists were reviewed prior to and after the introduction of ILD-specific therapies. Complexity of treatment regimen was examined using the validated Medication Regimen Complexity Index (MRCI). Of the 214 patients, 75 had idiopathic pulmonary fibrosis (IPF) while the rest had inflammatory ILD (chronic hypersensitivity pneumonitis: 45; connective tissue disease-related ILD: 41). Polypharmacy was common at baseline (IPF: 51%, inflammatory ILD: 63%). Following introduction of ILD-specific therapies, median total MRCI scores significantly increased from 8 (interquartile range (IQR) = 8-15) to 22.5 (17.5-27.5) and 14.5 (8.5-21) to 21.5 (16-30) for IPF and inflammatory ILD groups, respectively (P < 0.0001 for both). Complex dosing instructions contributed the most to total MRCI scores for ILD-specific therapies. Among patients receiving prednisolone (n = 113), 88% had ≥1 co-morbidity which may be impacted. Common co-morbidities included gastrointestinal diseases (56%), obesity (37%), osteoporosis (24%) and diabetes mellitus (18%). Polypharmacy and complex medication regimen are common in patients with ILD of different aetiologies. There is a high frequency of potential drug-disease interactions among patients who are prescribed systemic corticosteroids. These findings highlight the need for careful evaluation of the impact of therapeutic complexity and burden in patients with ILD.

STAT3 is involved in IL-6-Mediated Downregulation of Hepatic Transporters in Mice.

Our objective was to investigate whether IL-6-mediated effects occur through STAT3, and whether PXR plays a role in this regulation. PXR null (-/-) or wild-type (+/+) male mice were pre-dosed with a selective STAT3 inhibitor S3I-201 (7.5 mg/kg ip) or vehicle (n=5-8/group) 30 minutes before receiving a single dose of IL-6 (1 µg ip) or saline. Animals were sacrificed after 6 hours and liver samples were analyzed using qRT-PCR and western blotting. As compared to saline controls, IL-6 decreased the expression of Cyp3a, Abcb1a, Abcc3, and Slco1a4 20-70% similarly in PXR (+/+) and (-/-) mice at 6 hr, while downregulation of Abcb11, Abcc2, Slc10a1and Slco2b1 was only seen in PXR (+/+). Pre-administration of S3I-201 attenuated IL-6-mediated changes of most transporters in PXR (+/+) and PXR (-/-) mice. At early times after IL-6 administration (10-120 minutes), transcript levels of Socs3, PXR, Abcb1a, Abcc3, Abcb11, Slco1a4 and Slco2b1were increased in PXR (+/+) mice. Our findings demonstrate that IL-6 imposes a significant downregulation of numerous ABC and SLC transporters in liver primarily through activation of the STAT3 signaling pathway. Based on time-dependent changes in transporter expression, downregulation likely occurs downstream of STAT3 activation. As IL-6 is elevated in many diseases, understanding the underlying mechanism(s) involved in transporter dysregulation will allow us to predict potential drug-disease interactions.

Consistency and replicability of a pharmacist-led intervention for asthma patients: Italian Medicines Use Review (I-MUR).

Medication review is a common intervention provided by community pharmacists in many countries, but with little evidence of consistency and replicability. The I-MUR utilised a standardised question template in two separate large-scale studies. The template facilitated pharmacists in recording medicines and problems reported by patients, the pharmaceutical care issues (PCIs) they found and actions they took to improve medicines use. Community pharmacists from four cities and across 15 regions were involved in the two studies. Patients included were adults with asthma. Medicines use, adherence, asthma problems, PCIs and actions taken by pharmacists were compared across studies to assess consistency and replicability of I-MUR.FindingsThe total number of pharmacists and patients completing the studies was 275 and 1711, respectively. No statistically significant differences were found between the studies in the following domains: patients' demographic, patients' perceived problems, adherence, asthma medicines used and healthy living advice provided by pharmacists. The proportion of patients in which pharmacists identified PCIs was similar across both studies. There were differences only in the incidence of non-steroidal anti-inflammatory drug use, the frequency of potential drug-disease interactions and in the types of advice given to patients and GPs. The use of a standardised template for the I-MUR may have contributed to a degree of consistency in the issues found, which suggests this intervention could have good replicability.

