Your browser doesn't support javascript.
loading
How far are we from predicting multi-drug interactions during treatment for COVID-19 infection?
Lozano, Benjamin; Santibáñez, Javier; Severino, Nicolás; Saldias, Cristina; Vera, Magdalena; Retamal, Jaime; Torres, Soledad; Barrera, Nelson P.
Afiliação
  • Lozano B; Department of Physiology, Faculty of Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Santibáñez J; Department of Mathematical Engineering, Faculty of Physical and Mathematical Sciences, Universidad de Chile, Santiago, Chile.
  • Severino N; Department of Intensive Medicine, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Saldias C; School of Medicine, Faculty of Medicine, Universidad de Valparaíso, Valparaíso, Chile.
  • Vera M; Department of Intensive Medicine, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Retamal J; Department of Intensive Medicine, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
  • Torres S; CIMFAV, Faculty of Engineering, Universidad de Valparaíso, Valparaíso, Chile.
  • Barrera NP; Department of Physiology, Faculty of Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile.
Br J Pharmacol ; 179(14): 3831-3838, 2022 07.
Article em En | MEDLINE | ID: mdl-35180811
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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Injúria Renal Aguda / Tratamento Farmacológico da COVID-19 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Br J Pharmacol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Chile

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Injúria Renal Aguda / Tratamento Farmacológico da COVID-19 Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Br J Pharmacol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Chile