Potential Drug Interactions— Fact or Fallacy?

1975 ◽  
Vol 9 (11) ◽  
pp. 586-590 ◽  
Author(s):  
Curtis D. Black ◽  
Nicholas G. Popovich
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Patient Care ◽  
Clinical Studies ◽  
Literature Search ◽  
Potential Drug ◽  
Careful Evaluation ◽  
Current Drug ◽  
Drug Drug Interaction

At present, the pharmacist is faced with a perplexing number of potential drug interactions as they relate to patient care. The purpose of the investigation was to evaluate current drug-drug interaction literature, specifically gastrointestinal drug interactions. Literature search and review evaluated the authoritative basis on which conclusions were made. From this, a review was written to illustrate fallacies and misconceptions that could be derived from the literature with the intent it would serve as a guide in interpreting and evaluating drug-drug interactions. The overall study illustrates the vast need for careful evaluation of drug interaction literature before erroneous recommendations are made on conceivably inconclusive clinical studies.

scholarly journals A Minimal Information Model for Potential Drug-Drug Interactions

2021 ◽  
Vol 11 ◽  
Author(s):  
Harry Hochheiser ◽  
Xia Jing ◽  
Elizabeth A. Garcia ◽  
Serkan Ayvaz ◽  
Ratnesh Sahay ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Best Practice ◽  
Task Force ◽  
Information Model ◽  
Potential Drug ◽  
Community Group ◽  
Drug Drug Interaction ◽  
Potential Interactions ◽  
Minimal Information

Despite the significant health impacts of adverse events associated with drug-drug interactions, no standard models exist for managing and sharing evidence describing potential interactions between medications. Minimal information models have been used in other communities to establish community consensus around simple models capable of communicating useful information. This paper reports on a new minimal information model for describing potential drug-drug interactions. A task force of the Semantic Web in Health Care and Life Sciences Community Group of the World-Wide Web consortium engaged informaticians and drug-drug interaction experts in in-depth examination of recent literature and specific potential interactions. A consensus set of information items was identified, along with example descriptions of selected potential drug-drug interactions (PDDIs). User profiles and use cases were developed to demonstrate the applicability of the model. Ten core information items were identified: drugs involved, clinical consequences, seriousness, operational classification statement, recommended action, mechanism of interaction, contextual information/modifying factors, evidence about a suspected drug-drug interaction, frequency of exposure, and frequency of harm to exposed persons. Eight best practice recommendations suggest how PDDI knowledge artifact creators can best use the 10 information items when synthesizing drug interaction evidence into artifacts intended to aid clinicians. This model has been included in a proposed implementation guide developed by the HL7 Clinical Decision Support Workgroup and in PDDIs published in the CDS Connect repository. The complete description of the model can be found at https://w3id.org/hclscg/pddi.

scholarly journals A Comparison of Tertiary Drug Resources’ Consistency Regarding Drug-Drug Interactions of Adjunctive Analgesics

2020 ◽  
pp. 875512252095133
Author(s):  
Andrew Lang ◽  
Michael A. Veronin ◽  
Justin P. Reinert
Keyword(s):  
Health Care ◽  
Drug Interaction ◽  
Drug Interactions ◽  
Patient Care ◽  
Health Care Providers ◽  
Drug Information ◽  
Interaction Analysis ◽  
Information Resources ◽  
Care Providers ◽  
Drug Drug Interaction

Background: Health care providers routinely rely on tertiary drug information resources to affirm knowledge or proactively verify the safety and efficacy of medications. Though all patient care areas are affected, the reliability of these resources is perhaps nowhere as poignant as it is in high-acuity settings, including the emergency department and the intensive care unit. As providers seek to identify adjunctive analgesics for acute pain in these areas, they must be able to rely on the integrity to whichever resource their institution has granted access. Objective: To determine the congruency of drug-drug interaction information found on 3 tertiary drug resources. Methods: A drug-drug interaction analysis was conducted on Micromedex, Lexicomp, and Medscape. Adjunctive analgesics included dexmedetomidine and ketamine, which were compared with the intravenous opioid products morphine, fentanyl, and hydromorphone. Results: Significant discrepancies were appreciated with regard to the severity of drug-drug interactions. In addition, the heterogeneity in which reaction severity and likelihood are described by each respective resource makes direct comparisons difficult. Interaction warnings for dexmedetomidine and fentanyl included a “major interaction” from Micromedex, whereas Lexicomp did not identify a risk and Medscape only recommended increased monitoring on the grounds of respiratory and central nervous system depression. Conclusions: Health care providers must remain vigilant when reviewing tertiary drug information resources. Pharmacists possess the training and skills necessary to assist interdisciplinary medical teams in providing optimal patient care through evaluating and applying the information gleaned from these resources.