Involvement of Nuclear Factor κB, not Pregnane X Receptor, in Inflammation-Mediated Regulation of Hepatic Transporters

Endotoxin-induced inflammation decreases the hepatic expression of several drug transporters, metabolizing enzymes, and nuclear transcription factors, including pregnane X receptor (PXR). As the nuclear factor κB (NF-κB) is a major mediator of inflammation, and reciprocal repression between NF-κB and PXR signaling has been reported, the objective of this study was to examine whether NF-κB directly regulates the expression of transporters or exerts its effect indirectly via PXR. PXR-deficient (-/-) or wild-type (+/+) male mice were dosed with the selective NF-κB inhibitor PHA408 (40 mg/kg i.p.) or vehicle (n = 5-8/group), followed by endotoxin (5 mg/kg) or saline 30 minutes later. Animals were sacrificed at 6 hours; samples were analyzed using quantitative reverse-transcription polymerase chain reaction and Western blots. Endotoxin induced tumor necrosis factor-α, interleukin (IL)-6, IL-1β, and inducible nitric oxide synthase in PXR (+/+) and (-/-) mice. As compared with saline controls, endotoxin administration imposed 30%-70% significant decreases in the expression of Abcb1a, Abcb11, Abcc2, Abcc3, Abcg2, Slc10a1, Slco2b1, and Slco1a4 in PXR (+/+) and (-/-) mice to a similar extent. Preadministration of PHA408 attenuated endotoxin-mediated changes in both PXR (+/+) and (-/-) mice (P < 0.05). Our findings demonstrate that endotoxin activates NF-κB and imposes a downregulation of numerous ATP-binding cassette and solute carrier transporters through NF-κB in liver and is independent of PXR. Moreover, inhibition of NF-κB attenuates the impact of endotoxin on transporter expression. As NF-κB activation is involved in many acute and chronic disease states, disease-induced changes in transporter function may be an important source of variability in drug response. This information may be useful in predicting potential drug-disease interactions.

Medication Safety in Primary Care Practice

Reducing medication errors is a fundamental patient safety goal; however, few improvement interventions have been evaluated in primary care settings. The Medication Safety in Primary Care Practice project was designed to test the impact of a multimethod quality improvement intervention on 5 categories of preventable prescribing and monitoring errors in 20 Practice Partner Research Network (PPRNet) practices. PPRNet is a primary care practice-based research network among users of a common electronic health record (EHR). The intervention was associated with significant improvements in avoidance of potentially inappropriate therapy, potential drug-disease interactions, and monitoring of potential adverse events over 2 years. Avoidance of potentially inappropriate dosages and drug-drug interactions did not change over time. Practices implemented a variety of medication safety strategies that may be relevant to other primary care audiences, including use of EHR-based audit and feedback reports, medication reconciliation, decision-support tools, and refill protocols.

Non-prescription medicine use by outpatients of a hospital in north-central Trinidad living with hypertension, and the potential clinical risks

AbstractObjectiveTo describe the reported use of non-prescription medicines (NPMs) and the reported frequency of use by outpatients living with hypertension; to identify potential drug-drug and drug-disease interactions between reported NPMs and either antihypertensives prescribed or hypertension.SettingAdult outpatient clinics of the Eric Williams Medical Sciences Complex Adult Hospital in Trinidad.MethodOutpatients were interviewed about their use of NPMs using a structured instrument. Chi-squared test or Fisher's exact test was used to test for associations between NPM use and selected variables: age group, gender, education level, number of prescribed medicines, use of prescribed medicines and the presence of comorbidities. Combinations of NPMs and antihypertensive drugs or hypertension itself that may lead to undesirable interactions were identified.Key findingsOne hundred and fifty-five clients were interviewed (mean age 61 years; 46% men; 56% of East Indian descent). Of these, 82% were living with a cardiac condition and 60% with diabetes mellitus. In addition, 92% reported using NPMs to treat minor illnesses. Analgesic use was reported by 81%. Some 66% reported using paracetamol, 54% reported antitussives, 48% antacids, 47% antihistamines and 39% said they used sympathomimetic drugs. The majority (98%) of NPMs were used only when needed. Sixty per cent had at least one combination a with risk of interaction with NPMs and hypertension or antihypertensive medicines: 16% had risk of interactions between enalapril (or captopril) and antacids, 13% between angiotensin-converting enzyme (ACE) inhibitors and non-steroidal anti-inflammatory drugs (NSAIDs), 12% between beta-blockers and NSAIDs and 12% between thiazide diuretics and NSAIDs. Thirty-nine per cent had a drug-disease interaction risk due to sympathomimetic drugs and 26% had one due to NSAID use.ConclusionBased on self-reports, outpatients living with hypertension in north-central Trinidad use NPMs when needed to treat minor illnesses, mainly paracetamol for pain. Non-prescription-antihypertensive interactions may arise due to ACE inhibitor/antacid combinations and NPM-hypertension interactions may result from use of sympathomimetics. Interactions may also arise as a result of the use of NPMs containing NSAIDs and sodium.

