Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Nov 30, 2020)
Date Submitted: May 7, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A Data Driven Approach to Profile Potential SARS-CoV-2 Drug Interactions Using TylerADE
ABSTRACT
We use a data driven approach on a cleaned FAERS database to determine the adverse drug reaction severity of several covid-19 drug combinations and further investigate their safety for vulnerable populations such as individuals 65 years and older. Our key findings include 1. hydroxychloroquine/chloroquine is associated with increased adverse drug event severity versus other drug combinations already not recommended by NIH treatment guidelines, 2. hydroxychloroquine/azithromycin is associated with lower adverse drug event severity among older populations and 3. lopinavir/ritonavir has lower adverse reaction severity among toddlers. While this approach does not consider drug efficacy, it can help prioritize clinical trials for drug combinations by focusing on those combinations with decreased adverse drug reaction severity.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.