Mostrar el registro sencillo del ítem

dc.contributor.author
Cavasotto, Claudio Norberto  
dc.contributor.author
Di Filippo, Juan Ignacio  
dc.date.available
2022-12-22T15:32:00Z  
dc.date.issued
2021-01  
dc.identifier.citation
Cavasotto, Claudio Norberto; Di Filippo, Juan Ignacio; Artificial intelligence in the early stages of drug discovery; Elsevier Science Inc.; Archives of Biochemistry and Biophysics; 698; 108730; 1-2021; 1-20  
dc.identifier.issn
0003-9861  
dc.identifier.uri
http://hdl.handle.net/11336/182200  
dc.description.abstract
Although the use of computational methods within the pharmaceutical industry is well established, there is an urgent need for new approaches that can improve and optimize the pipeline of drug discovery and development. In spite of the fact that there is no unique solution for this need for innovation, there has recently been a strong interest in the use of Artificial Intelligence for this purpose. As a matter of fact, not only there have been major contributions from the scientific community in this respect, but there has also been a growing partnership between the pharmaceutical industry and Artificial Intelligence companies. Beyond these contributions and efforts there is an underlying question, which we intend to discuss in this review: can the intrinsic difficulties within the drug discovery process be overcome with the implementation of Artificial Intelligence? While this is an open question, in this work we will focus on the advantages that these algorithms provide over the traditional methods in the context of early drug discovery.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science Inc.  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ARTIFICIAL INTELLIGENCE  
dc.subject
DEEP LEARNING  
dc.subject
DRUG DISCOVERY  
dc.subject
HIT AND LEAD IDENTIFICATION  
dc.subject
MACHINE LEARNING  
dc.subject
PROPERTY PREDICTION  
dc.subject
TARGET IDENTIFICATION  
dc.subject.classification
Otras Ciencias Químicas  
dc.subject.classification
Ciencias Químicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Artificial intelligence in the early stages of drug discovery  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2022-09-21T14:10:05Z  
dc.journal.volume
698  
dc.journal.number
108730  
dc.journal.pagination
1-20  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Cavasotto, Claudio Norberto. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina  
dc.description.fil
Fil: Di Filippo, Juan Ignacio. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina  
dc.journal.title
Archives of Biochemistry and Biophysics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.abb.2020.108730  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0003986120307384