scholarly journals Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data

2021 ◽  
Vol 12 ◽  
pp. 204209862110412
Author(s):  
Levin Thomas ◽  
Sumit Raosaheb Birangal ◽  
Rajdeep Ray ◽  
Sonal Sekhar Miraj ◽  
Murali Munisamy ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Molecular Modelling ◽  
Molecular Level ◽  
Drug Information ◽  
Potential Drug ◽  
African Countries ◽  
Antitubercular Drugs ◽  
Tuberculosis Patients ◽  
Drug Drug Interaction

Introduction: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug–drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs. Methods: We assessed the potential drug–drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug–drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug–drug interactions between repurposed COVID-19 and antitubercular drugs. Results: A total of 91 potential drug–drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug–drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug–drug interaction, whereas drug–drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug–drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs. Conclusion: Predicting these potential drug–drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug–drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug–drug interaction studies. Plain Language Summary Introduction: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients predicted to be infected with COVID-19 during this period, there is a higher risk for the occurrence of medication interactions between the medicines used for COVID-19 and tuberculosis. Hence, identifying and managing these interactions is vital to ensure the safety of patients undergoing COVID-19 and tuberculosis treatment simultaneously. Methods: We studied the major medication interactions that could likely happen between the various medicines that are currently given for COVID-19 and tuberculosis treatment using the medication interaction checker of a drug information software (Micromedex®). In addition, thorough molecular modelling was done to confirm and understand the interactions found from the medication interaction checker database using specific docking software. Molecular docking is a method that predicts the preferred orientation of one medicine molecule to a second molecule, when bound to each other to form a stable complex. Knowledge of the preferred orientation may be used to determine the strength of association or binding affinity between two medicines using scoring functions to determine the extent of the interactions between medicines. The combined knowledge from Micromedex and molecular modelling data was used to properly predict the potential medicine interactions between currently used COVID-19 and antitubercular medicines. Results: We found a total of 91 medication interactions from Micromedex. Majority of our molecular modelling findings matched with the interaction information obtained from the drug information software. QT prolongation, an abnormal heartbeat, was identified as one of the most common interactions. Our findings suggest that antitubercular medicines, mainly rifampin and second-line agents, suggest high alert and scrutiny while prescribing with the repurposed COVID-19 medicines. Conclusion: Our current study highlights the need for further well-designed studies confirming the current information for recommending safe prescribing in patients with both infections.

scholarly journals THE PREDICTORS OF POTENTIAL DRUG-DRUG INTERACTIONS AMONG DIABETIC HYPERTENSIVE ADULT OUTPATIENTS IN A KENYAN REFERRAL HOSPITAL

2020 ◽  
pp. 63-67
Author(s):  
MAKITE SIMON LATI ◽  
NYAMU GITONGA DAVID ◽  
ROSALINE NJERI KINUTHIA
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Cross Sectional Study ◽  
Potential Drug ◽  
National Hospital ◽  
Cross Sectional ◽  
Kenyatta National Hospital ◽  
Stage 4 ◽  
Drug Drug Interaction ◽  
Study Participants

Objective: To characterize the predictors of potential drug-drug interactions among adult diabetic hypertensive outpatients at Kenyatta National Hospital. Methods: This cross-sectional study collected and analyzed data on potential drug interactions from 104 diabetic hypertensive outpatients (aged ≥18 y) at the Department of Endocrinology Outpatient Clinic of Kenyatta National Hospital from 1st May 2019 to 31st August 2019. The main outcome measure was the prevalence of potential drug-drug interactions and their predictors among the study population. Results: There was a female preponderance (70.2%). The mean age of the study participants was 61.6 y (SD±10.8). The prevalence of potential drug interactions was high at 57.7%. The average number of drug interactions was one interacting pair per patient, with a majority of the prescriptions (81.0%) having moderate drug-drug interactions. Patients receiving>2 drugs were almost three times more likely to have drug-drug interaction compared to those prescribed ≤ 2 drugs (AOR=2.79; 95% CI: 1.11-7.28); p=0.029). Participants who were at stage 4 of hypertension were 2.5 times more likely to have a drug-drug interaction compared to the other stages of hypertension (AOR=2.52; 95% CI 1.31-4.89; p=0.007). Conclusion: Polypharmacy and stage 4 hypertension are independently associated with drug-drug interactions among patients with both diabetes and hypertension. Future studies should characterize the specific type of drug interactions and possible targets of minimization of drug-drug interactions.

