Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?

Ebtisam Alharbi, Yojana Gadiya, David Henderson, Andrea Zaliani, Alejandra Delfin-rossaro, Anne Cambon-thomsen, Manfred Kohler, Gesa Witt, Danielle Welter, Nick Juty, Caroline Jay, Ola Engkvist, Carole Goble, Dorothy S. Reilly, Venkata Satagopam, Vassilios Ioannidis, Wei Gu, Philip Gribbon

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Despite the intuitive value of adopting the Findable, Accessible, Interoperable, and Reusable (FAIR) principles in both academic and industrial sectors, challenges exist in resourcing, balancing long- versus short-term priorities, and achieving technical implementation. This situation is exacerbated by the unclear mechanisms by which costs and benefits can be assessed when decisions on FAIR are made. Scientific and research and development (R&D) leadership need reliable evidence of the potential benefits and information on effective implementation mechanisms and remediating strategies. In this article, we describe procedures for cost–benefit evaluation, and identify best-practice approaches to support the decision-making process involved in FAIR implementation.
Original languageEnglish
Pages (from-to)2080-2085
Number of pages6
JournalDrug discovery today
Issue number8
Early online date17 May 2022
Publication statusPublished - 1 Aug 2022


  • Cost–benefit
  • Drug discovery
  • FAIR
  • FAIRification
  • Pharmaceutical R&D


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  • The FAIR Guiding Principles for scientific data management and stewardship

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