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Article

COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments

1
School of Cybersecurity, Data Science and Computing, Norwich University, Northfield, VT 05663, USA
2
Sano Centre for Computational Medicine, 30-072 Kraków, Poland
3
Department of Pharmaceutical and Administrative Sciences, University of Charleston, Charleston, WV 25304, USA
4
School of Computing Technologies, RMIT University, Melbourne 3001, Australia
5
School of Computing and Information Systems, The University of Melbourne, Melbourne 3010, Australia
6
Department of Computer Science, University of Vermont, Burlington, VT 05405, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Luis Cobra Branco and Miguel Santos
Pharmaceutics 2022, 14(3), 567; https://doi.org/10.3390/pharmaceutics14030567
Received: 31 December 2021 / Revised: 25 February 2022 / Accepted: 25 February 2022 / Published: 4 March 2022
(This article belongs to the Special Issue Therapeutic Formulations of Repurposed Drugs against COVID-19)
Background: With the Coronavirus becoming a new reality of our world, global efforts continue to seek answers to many questions regarding the spread, variants, vaccinations, and medications. Particularly, with the emergence of several strains (e.g., Delta, Omicron), vaccines will need further development to offer complete protection against the new variants. It is critical to identify antiviral treatments while the development of vaccines continues. In this regard, the repurposing of already FDA-approved drugs remains a major effort. In this paper, we investigate the hypothesis that a combination of FDA-approved drugs may be considered as a candidate for COVID-19 treatment if (1) there exists an evidence in the COVID-19 biomedical literature that suggests such a combination, and (2) there is match in the clinical trials space that validates this drug combination. Methods: We present a computational framework that is designed for detecting drug combinations, using the following components (a) a Text-mining module: to extract drug names from the abstract section of the biomedical publications and the intervention/treatment sections of clinical trial records. (b) a network model constructed from the drug names and their associations, (c) a clique similarity algorithm to identify candidate drug treatments. Result and Conclusions: Our framework has identified treatments in the form of two, three, or four drug combinations (e.g., hydroxychloroquine, doxycycline, and azithromycin). The identifications of the various treatment candidates provided sufficient evidence that supports the trustworthiness of our hypothesis. View Full-Text
Keywords: Coronavirus pandemic; COVID-19 treatment; drug repurposing; adjuvant treatment; clinical trials ground-truth; drug association maps; literature mining; clique identification Coronavirus pandemic; COVID-19 treatment; drug repurposing; adjuvant treatment; clinical trials ground-truth; drug association maps; literature mining; clique identification
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MDPI and ACS Style

Hamed, A.A.; Fandy, T.E.; Tkaczuk, K.L.; Verspoor, K.; Lee, B.S. COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments. Pharmaceutics 2022, 14, 567. https://doi.org/10.3390/pharmaceutics14030567

AMA Style

Hamed AA, Fandy TE, Tkaczuk KL, Verspoor K, Lee BS. COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments. Pharmaceutics. 2022; 14(3):567. https://doi.org/10.3390/pharmaceutics14030567

Chicago/Turabian Style

Hamed, Ahmed Abdeen, Tamer E. Fandy, Karolina L. Tkaczuk, Karin Verspoor, and Byung Suk Lee. 2022. "COVID-19 Drug Repurposing: A Network-Based Framework for Exploring Biomedical Literature and Clinical Trials for Possible Treatments" Pharmaceutics 14, no. 3: 567. https://doi.org/10.3390/pharmaceutics14030567

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