Abstract
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.
Highlights
With the virus constantly mutating and new strains are emerging (e.g., Delta [1], Omicron [2]), much research is needed to decide the efficay of the available vaccines against the new variants
We compared the cliques of the same size with the cliques resulting from the clinical trial records
The very small number of cliques found in the network contructed from the clinical trial records (92 cliques) eliminated 3551 cliques detected from the publications
Summary
With the virus constantly mutating and new strains are emerging (e.g., Delta [1], Omicron [2]), much research is needed to decide the efficay of the available vaccines against the new variants. The oral antiviral molnupiravir, which was originally FDA-approved for SARS-COV, shows to reduce the risk of hospitalization or death by approximatly 50% in COVID-19 patients [3]. A recent clinical trial concluded that the two drugs combined have reduced the risk of hospitalization or death. 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. We investigate the hypothesis that a combination of FDA-approved drugs may be considered as a candidate for COVID19 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
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