Evidence map›Paper›PMID 34471515›Full record

ArticleTherapeutic advances in drug safety2021

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

Levin Thomas, Sumit Raosaheb Birangal, Rajdeep Ray, Sonal Sekhar Miraj, Murali Munisamy, Muralidhar Varma, Chidananda Sanju S V, Mithu Banerjee, Gautham G Shenoy, Mahadev Rao

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in drug safety, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Levin ThomasDepartment of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Sumit Raosaheb BirangalDepartment of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Rajdeep RayDepartment of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Sonal Sekhar MirajDepartment of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.ORCID https://orcid.org/0000-0003-3660-2022
Murali MunisamyDepartment of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Muralidhar VarmaDepartment of Infectious Diseases, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.
Chidananda Sanju S VDistrict Tuberculosis Control Office, Ajjarakad, Udupi, Karnataka, India.
Mithu BanerjeeDepartment of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India.
Gautham G ShenoyDepartment of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.
Mahadev RaoProfessor and Head, Department of Pharmacy Practice, Coordinator, Centre for Translational Research, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India.ORCID https://orcid.org/0000-0003-3322-5399
Manipal Academy of Higher Education · INAll India Institute of Medical Sciences Jodhpur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTuberculosis 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.

methodsWe 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.

resultsA 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.

conclusionPredicting 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:

Indexed as

antitubercular drugsdrug–drug interactionsmolecular dockingQT prolongationrepurposed COVID-19 drugs

Identifiers

PMID34471515
PMCPMC8404633
OpenAlexW3198256236

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.