Alharbi E, Skeva R, Juty N, Jay C, Goble C. A FAIR-Decide framework for pharmaceutical R&D: FAIR data cost-benefit assessment.
Drug Discov Today 2023;
28:103510. [PMID:
36716952 DOI:
10.1016/j.drudis.2023.103510]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 01/24/2023] [Accepted: 01/24/2023] [Indexed: 01/29/2023]
Abstract
The FAIR (findable, accessible, interoperable and reusable) principles are data management and stewardship guidelines aimed at increasing the effective use of scientific research data. Adherence to these principles in managing data assets in pharmaceutical research and development (R&D) offers pharmaceutical companies the potential to maximise the value of such assets, but the endeavour is costly and challenging. We describe the 'FAIR-Decide' framework, which aims to guide decision-making on the retrospective FAIRification of existing datasets by using business analysis techniques to estimate costs and expected benefits. This framework supports decision-making on FAIRification in the pharmaceutical R&D industry and can be integrated into a company's data management strategy.
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