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Implementation and relevance of FAIR data principles in biopharmaceutical R&D

Lookup NU author(s): Victoria HedleyORCiD

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Abstract

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

Publication metadata

Author(s): Wise J, Grebe de Barron A, Splendiani A, Balali-Mood B, Vasant D, Little E, Gaspare M, Harrow I, Smith I, Taubert J, van Bochove K, Romacker M, Walgemoed R, Jiminez R, Winnenburg R, Plasterer T, Gupta V, Hedley V

Publication type: Article

Publication status: Published

Journal: Drug Discovery Today

Year: 2019

Volume: 24

Issue: 4

Pages: 933-938

Print publication date: 01/04/2019

Online publication date: 01/04/2019

Acceptance date: 01/12/2018

ISSN (print): 1359-6446

ISSN (electronic): 1878-5832

Publisher: Elsevier

URL: https://doi.org/10.1016/j.drudis.2019.01.008

DOI: 10.1016/j.drudis.2019.01.008

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