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Implementation and Relevance of FAIR Data Principles in Biopharmaceutical Research and Development

John, Wise and Ian, Harrow and Rafael, Jimenez and Eric, Little and Kees, van Bochove and Gaspare, Mellino and Victoria, Hedley and Splendiani, Andrea and Alexandra, Grebe de Barron and Peter, Walgemond and Vibhor, Gupta and Jan, Taubert and Tom, Plasterer and Rainer, Winnenberg and Beeta, Balali-Mood and Drashiti, Vasant and Ian, Smith (2019) Implementation and Relevance of FAIR Data Principles in Biopharmaceutical Research and Development. Drug discovery today. ISSN 13596446

Abstract

Biopharmaceutical industry R&D, and indeed other Life Sciences R&D such as agri-food, is 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.

Item Type: Article
Keywords: FAIR, Data management, ontologies
Date Deposited: 19 Mar 2019 00:45
Last Modified: 19 Mar 2019 00:45
URI: https://oak.novartis.com/id/eprint/38113

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