Clinically significant drug-drug interactions between tramadol and CYP3A4 inhibitors: disproportionality analysis in VigiBase® and hypothesis on the underlying mechanism

2020 ◽  
Vol 76 (7) ◽  
pp. 1049-1051
Author(s):  
Clémence Delafoy ◽  
Charles Dolladille ◽  
Paul Besnier ◽  
Marion Sassier ◽  
Joanna Bourgine ◽  
...  
Keyword(s):  
Drug Interactions ◽  
Underlying Mechanism ◽  
Disproportionality Analysis ◽  
Cyp3a4 Inhibitors ◽  
Clinically Significant

scholarly journals Drug interactions: a review of the unseen danger of experimental COVID-19 therapies

2020 ◽  
Vol 75 (12) ◽  
pp. 3417-3424 ◽  
Author(s):  
Catherine Hodge ◽  
Fiona Marra ◽  
Catia Marzolini ◽  
Alison Boyle ◽  
Sara Gibbons ◽  
...  
Keyword(s):  
Drug Interactions ◽  
Herbal Medicines ◽  
Qt Prolongation ◽  
Critically Ill Patient ◽  
Experimental Drugs ◽  
Mesh Terms ◽  
Experimental Therapies ◽  
Clinically Significant ◽  
Novel Coronavirus

Abstract As global health services respond to the coronavirus pandemic, many prescribers are turning to experimental drugs. This review aims to assess the risk of drug–drug interactions in the severely ill COVID-19 patient. Experimental therapies were identified by searching ClinicalTrials.gov for ‘COVID-19’, ‘2019-nCoV’, ‘2019 novel coronavirus’ and ‘SARS-CoV-2’. The last search was performed on 30 June 2020. Herbal medicines, blood-derived products and in vitro studies were excluded. We identified comorbidities by searching PubMed for the MeSH terms ‘COVID-19’, ‘Comorbidity’ and ‘Epidemiological Factors’. Potential drug–drug interactions were evaluated according to known pharmacokinetics, overlapping toxicities and QT risk. Drug–drug interactions were graded GREEN and YELLOW: no clinically significant interaction; AMBER: caution; RED: serious risk. A total of 2378 records were retrieved from ClinicalTrials.gov, which yielded 249 drugs that met inclusion criteria. Thirteen primary compounds were screened against 512 comedications. A full database of these interactions is available at www.covid19-druginteractions.org. Experimental therapies for COVID-19 present a risk of drug–drug interactions, with lopinavir/ritonavir (10% RED, 41% AMBER; mainly a perpetrator of pharmacokinetic interactions but also risk of QT prolongation particularly when given with concomitant drugs that can prolong QT), chloroquine and hydroxychloroquine (both 7% RED and 27% AMBER, victims of some interactions due to metabolic profile but also perpetrators of QT prolongation) posing the greatest risk. With management, these risks can be mitigated. We have published a drug–drug interaction resource to facilitate medication review for the critically ill patient.

Cytochrome P450 3. Clinically Significant Drug Interactions

2000 ◽  
Vol 30 (4) ◽  
pp. 146-149 ◽  
Author(s):  
Ross A McKinnon ◽  
Allan M Evans
Keyword(s):  
Cytochrome P450 ◽  
Drug Interactions ◽  
Clinically Significant

Drug Interactions of Macrolides: Emphasis on Dirithromycin

1997 ◽  
Vol 31 (3) ◽  
pp. 349-356 ◽  
Author(s):  
Vish S Watkins ◽  
Ron E Polk ◽  
Jennifer L Stotka
Keyword(s):  
Cytochrome P450 ◽  
Drug Interactions ◽  
Ethinyl Estradiol ◽  
Enzyme System ◽  
Cytochrome P450 Enzyme ◽  
Cytochrome P450 Enzymes ◽  
Kidney Transplant Recipients ◽  
P450 Enzyme ◽  
Cytochrome P450 Enzyme System ◽  
Clinically Significant