Assessing the Impact of Substance use and Hepatitis Coinfection on Atazanavir and Lopinavir Trough Concentrations in HIV-Infected Patients During Therapeutic Drug Monitoring

Atazanavir (ATV) and lopinavir (LPV) are widely used HIV-1 protease inhibitors. Like with other protease inhibitors, careful monitoring of potential drug-drug and drug-disease interactions in clinical practice is necessary. The aim of this study was to assess the impact of substance use and hepatitis virus coinfection on plasma ATV and LPV trough concentrations in HIV-positive substance users and nonusers. Individuals established on ATV (300 mg and 100 mg ritonavir daily) or LPV (400 mg and 100 mg ritonavir twice daily)-containing regimens completed two clinical visits (trough and directly observed therapy) during which dosing characteristics, concomitant medication, and substance use were recorded. Trough plasma concentrations (22-26 hours for ATV and 10-14 hours for LPV) were measured using LCMSMS. The influence of substance use was evaluated by Kruskal-Wallis test. Substance use was associated with a marked decrease in trough LPV concentrations during the trough visit (median, 5.536 and 3.791 microg/mL for nonsubstance users and substance users, respectively, P = 0.029). Significantly lower LPV trough levels were also noted among patients with active hepatitis C virus coinfection evaluated as an independent variable (median, 2.253 and 5.927 microg/mL for active and inactive/no hepatitis C virus infection, respectively, P = 0.032). Substance use and hepatitis virus coinfection had limited effects on ATV trough levels. In this cohort, despite the wide interindividual variability of ATV and LPV trough concentrations, significant associations between substance use and active hepatitis C virus infection and low LPV trough concentrations were observed. Further work is needed to assess the optimal dosing regimen when using LPV in HIV-infected substance users.

Potential drug-drug and drug-disease interactions in prescriptions for ambulatory patients over 50 years of age in family medicine clinics in Mexico City

BackgroundIn Mexico, inappropriate prescription of drugs with potential interactions causing serious risks to patient health has been little studied. Work in this area has focused mainly on hospitalized patients, with only specific drug combinations analyzed; moreover, the studies have not produced conclusive results. In the present study, we determined the frequency of potential drug-drug and drug-disease interactions in prescriptions for ambulatory patients over 50 years of age, who used Mexican Institute of Social Security (IMSS) family medicine clinics. In addition, we aimed to identify the associated factors for these interactions.MethodsWe collected information on general patient characteristics, medical histories, and medication (complete data). The study included 624 ambulatory patients over 50 years of age, with non-malignant pain syndrome, who made ambulatory visits to two IMSS family medicine clinics in Mexico City. The patients received 7-day prescriptions for non-opioid analgesics. The potential interactions were identified by using the Thompson Micromedex program. Data were analyzed using descriptive, bivariate and multiple logistic regression analyses.ResultsThe average number of prescribed drugs was 5.9 ± 2.5. About 80.0% of patients had prescriptions implying one or more potential drug-drug interactions and 3.8% of patients were prescribed drug combinations with interactions that should be avoided. Also, 64.0% of patients had prescriptions implying one or more potential drug disease interactions. The factors significantly associated with having one or more potential interactions included: taking 5 or more medicines (adjusted Odds Ratio (OR): 4.34, 95%CI: 2.76–6.83), patient age 60 years or older (adjusted OR: 1.66, 95% CI: 1.01–2.74) and suffering from cardiovascular diseases (adjusted OR: 7.26, 95% CI: 4.61–11.44).ConclusionThe high frequency of prescription of drugs with potential drug interactions showed in this study suggests that it is common practice in primary care level. To lower the frequency of potential interactions it could be necessary to make a careful selection of therapeutic alternatives, and in cases without other options, patients should be continuously monitored to identify adverse events.

Count and Be Counted: Preparing Future Pharmacists to Promote a Culture of Safety

Count and Be Counted: Preparing Future Pharmacists to Promote a Culture of Safety

Clinically important drug-disease interactions and their prevalence in older adults

