Implementation and relevance of FAIR data principles in biopharmaceutical R&D.
Journal
Drug discovery today
ISSN: 1878-5832
Titre abrégé: Drug Discov Today
Pays: England
ID NLM: 9604391
Informations de publication
Date de publication:
04 2019
04 2019
Historique:
received:
20
10
2018
revised:
21
12
2018
accepted:
20
01
2019
pubmed:
29
1
2019
medline:
18
1
2020
entrez:
29
1
2019
Statut:
ppublish
Résumé
Biopharmaceutical industry R&D, and indeed other life sciences R&D such as biomedical, environmental, agricultural and food production, is becoming increasingly data-driven and can significantly improve its efficiency and effectiveness by implementing the FAIR (findable, accessible, interoperable, reusable) guiding principles for scientific data management and stewardship. By so doing, the plethora of new and powerful analytical tools such as artificial intelligence and machine learning will be able, automatically and at scale, to access the data from which they learn, and on which they thrive. FAIR is a fundamental enabler for digital transformation.
Identifiants
pubmed: 30690198
pii: S1359-6446(18)30303-9
doi: 10.1016/j.drudis.2019.01.008
pii:
doi:
Substances chimiques
Biological Products
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
933-938Informations de copyright
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.