scholarly journals Prevalence of potential drug- drug interactions and associated factors among outpatients and inpatients in Ethiopian Hospitals: a systematic review and Meta-analysis of observational studies

2020 ◽  
Author(s):  
Wondim Ayenew ◽  
Getahun Asmamaw ◽  
Arebu Issa
Keyword(s):  
Systematic Review ◽  
Drug Interaction ◽  
Drug Interactions ◽  
Associated Factors ◽  
Meta Analysis ◽  
Random Effect Model ◽  
Potential Drug ◽  
Comorbid Disease ◽  
Factors Associated ◽  
Drug Drug Interaction

Abstract Background: Drug-drug interaction is an emerging threat to public health. Currently, there is an increase in comorbid disease, polypharmacy, and hospitalization in Ethiopia. Thus, the possibility of drug-drug interaction occurrence is high in hospitals. This study aims to summarize the prevalence of potential drug-drug interactions and associated factors in Ethiopian hospitals.Methods: A literature search was performed by accessing legitimate databases in PubMed/MEDLINE, Google Scholar, and Research Gate for English-language publications. To fetch further related topics advanced search was also applied in Science Direct and HINARI databases. The search was conducted on August 3 to 25, 2019. All published articles available online until the day of data collection were considered. Outcome measures were analyzed with Open Meta Analyst and CMA version statistical software. Der Simonian and Laird’s random effect model, I2 statistics, and Logit event rate were also performed.Results: A total of 14 studies remained eligible for inclusion in systematic review and meta-analysis. From the included studies, around 8,717 potential drug-drug interactions were found in 3,259 peoples out of 5,761 patients. The prevalence of patients with potential drug-drug interactions in Ethiopian hospitals was found to be 72.2% (95% confidence interval: 59.1%, 85.3%). Based on severity, the prevalence of major, moderate, and minor potential drug-drug interaction was 25.1%, 52.8%, 16.9%, respectively, also 1.27% for contraindications. The factors associated with potential drug-drug interactions were related to patient characteristics such as polypharmacy, age, comorbid disease, and hospital stay.Conclusions: There is a high prevalence of potential drug-drug interactions in Ethiopian hospitals. Polypharmacy, age, comorbid disease, and hospital stay were the risk factors associated with potential drug-drug interactions.

scholarly journals Potential drug–drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia

2019 ◽  
Vol 7 ◽  
pp. 205031211985735 ◽  
Author(s):  
Netsanet Diksis ◽  
Tsegaye Melaku ◽  
Desta Assefa ◽  
Andualem Tesfaye
Keyword(s):  
Drug Interaction ◽  
Confidence Interval ◽  
Drug Interactions ◽  
Hospital Stay ◽  
Prevalence Rate ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Cardiac Patients ◽  
Potential Drug ◽  
Drug Drug Interaction

