A FAIR-Decide framework for pharmaceutical R&D: FAIR data cost–benefit assessment

Ebtisam Alharbi, Rigina Skeva, Nick Juty, Caroline Jay, Carole Goble

Research output: Contribution to journalArticlepeer-review

62 Downloads (Pure)


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.
Original languageEnglish
Article number103510
JournalDrug discovery today
Issue number4
Early online date27 Jan 2023
Publication statusPublished - 1 Apr 2023


  • FAIR data
  • FAIRification
  • Pharmaceutical R&D
  • cost-benefit
  • decision-making process


Dive into the research topics of 'A FAIR-Decide framework for pharmaceutical R&D: FAIR data cost–benefit assessment'. Together they form a unique fingerprint.

Cite this