| Literature DB >> 30690198 |
John Wise1, Alexandra Grebe de Barron2, Andrea Splendiani3, Beeta Balali-Mood4, Drashtti Vasant2, Eric Little5, Gaspare Mellino6, Ian Harrow4, Ian Smith7, Jan Taubert8, Kees van Bochove9, Martin Romacker6, Peter Walgemoed10, Rafael C Jimenez11, Rainer Winnenburg12, Tom Plasterer13, Vibhor Gupta14, Victoria Hedley15.
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.Mesh：
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Year: 2019 PMID： 30690198 DOI： 10.1016/j.drudis.2019.01.008
Source DB: PubMed Journal: Drug Discov Today ISSN： 1359-6446 Impact factor: 7.851