Background: Concomitant use of several drugs for a patient is often imposing increased risk of drug–drug interactions. Drug–drug interactions are a major cause for concern in patients with cardiovascular disorders due to multiple co-existing conditions and the wide class of drugs they receive. This study is aimed to assess the prevalence of potential drug–drug interactions and associated factors among hospitalized cardiac patients at medical wards of Jimma University Medical Center, Southwest Ethiopia. Methods: A hospital-based prospective observational study was conducted among hospitalized cardiac adult patients based on the inclusion criteria. Patient-specific data were collected using structured data collection tool. Potential drug–drug interaction was analyzed using Micromedex 3.0 DRUG-REAX® System. Data were analyzed using statistical software package, version 20.0. To identify the independent predictors of potential drug–drug interaction, multiple stepwise backward logistic regression analysis was done. Statistical significance was considered at a p-value < 0.05. Written informed consent from patients was obtained and the patients were informed about confidentiality of the information obtained. Results: Of the total 200 patients, majority were male (52.50%) and with a mean(±standard deviation) age of 42.54(±7.89) years. Out of 673 patients’ prescriptions analyzed, 521 prescriptions comprised potential drug interactions and it was found that 967 drug interactions were present. The prevalence rate of potential drug–drug interactions among the study unit was 4.83 per patient and 1.44 per prescription regardless of the severity during their hospital stay. Overall the prevalence rate of potential drug interactions was 74.41%. Older age (adjusted odds ratio (95% confidence interval): 1.067 (2.33–27.12), p = 0.049), long hospital stay (⩾7 days) (adjusted odds ratio (95% confidence interval): 2.80 (1.71–4.61), p = 0.024), and polypharmacy (adjusted odds ratio (95% confidence interval): 1.64 (0.66–4.11), p = 0.041) were independent predictors for the occurrence of potential drug–drug interactions. Conclusion: This study demonstrated a high prevalence of potential DIs among hospitalized cardiac patients in medical wards due to the complexity of pharmacotherapy. The prevalence rate is directly related to age, number of prescribed drugs, and length of hospital stay. Pharmacodynamic drug–drug interaction was the common mechanism of drug–drug interactions. Therefore, close monitoring of hospitalized patients is highly recommended.

scholarly journals Polypharmacy and potential drug-drug interactions among medications prescribed to chronic kidney disease patients

2021 ◽  
Vol 9 (1) ◽  
pp. 25-32
Author(s):  
Shrijana Kumari Chaudhary ◽  
Naresh Manadhar ◽  
Laxman Adhikari
Keyword(s):  
Chronic Kidney Disease ◽  
Drug Interaction ◽  
Kidney Disease ◽  
Drug Interactions ◽  
Teaching Hospital ◽  
College Teaching ◽  
Potential Drug ◽  
Comorbid Conditions ◽  
Medical College ◽  
Drug Drug Interaction

Background and Objectives: Chronic kidney disease is a major systemic condition. Presence of comorbid conditions with the deteriorating renal function, lead them to use multiple drugs. Polypharmacy is common among chronic kidney disease. The possibility of drug interaction rises when a patients concurrently receive more than one drug and the chances increase with the number of drugs taken, which may be associated with increased morbidity, mortality, length of hospital stay and health-care cost. The aim of this study was to assess the polypharmacy and pattern of drug- drug interactions in chronic kidney disease patients attending OPD and ward of nephrology unit in Kathmandu Medical College teaching hospital. Material and Methods: This was a prospective cross sectional study conducted among 143 chronic kidney disease diagnosed patients in Kathmandu Medical College Teaching Hospital. The Lexi-comp database was used to evaluate patient’s medications for potential drug-drug interactions. Results: Chronic kidney disease was predominant among male (65.7%) than the female (34.3%). The most common age group was 41-60yrs followed by 61-80 yrs. The mean age of the patients was 54.38 ± 16.43 years. Chronic kidney disease was associated with multiple co-morbid conditions. The most common comorbid conditions were hypertension 52 (36. 4%) and hypertension and diabetes both in 42 (29.4%). A total of 143 prescriptions were included in this study. Average number of drugs per prescription was 6.1. Almost 5-8 medicines per prescription were observed among 95(65.73%) patients. A total of 837 medicines were prescribed. A total number of 206 potential drug-drug interactions were observed among 143 patients. Depending upon the risk rating categorize, the most common were,  risk rating C 178( 86.4%) and the most frequent drug interaction was between amlodipine and calcium carbonate 65 (45.45%) . Conclusion: The prevalence of potential drug-drug interaction is high among chronic kidney disease patients. About 63% of interactions have moderate severity. The safest approach to avoid potentials drug-drug interaction is the implementation of appropriate guidelines, detailed and rationalize knowledge of drugs and to utilize available drug-drug interaction software to avoid harmful drug-drug interaction among chronic kidney disease patients.

