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

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...

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Veröffentlicht in:Therapeutic advances in drug safety 2021, Vol.12, p.20420986211041277-20420986211041277
Hauptverfasser: Thomas, Levin, Birangal, Sumit Raosaheb, Ray, Rajdeep, Sekhar Miraj, Sonal, Munisamy, Murali, Varma, Muralidhar, S.V., Chidananda Sanju, Banerjee, Mithu, Shenoy, Gautham G., Rao, Mahadev
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Zusammenfassung: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
ISSN:2042-0986
2042-0994
DOI:10.1177/20420986211041277