Abstract
•Implementing FAIR in pharmaceutical R&D is a costly and challenging endeavour.•None of the existing approaches for implementing FAIR principles in drug R&D address the need for a decision framework.•The application of business analysis techniques to tackle the prioritisation of data assets for FAIRification plays a critical role in facilitating FAIR implementation.
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.