Objective To describe the drug interactions of dirithromycin, a new macrolide, and to compare them with those of other macrolides. Data Sources A literature search was performed using MEDLINE to identify articles published between January 1980 and July 1995 concerning the drug interactions of macrolides. Published abstracts were also examined. All studies using dirithromycin were performed under the sponsorship of Eli Lilly and Company. Data Synthesis Erythromycin, the first macrolide discovered, is metabolized by the cytochrome P450 enzyme system. By decreasing their metabolism, erythromycin can interact with other drugs metabolized by the cytochrome P450 enzymes. The lack of such interactions would be a desirable feature in a newer macrolide. We describe studies performed to detect any interactions of dirithromycin with cyclosporine, theophylline, terfenadine, warfarin, and ethinyl estradiol. The studies showed that dirithromycin, like azithromycin, is much less likely to cause the interactions detected with clarithromycin and erythromycin. A review of the literature showed differences among macrolides in their abilities to inhibit cytochrome P450 enzymes and, thus, to cause drug–drug interactions. Erythromycin and clarithromycin inhibit cytochrome P450 enzymes, and have been implicated in clinically significant interactions. Azithromycin and dirithromycin neither inhibit cytochrome P450 enzymes nor are implicated in clinically significant drug–drug interactions. Conclusions Dirithromycin, a new macrolide, does not inhibit the cytochrome P450 enzyme system. The concomitant use of dirithromycin with cyclosporine, theophylline, terfenadine, warfarin, or ethinyl estradiol was studied in pharmacokinetic and pharmacodynamic studies. In vitro, dirithromycin did not bind cytochrome P450. In healthy subjects, erythromycin increases the clearance of cyclosporine by 51%, whereas dirithromycin causes no significant changes in the pharmacokinetics of cyclosporine. In kidney transplant recipients, administration of dirithromycin was associated with a significant (p < 0.003) decrease of 17.4% in the clearance of cyclosporine. In patients taking low-dose estradiol, the administration of dirithromycin caused a significant (p < 0.03) increase of 9.9% in the clearance of ethinyl estradiol; escape ovulation did not occur. Unlike erythromycin and clarithromycin, dirithromycin had no significant effects on the pharmacokinetics of theophylline, terfenadine, or warfarin. The alterations typical of drug interactions that are based on inhibition of the cytochrome P450 system occurring with erythromycin and clarithromycin were not observed with dirithromycin.

Lack of Clinically Significant Drug−Drug Interactions for Dalcetrapib Coadministered with Simvastatin

2009 ◽  
Vol 3 (3) ◽  
pp. 234-235
Author(s):  
Michael Derks ◽  
Markus Abt ◽  
Mary Phelan
Keyword(s):  
Drug Interactions ◽  
Clinically Significant

scholarly journals A multicentered pharmacoepidemiological approach to evaluate clinically significant potential drug–drug interactions in medical intensive care settings in Pakistan

2018 ◽  
Vol 25 (4) ◽  
pp. 190-195 ◽  
Author(s):  
Faisal Shakeel ◽  
Jamshaid Ali Khan ◽  
Muhammad Aamir ◽  
Syed Muhammad Asim ◽  
Irfan Ullah
Keyword(s):  
Intensive Care ◽  
Drug Interactions ◽  
Intensive Care Units ◽  
Potential Drug ◽  
Significant Potential ◽  
Significant Difference ◽  
Tertiary Hospitals ◽  
Medical Intensive Care ◽  
Clinically Significant ◽  
Multiple Drugs

Background: Iatrogenic injuries due to drug–drug interactions are particularly significant in critical care units because of the severely compromised state of the patient. The risk further increases with the use of multiple drugs, increasing age, and stay of the patient. Objective: The aim was to assess potential drug–drug interactions, evaluate clinically significant potential drug–drug interactions and their predictors in medical intensive care units of tertiary hospitals in Pakistan. Methods: Analysis of patient data collected from medical intensive care units of tertiary hospitals in Pakistan were carried out using Micromedex DrugReax. Various statistical tools were applied to identify the significance of associated predictors. Results: In a total of 830 patients, prevalence of potential drug–drug interactions was found to be 39%. These attributed to 190 drug combinations, of which 15.4% were clinically significant. A significant association of potential drug–drug interactions was present with number of prescribed drugs, age, and gender. In terms of clinically significant potential drug–drug interactions, the association was significant with increasing age. Moreover, one-way analysis of variance revealed a significant difference in the means of potential drug–drug interactions among the four hospitals. Conclusion: A prevalence of 39% potential drug–drug interactions was observed in patients of medical intensive care unit, with 22.8% being clinically significant. These attributed to nine drug pairs and could easily be avoided to reduce the risk of adverse effects from potential drug–drug interactions.

The Potential for Clinically Significant Drug-Drug Interactions Involving the CYP 2D6 System: Effects with Fluoxetine and Paroxetine versus Sertraline

2007 ◽  
Vol 13 (1) ◽  
pp. 5-12 ◽  
Author(s):  
SHELDON H. PRESKORN ◽  
ROZINA SHAH ◽  
MELISSA NEFF ◽  
AMANDA L. GOLBECK ◽  
JOE CHOI
Keyword(s):  
Drug Interactions ◽  
Clinically Significant ◽  
Cyp 2D6
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