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On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine
The complexity of orphan diseases, which are those that do not have an effective treatment, together with the high dimensionality of the genetic data used for their analysis and the high degree of uncertainty in the understanding of the mechanisms and genetic pathways which are involved in their dev...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090191/ https://www.ncbi.nlm.nih.gov/pubmed/32256101 http://dx.doi.org/10.2147/PGPM.S205082 |
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author | Álvarez-Machancoses, Óscar DeAndrés Galiana, Enrique J Cernea, Ana Fernández de la Viña, J Fernández-Martínez, Juan Luis |
author_facet | Álvarez-Machancoses, Óscar DeAndrés Galiana, Enrique J Cernea, Ana Fernández de la Viña, J Fernández-Martínez, Juan Luis |
author_sort | Álvarez-Machancoses, Óscar |
collection | PubMed |
description | The complexity of orphan diseases, which are those that do not have an effective treatment, together with the high dimensionality of the genetic data used for their analysis and the high degree of uncertainty in the understanding of the mechanisms and genetic pathways which are involved in their development, motivate the use of advanced techniques of artificial intelligence and in-depth knowledge of molecular biology, which is crucial in order to find plausible solutions in drug design, including drug repositioning. Particularly, we show that the use of robust deep sampling methodologies of the altered genetics serves to obtain meaningful results and dramatically decreases the cost of research and development in drug design, influencing very positively the use of precision medicine and the outcomes in patients. The target-centric approach and the use of strong prior hypotheses that are not matched against reality (disease genetic data) are undoubtedly the cause of the high number of drug design failures and attrition rates. Sampling and prediction under uncertain conditions cannot be avoided in the development of precision medicine. |
format | Online Article Text |
id | pubmed-7090191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-70901912020-04-01 On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine Álvarez-Machancoses, Óscar DeAndrés Galiana, Enrique J Cernea, Ana Fernández de la Viña, J Fernández-Martínez, Juan Luis Pharmgenomics Pers Med Review The complexity of orphan diseases, which are those that do not have an effective treatment, together with the high dimensionality of the genetic data used for their analysis and the high degree of uncertainty in the understanding of the mechanisms and genetic pathways which are involved in their development, motivate the use of advanced techniques of artificial intelligence and in-depth knowledge of molecular biology, which is crucial in order to find plausible solutions in drug design, including drug repositioning. Particularly, we show that the use of robust deep sampling methodologies of the altered genetics serves to obtain meaningful results and dramatically decreases the cost of research and development in drug design, influencing very positively the use of precision medicine and the outcomes in patients. The target-centric approach and the use of strong prior hypotheses that are not matched against reality (disease genetic data) are undoubtedly the cause of the high number of drug design failures and attrition rates. Sampling and prediction under uncertain conditions cannot be avoided in the development of precision medicine. Dove 2020-03-19 /pmc/articles/PMC7090191/ /pubmed/32256101 http://dx.doi.org/10.2147/PGPM.S205082 Text en © 2020 Álvarez-Machancoses et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Review Álvarez-Machancoses, Óscar DeAndrés Galiana, Enrique J Cernea, Ana Fernández de la Viña, J Fernández-Martínez, Juan Luis On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title | On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title_full | On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title_fullStr | On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title_full_unstemmed | On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title_short | On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine |
title_sort | on the role of artificial intelligence in genomics to enhance precision medicine |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090191/ https://www.ncbi.nlm.nih.gov/pubmed/32256101 http://dx.doi.org/10.2147/PGPM.S205082 |
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