Artificial Intelligence and Antibiotic Discovery.
antibiotic development
antibiotic discovery
antibiotic resistance
artificial intelligence
automated antibiotic discovery
computer-aided drug design
deep learning
future of medicine
machine learning
Journal
Antibiotics (Basel, Switzerland)
ISSN: 2079-6382
Titre abrégé: Antibiotics (Basel)
Pays: Switzerland
ID NLM: 101637404
Informations de publication
Date de publication:
10 Nov 2021
10 Nov 2021
Historique:
received:
13
10
2021
revised:
01
11
2021
accepted:
08
11
2021
entrez:
27
11
2021
pubmed:
28
11
2021
medline:
28
11
2021
Statut:
epublish
Résumé
Over recent decades, a new antibiotic crisis has been unfolding due to a decreased research in this domain, a low return of investment for the companies that developed the drug, a lengthy and difficult research process, a low success rate for candidate molecules, an increased use of antibiotics in farms and an overall inappropriate use of antibiotics. This has led to a series of pathogens developing antibiotic resistance, which poses severe threats to public health systems while also driving up the costs of hospitalization and treatment. Moreover, without proper action and collaboration between academic and health institutions, a catastrophic trend might develop, with the possibility of returning to a pre-antibiotic era. Nevertheless, new emerging AI-based technologies have started to enter the field of antibiotic and drug development, offering a new perspective to an ever-growing problem. Cheaper and faster research can be achieved through algorithms that identify hit compounds, thereby further accelerating the development of new antibiotics, which represents a vital step in solving the current antibiotic crisis. The aim of this review is to provide an extended overview of the current artificial intelligence-based technologies that are used for antibiotic discovery, together with their technological and economic impact on the industrial sector.
Identifiants
pubmed: 34827314
pii: antibiotics10111376
doi: 10.3390/antibiotics10111376
pmc: PMC8614913
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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