How far are we from predicting multi‐drug interactions during treatment for COVID‐19 infection?. (28th March 2022)

• Record Type: Journal Article
• Authors: Lozano, Benjamin; Santibáñez, Javier; Severino, Nicolás; Saldias, Cristina; Vera, Magdalena; Retamal, Jaime; Torres, Soledad; Barrera, Nelson P.
• Other Names: Stephens Gary guestEditor.; Shukla Arun guestEditor.
• Is Part Of: British journal of pharmacology. Volume 179:Number 14(2022)
• Page Start: 3831
• Page End: 3838
• Publication Date: 2022-03-28
• Subjects: acute kidney injury -- biochemical simulations -- COVID‐19 treatment -- drug‐drug interaction -- intensive care unit; Pharmacology -- Periodicals; Chemotherapy -- Periodicals; Drug Therapy -- Periodicals; Pharmacology -- Periodicals; 615.1
• DOI: 10.1111/bph.15819
• Languages: English
• ISSNs: 0007-1188

Abstract

Abstract : Seriously ill patients infected with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and hospitalized in intensive care units (ICUs) are commonly given a combination of drugs, a process known as multi‐drug treatment. After extracting data on drug–drug interactions with clinical relevance from available online platforms, we hypothesize that an overall interaction map can be generated for all drugs administered. Furthermore, by combining this approach with simulations of cellular biochemical pathways, we may be able to explain the general clinical outcome. Finally, we postulate that by applying this strategy retrospectively to a cohort of patients hospitalized in ICU, a prediction of the timing of developing acute kidney injury (AKI) could be made. Whether or not this approach can be extended to other diseases is uncertain. Still, we believe it represents a valuable pharmacological insight to help improve clinical outcomes for severely ill patients.