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Artificial Intelligence and Antibiotic Discovery
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 f...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614913/ https://www.ncbi.nlm.nih.gov/pubmed/34827314 http://dx.doi.org/10.3390/antibiotics10111376 |
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author | David, Liliana Brata, Anca Monica Mogosan, Cristina Pop, Cristina Czako, Zoltan Muresan, Lucian Ismaiel, Abdulrahman Dumitrascu, Dinu Iuliu Leucuta, Daniel Corneliu Stanculete, Mihaela Fadygas Iaru, Irina Popa, Stefan Lucian |
author_facet | David, Liliana Brata, Anca Monica Mogosan, Cristina Pop, Cristina Czako, Zoltan Muresan, Lucian Ismaiel, Abdulrahman Dumitrascu, Dinu Iuliu Leucuta, Daniel Corneliu Stanculete, Mihaela Fadygas Iaru, Irina Popa, Stefan Lucian |
author_sort | David, Liliana |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8614913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86149132021-11-26 Artificial Intelligence and Antibiotic Discovery David, Liliana Brata, Anca Monica Mogosan, Cristina Pop, Cristina Czako, Zoltan Muresan, Lucian Ismaiel, Abdulrahman Dumitrascu, Dinu Iuliu Leucuta, Daniel Corneliu Stanculete, Mihaela Fadygas Iaru, Irina Popa, Stefan Lucian Antibiotics (Basel) Review 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. MDPI 2021-11-10 /pmc/articles/PMC8614913/ /pubmed/34827314 http://dx.doi.org/10.3390/antibiotics10111376 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review David, Liliana Brata, Anca Monica Mogosan, Cristina Pop, Cristina Czako, Zoltan Muresan, Lucian Ismaiel, Abdulrahman Dumitrascu, Dinu Iuliu Leucuta, Daniel Corneliu Stanculete, Mihaela Fadygas Iaru, Irina Popa, Stefan Lucian Artificial Intelligence and Antibiotic Discovery |
title | Artificial Intelligence and Antibiotic Discovery |
title_full | Artificial Intelligence and Antibiotic Discovery |
title_fullStr | Artificial Intelligence and Antibiotic Discovery |
title_full_unstemmed | Artificial Intelligence and Antibiotic Discovery |
title_short | Artificial Intelligence and Antibiotic Discovery |
title_sort | artificial intelligence and antibiotic discovery |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614913/ https://www.ncbi.nlm.nih.gov/pubmed/34827314 http://dx.doi.org/10.3390/antibiotics10111376 |
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