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Updated: Sep 22, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?
Ebtisam Alharbi1, Yojana Gadiya2, David Henderson3
1Department of Computer Science, The University of Manchester, Oxford Road, Manchester, UK; College of Computer and Information Systems, Umm Al-Qura University, Mecca, Saudi Arabia.
Abstract:
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.
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