Background:Older adults may have decreased homeostatic reserve, have multiple chronic diseases, and take multiple medications. Therefore, they are at risk for adverse outcomes after receiving a drug that exacerbates a chronic disease. Objectives:The aims of this study were to compile a list of clinically important drug-disease interactions in older adults, obtain the consensus of a multidisciplinary panel of geriatric health care professionals on these interactions, and determine the prevalence of these interactions in a sample of outpatients. Methods:This analysis included a 2-round modified Delphi survey and cross-sectional study. Possible drug-disease interactions in patients aged ≥65 years were identified through a search of the English-language literature indexed on MEDLINE and International Pharmaceutical Abstracts (1966–July 2004) using terms that included drug-disease interaction, medication errors, and inappropriate prescribing. Nine health care professionals with expertise in geriatrics (2 geriatricians, 7 geriatric clinical pharmacist specialists) were selected based on specialty training and continuing clinical work in geriatrics, academic appointments, and geographic location. The panel rated the importance of the potential drug-disease interactions using a 5-point Likert scale (from 1 = definitely not serious to 5 = definitely serious). Consensus on a drug-disease interaction was defined as a lower bound of the 95% CI ≥4.0. The prevalence of drug-disease interactions was determined by applying the consensus criteria to a convenience sample of frail older veterans at hospital discharge who were enrolled in a health services intervention trial. Results:The panel reached consensus on 28 individual drug-disease interactions involving 14 diseases or conditions. Overall, 205 (15.3%) of the 1340 veterans in the sample had >_1 drug-disease interaction. The 2 most common drug-disease interactions were use of first-generation calcium channel blockers in patients with congestive heart failure and use of aspirin in patients with peptic ulcer disease (both, 3.7%) Conclusions:A survey of multidisciplinary geriatric health care professionals resulted in a concise consensus list of clinically important drug-disease interactions in older adults. Further research is needed to examine the impact of these drug-disease interactions on health outcomes and their applicability as national measures for the prevention of drug-related problems.

Potential Drug—Disease Interactions in Frail, Hospitalized Elderly Veterans

Drugs can improve quality of life for many older people, but they may cause adverse health outcomes (eg, drug-disease interactions) if used inappropriately. To determine the prevalence of potential drug-disease interactions as defined by explicit criteria and examine associations between sociodemographic and health status variables and potential drug-disease interactions. The study design was cross-sectional. We evaluated 397 frail elderly inpatients from the Geriatric Evaluation and Management trial conducted at 11 Veterans Affairs Medical Centers. Drug-disease interactions were defined using explicit criteria from consensus expert panels of geriatricians from the US and Canada. Overall, 159 (40.1%) patients had one or more potential drug-disease interaction. The most common potential interactions were calcium-channel blockers and heart failure (12.3%) and beta-blockers and diabetes (6.8%). Multivariable logistic regression analyses revealed that age > or =75 years (adjusted OR 2.43; 95% CI 1.52 to 3.88), being married (adjusted OR 1.77; 95% CI 1.11 to 2.82), comorbidity index defined by Charlson method (adjusted OR 1.19; 95% CI 1.05 to 1.34), and use of multiple prescription drugs (5-8: adjusted OR 4.17; 95% CI 1.96 to 8.88, > or =9: adjusted OR 9.22; 95% CI 4.26 to 19.95), were significantly (p < 0.05) associated with having one or more potential drug-disease interaction. Potential drug-disease interactions are common in hospitalized elderly patients and are related to specific sociodemographic and health status factors. Further research is needed to examine the relationship between health outcomes and drug-disease interactions.

Incidence and Possible Causes of Prescribing Potentially Hazardous/Contraindicated Drug Combinations in General Practice

Preventing the use of medications where there is the potential for serious drug-drug interactions or drug-disease interactions (contraindications) is essential to ensure patient safety. Previous studies have looked at the incidence of prescribing contraindicated drug combinations, but little is known about the underlying reasons for the co-prescribing events. The objectives of this study were to estimate the incidence of prescribing contraindicated drug combinations in general practice and to explore the clinical context, possible causes and potential systems failures leading to their occurrence. A list of contraindicated drug combinations was compiled according to established references. A search of computerised patient medication records was performed, followed by detailed chart review and assessment. The patient records from four general practices in an area of England were searched for a period of 1 year (1 June 1999-31 May 2000) to identify contraindicated drug combinations. All patients registered with the four participating practices during the study period were included (estimated n = 37 940). Medical records of the cases identified by the computer search were reviewed in detail and relevant information was extracted. Each case was then independently assessed by a pharmacist and a physician who judged whether the co-prescribing was justified and whether it was associated with an adverse drug event. Proximal causes and potential systems failures were suggested for each co-prescribing event. Fourteen patients with potential drug-drug interactions and 50 patients with potential drug-disease interactions were identified. Overall, these represent an incidence of 1.9 per 1000 patient-years (95% CI 1.5, 2.3) or 4.3 per 1000 patients being concurrently prescribed > or =2 drugs per year (95% CI 3.2, 5.4). 62 cases involving 63 co-prescribing events were reviewed. Two-thirds of these events involved medications that were initiated by hospital doctors. Awareness of the potential drug-drug or drug-disease interactions was documented in one-third of the events at the time of initial co-prescribing. Within the study period, the co-prescribing was judged to be not justified in 44 events (70%). Potential drug-drug interactions possibly resulted in two adverse drug events. The majority of contraindicated co-prescribing related to drug-disease interactions involved the use of propranolol or timolol eye drops for patients receiving bronchodilators and the use of amiodarone for patients receiving levothyroxine sodium. The prescribing of contraindicated drug combinations was relatively rare in this study. Multiple possible causes and systems failures were identified and could be used to develop strategies for the prevention of prescribing errors involving contraindicated drug combinations in primary care.

