Similarity and Consistency Assessment of Three Major Online Drug-Drug Interaction Resources

AIM: To explore the level of agreement on drug-drug interaction (DDI) information listed in three major online drug information resources (DIRs) in terms of: (1) interacting drug pairs; (2) severity rating; (3) evidence rating and (4) clinical management recommendations. METHODS: We extracted DDI information from the British National Formulary (BNF), Thesaurus, and Micromedex. Following drug name normalisation, we estimated the overlap of the DIRs. We annotated clinical management recommendations either manually, where possible, or through application of a machine learning algorithm. RESULTS: The DIRs contained 51,481 (BNF), 38,037 (Thesaurus), and 65,446 (Micromedex) drug pairs involved in DDIs. The number of common DDIs across the three DIRs was 6,970 (13.54% of BNF, 18.32% of Thesaurus, and 10.65% of Micromedex). Micromedex and Thesaurus overall showed higher levels of similarity in their severity ratings, while the BNF agreed more with Micromedex on the critical severity ratings and with Thesaurus on the least significant ones. Evidence rating agreement between BNF and Micromedex was generally poor. Variation in clinical management recommendations was also identified, with some categories (i.e. Monitor and Adjust dose) showing higher levels of agreement compared to others (i.e. Use with caution, Wash-out, Modify administration). CONCLUSIONS: There is considerable variation in the DDIs included in the examined DIRs, together with variability in categorisation of severity and clinical advice given. DDIs labelled as critical are more likely to appear in multiple DIRs. Such variability in information could have deleterious consequences for patient safety, and there is a need for harmonisation and standardisation.

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Development and validation of standardized severity rating scale to assess the consistency of drug-drug interaction severity among various drug information resources

Research in Social and Administrative Pharmacy ◽

10.1016/j.sapharm.2021.12.006 ◽

2022 ◽

Author(s):

Atiqulla Shariff ◽

Sathvik Belagodu Sridhar ◽

Neelufarhath Abdullah Basha ◽

Shamma Sulaiman Hasan Bin Taleth Alshemeil ◽

Noora Adel Ahmed Aljallaf Alzaabi

Keyword(s):

Drug Interaction ◽

Rating Scale ◽

Drug Information ◽

Information Resources ◽

Severity Rating ◽

Drug Drug Interaction ◽

Development And Validation

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DRUG-DRUG INTERACTION;

The Professional Medical Journal ◽

10.29309/tpmj/2017.24.03.1551 ◽

2017 ◽

Vol 24 (03) ◽

pp. 357-365

Author(s):

Hina Hasnain ◽

Huma Ali ◽

Farya Zafar ◽

Ali Akbar Sial ◽

Kamran Hameed ◽

...

Keyword(s):

Patient Outcome ◽

Adverse Event ◽

Drug Interaction ◽

Drug Interactions ◽

Multidisciplinary Approach ◽

Drug Information ◽

Drug Effects ◽

Information Provision ◽

Drug Drug Interaction ◽

Drug Order

Drug-drug interaction (DDI) is a specific type of adverse event, which developsdue to multiple regimen therapy, and that may lead to significant hospitalization and death.Clinical and economic impact of drug interactions are increasingly accredited as a chiefconcern in critical care. Potentiating effects of DDIs in intensive care units are far more criticaldue to complex medications regimen, high risk severely ill population and associated metabolicand physiological disturbances which can impede drug effects. Pharmacist contribution isclassified as clarification of drug order, appropriate drug information provision, and advice forsubstitute treatment. A multidisciplinary approach is very necessary in developing a pharmacotherapeuticregimen designed to optimize patient outcome and minimize any potential dugdrug interactions. This review encompasses the prevalence, categorization, significance interm of patient safety and prescription efficacy, clinical and economic burdens, national andinternational data comparisons related to drug-drug interactions.

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

Journal of Pharmacy Technology ◽

10.1177/8755122520951331 ◽

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.

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

Therapeutic Advances in Drug Safety ◽

10.1177/20420986211041277 ◽

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.

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