Pharmacokinetic Drug-drug Interaction of Antibiotics Used in Sepsis Care in China

2020 ◽  
Vol 21 ◽  
Author(s):  
Xuan Yu ◽  
Zixuan Chu ◽  
Jian Li ◽  
Rongrong He ◽  
Yaya Wang ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Drug Interactions ◽  
Penicillin G ◽  
Literature Mining ◽  
Human Pharmacokinetics ◽  
P450 Enzyme ◽  
Drug Drug Interaction ◽  
Pharmacokinetic Drug ◽  
Sepsis Care

Background: Many antibiotics have a high potential for having an interaction with drugs, as perpetrator and/or victim, in critically ill patients, and particularly in sepsis patients. Methods: The aim of this review is to summarize the pharmacokinetic drug-drug interaction (DDI) of 45 antibiotics commonly used in sepsis care in China. Literature mining was conducted to obtain human pharmacokinetics/dispositions of the antibiotics, their interactions with drug metabolizing enzymes or transporters, and their associated clinical drug interactions. Potential DDI is indicated by a DDI index > 0.1 for inhibition or a treated-cell/untreated-cell ratio of enzyme activity being > 2 for induction. Results: The literature-mined information on human pharmacokinetics of the identified antibiotics and their potential drug interactions is summarized. Conclusion: Antibiotic-perpetrated drug interactions, involving P450 enzyme inhibition, have been reported for four lipophilic antibacterials (ciprofloxacin, erythromycin, trimethoprim, and trimethoprim-sulfamethoxazole) and three lipophilic antifungals (fluconazole, itraconazole, and voriconazole). In addition, seven hydrophilic antibacterials (ceftriaxone, cefamandole, piperacillin, penicillin G, amikacin, metronidazole, and linezolid) inhibit drug transporters in vitro. Despite no reported clinical PK drug interactions with the transporters, caution is advised in the use of these antibacterials. Eight hydrophilic antibacterials (all β-lactams; meropenem, cefotaxime, cefazolin, piperacillin, ticarcillin, penicillin G, ampicillin, and flucloxacillin), are potential victims of drug interactions due to transporter inhibition. Rifampin is reported to perpetrate drug interactions by inducing CYP3A or inhibiting OATP1B; it is also reported to be a victim of drug interactions, due to the dual inhibition of CYP3A4 and OATP1B by indinavir. In addition, three antifungals (caspofungin, itraconazole, and voriconazole) are reported to be victims of drug interactions because of P450 enzyme induction. Reports for other antibiotics acting as victims in drug interactions are scarce.

scholarly journals Herb–Drug Interactions: Worlds Intersect with the Patient at the Center

Medicines ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 44
Author(s):  
Mary Beth Babos ◽  
Michelle Heinan ◽  
Linda Redmond ◽  
Fareeha Moiz ◽  
Joao Victor Souza-Peres ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Case Report ◽  
Drug Interactions ◽  
Clinical Studies ◽  
Drug Information ◽  
Case Reports ◽  
Full Information ◽  
Information Need ◽  
Herbal Products ◽  
Reduce Risk

This review examines three bodies of literature related to herb–drug interactions: case reports, clinical studies, evaluations found in six drug interaction checking resources. The aim of the study is to examine the congruity of resources and to assess the degree to which case reports signal for further study. A qualitative review of case reports seeks to determine needs and perspectives of case report authors. Methods: Systematic search of Medline identified clinical studies and case reports of interacting herb–drug combinations. Interacting herb–drug pairs were searched in six drug interaction resources. Case reports were analyzed qualitatively for completeness and to identify underlying themes. Results: Ninety-nine case-report documents detailed 107 cases. Sixty-five clinical studies evaluated 93 mechanisms of interaction relevant to herbs reported in case studies, involving 30 different herbal products; 52.7% of these investigations offered evidence supporting reported reactions. Cohen’s kappa found no agreement between any interaction checker and case report corpus. Case reports often lacked full information. Need for further information, attitudes about herbs and herb use, and strategies to reduce risk from interaction were three primary themes in the case report corpus. Conclusions: Reliable herb–drug information is needed, including open and respectful discussion with patients.

Prevalence and trend of potential drug–drug interaction among children with depression in U.S. outpatient settings

2019 ◽  
Vol 10 (4) ◽  
pp. 393-399
Author(s):  
L. Leanne Lai ◽  
Goar Alvarez ◽  
Linh Dang ◽  
Dung Vuong ◽  
Vy Ngo ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Potential Drug ◽  
Drug Drug Interaction ◽  
Outpatient Settings
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