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

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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.

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          Author and article information

          Journal
          Drug Discovery Today
          Drug Discovery Today
          Elsevier BV
          13596446
          April 2019
          April 2019
          : 24
          : 4
          : 933-938
          Article
          10.1016/j.drudis.2019.01.008
          30690198
          5446e827-b86f-4ad6-ba47-be73da440e2e
          © 2019

          https://www.elsevier.com/tdm/userlicense/1.0/

          http://creativecommons.org/licenses/by/4.0/


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