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Journal of personalized medicine
Sep 18, 2021;11 (9):

A Systematic Review on the Contribution of Artificial Intelligence in the Development of Medicines for COVID-2019.

Carla Pires
Author Information
  1. Carla Pires: CBIOS, Escola de Ciências e Tecnologias da Saúde, Universidade Lusófona's Research Center for Biosciences and Health Technologies, Campo Grande 376, 1749-024 Lisboa, Portugal. ORCID
PMID: 34575703 DOI: 10.3390/jpm11090926

Abstract

BACKGROUND: COVID-2019 pandemic lead to a raised interest on the development of new treatments through Artificial Intelligence (AI).
AIM: to carry out a systematic review on the development of repurposed drugs against COVID-2019 through the application of AI.
METHODS: The Systematic Reviews and Meta-Analyses (PRISMA) checklist was applied.
KEYWORDS: ["Artificial intelligence" and (COVID or SARS) and (medicine or drug)]. Databases: PubMed, DOAJ and SciELO. Cochrane Library was additionally screened to identify previous published reviews on the same topic.
RESULTS: From the 277 identified records [PubMed (n = 157); DOAJ ( = 119) and SciELO ( = 1)], 27 studies were included. Among other, the selected studies on new treatments against COVID-2019 were classified, as follows: studies with in-vitro and/or clinical data; association of known drugs; and other studies related to repurposing of drugs.
CONCLUSION: Diverse potentially repurposed drugs against COVID-2019 were identified. The repurposed drugs were mainly from antivirals, antibiotics, anticancer, anti-inflammatory, and Angiotensin-converting enzyme 2 (ACE2) groups, although diverse other pharmacologic groups were covered. AI was a suitable tool to quickly analyze large amounts of data or to estimate drug repurposing against COVID-2019.

Keywords

COVID-2019 SARS-CoV-2 artificial intelligence drug design in silico methods machine learning medicines molecular docking molecular dynamics repurposing of drugs

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Journal Article Review

Word Cloud

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