New hope for effective COVID-19 treatment? – Drug repurposing with the computational framework

New hope for effective COVID-19 treatment? – Drug repurposing with the computational framework

Almost two years have passed since the outbreak of the pandemic, during which hundreds of thousands of scientific publications related to COVID-19 have been published. Hence, can we say that we already know everything about SARS-CoV-2? Our scientists Ahmed Abdeen Hamed and Karolina L. Tkaczuk, in their latest article, published in Pharmaceutics, pose a bold question whether the combination of FDA-approved drugs may be considered as a candidate for COVID-19 treatment and provide specific answers to it. All this with using a computational framework that can undeniably revolutionize therapy planning and implementation of innovative treatments. 

COVID-19 without any doubt is a disease, which has already put a huge impact on the evolution of science. Development of the vaccines in a significantly compressed timeline, discovering and implementing modern methods of disease prevention and clinical trials aimed at drug repurposing to treat the new disease. These are amazing achievements, and the last one is attracting more and more scientists. It is not surprising then that Sano experts, who are specialists in computational medicine, decided to use these methods in COVID-19 drug repurposing, which significance in this process is undeniable as they emphasized. To achieve the goal – they investigated the hypothesis that a combination of FDA-approved drugs may be considered as a candidate for COVID-19 treatment. However, there were two circumstances (1) evidence in the COVID-19 biomedical literature that suggests such a combination, and (2) a match in the clinical trials space that validates this drug combination it was used a computational framework with: a text-mining module, a network model constructed from the drug names and their associations and a clique similarity algorithm to identify candidate drug treatments.  

In the study, it was used a set of 110,000 COVID-19 related publications including biomedical literature and clinical trial records. As a result, there were identified treatments in the form of two, three, or four-drug combinations (e.g., hydroxychloroquine, doxycycline, and azithromycin). It was indicated whether the combinations of drugs presented in selected publications are possible or not, which may bring benefits and which may not in COVID-19 treatment. The identifications of the various treatment candidates provided sufficient evidence that supports the trustworthiness of the hypothesis what was highlighted by the authors. Is that all? It is certainly a good start and promising results, but the road is still long and the results of subsequent works may knock us to our knees and revolutionize the future treatment of not only COVID-19 but also other diseases. 

Read more at: www.mdpi.com/1999-4923/14/3/567