Interacting with drugs used in oncology: an Alberta Cancer Board initiative

Objective. The Alberta Cancer Board (ACB) Pharmacy recognized the importance of having a sound knowledge of drug interactions with anti-neoplastic agents. A pharmacy student was given the task of surveying ACB pharmacists for published literature and Internet sources used most often as sources of drug interaction information during medication order review and evaluation of patient profiles. The goal was to extract information from these sources and integrate it into a concise ACB drug interaction database, which lists the actual and potential antineoplastic drug-drug, drug-disease, drug-natural products and drug-food interactions. The antineoplastic agents identified and examined were part of the ACB Out-patient Cancer Drug Benefit Program (OCDBP) (August 2002). Equipped with this information and using their clinical expertise, pharmacists can play an important role in the medical management of patients with cancer. Data sources. The student collected information from literary and remote sources used most often by ACB pharmacists. Study selection. ACB pharmacists were surveyed for published literature and Internet sources that contained drug interaction information on antineoplastics used most often during medication order review, patient counselling sessions and when responding to drug information requests. The contributors of these information sources claim to have reviewed existing references and thus the student relied on the accurate reporting of their findings instead of collecting data from the original works. The drugs reviewed for the purpose of the study were taken from the ACB OCDBP. Data extraction. There was an extensive data collection process. Dorland’s definition of a drug interaction was adopted. The student determined a potential interaction based on the words `may’ or `risk’ found in the statement of the interaction. The student extracted the drug interaction information into tables and a sample of 10 of 87 drugs from the ACB OCDBP are presented in this paper. A complete guide of the ACB drug interaction index can be obtained from the ACB Pharmacy. Data synthesis. Actual and potential antineo-plastic drug-drug, drug-disease, drug-natural products and drug-food interactions are summarized in tables. The information collected was as current as the date that the data were extracted. The determination of clinical significance relies on the expertise of the pharmacist or other healthcare professional. Moreover, the data contained in the tables is representative of the information collected exclusively from sources used most often by ACB pharmacists and therefore is only one source of drug interaction information. Conclusion. An indepth knowledge of actual and potential interactions with antineoplastic agents is critical for pharmacists in the management of patients with cancer. The ACB drug interaction index is an attempt to promote awareness of interactions with antineoplastic drugs and to encourage clinicians to investigate drug interactions during their treatment and management protocols.

Drug-drug and drug-disease interactions in the ED: Analysis of a high-risk population

A study was undertaken to determine the potential for adverse drug interactions (ADIs) and drug-disease interactions (DDIs) in a high-risk population of emergency department (ED) patients and to characterize drug-drug and drug-disease interactions in terms of percentage of patients at risk from existing drug regimens, percentage of patients at risk from ED treatment, relation between number of drugs and potential for interactions, types of drugs and diseases posing greatest potential for interaction, and the differences in a general versus community hospital population with respect to these parameters. Records of 205 consecutive patients, 111 from a general hospital teaching facility ED (Facility 1) and 94 from a community hospital ED (Facility 2) were retrospectively reviewed. The records of all patients receiving three or more medications and all patients older than 50 years of age receiving two or more medications were analyzed by two computer programs for the presence of potential drug-drug and drug-disease interactions. A total of 226 potential ADIs were found in 89 patients (47%), with 50% of ADIs being related to ED treatment. A total of 94 potential DDIs were found in 44 patients (21%), with 34% of DDIs being related to ED treatment. The risk of an ADI rose from 13% for patients taking 2 medications to 82% for patients taking 7 or more medications. Eleven medications and four disease categories were identified as having particular potential for interactions. No significant differences were found between the general and the community hospital populations in these respects. ED patients taking three or more medications and patients older than 50 years of age taking two or more medications are at substantial risk for adverse drug-drug and drug-disease interactions. The risk is increased in patients taking particular drugs or having particular disease states.