Aside from the immediate potential for loss of life and strain on healthcare services, the socioeconomic impact of COVID-19 brings an urgency to develop effective strategies for preventing and treating the disease.

 

Where vaccines and therapy are concerned, the development of a new vaccine requires at least 12 months, and new drug therapies, from research to marketing approval, typically run 10 or more years.

 

As such, finding treatments in a more reduced timeline is achieved by repurposing existing drugs, with known human pharmacological and safety profiles.

 

After the relative breakthroughs concerning the use of remdesivir and dexamethasone for the treatment of COVID-19, various ongoing trials, like large-scale WHO’s Solidarity, France’s DisCoVery and the University of Oxford’s RECOVERY, or more focused, drug-specific trials for immunomodulators (infliximab, tocilizumab, sarilumab, baricitinib, anakinra), corticosteroids (dexamethasone, prednisone, methylprednisolone), antivirals (favipiravir) and non-steroidal anti-inflammatory drugs (ibuprofen), among others, have yet to produce more significant results, preliminary or otherwise.

 

While some drugs are identified for study empirically, one strategy for screening a large number, potentially thousands, of molecules in a relatively short amount of time is through computational analysis of existing drug databases.

 

One such study has identified 13 drugs, out of over 12 000, that inhibit viral replication, with dose response relationships and effective concentrations achievable in therapeutic doses in patients. This study highlighted apilimod, a PIKfyve kinase inhibitor, which is, as a result, the subject of a phase II clinical trial, in collaboration with Yale University.

 

While apilimod and other drugs show promise, we must await the results of carefully designed trials in order to assess the response to the SARS-CoV-2 virus in humans, and thus ascertain its effectiveness in treating this disease.

 

Melanie Salgado

Pharmacist and Medication Content Analyst

ALERT Life Sciences Computing