Back in 2016, FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles were published in Scientific Data to help companies find, use (and reuse) the data most relevant to them. But new data is produced on a daily basis and many companies have struggled to implement the FAIR measures.
The Pistoia Alliance – an organization that seeks to lower the barrier to R&D and innovation – is looking to lend a helping hand. Alongside Roche and Bayer, the Pistoia Alliance has launched its FAIR Implementation project to develop a data management toolkit, which will consist of best practices, training materials, use cases, and methodology for change management – all aiming to help companies manage the wave of change that digitalization has brought to the pharma industry.
“We created the FAIR project because it is better to work together as industry peers and share our expertise, rather than have each organization attempting to adopt FAIR by itself,” explained.
Ian Harrow, a Consultant at the Pistoia Alliance. “As the life sciences industry continues to transform digitally, the sector needs clear and practical guidance on how data and relevant metadata is captured and managed to foster greater collaborative partnerships and more effective application of artificial intelligence and machine learning.”
Earlier this year, the Pistoia Alliance hosted several workshops to discuss the toolkit. Harrow explains that it was clear that a number of pharma organizations saw the need for FAIR to make their R&D efforts more productive. “The FAIR Implementation toolkit should help drive crucial change and prevent companies from dealing with the problem of harnessing data in isolation. We hope that the FAIR toolkit being developed by this project will bring together companies to learn from each other and undergo this culture shift together.” When officially launched, the toolkit will be hosted on a user-friendly, open access website.
If companies share data, it should help improve best practices by increasing efficiency and preventing work being repeated unnecessarily; the Pistoia Alliance wants companies to recognize that not all data are proprietary, and non-competitive data could offer great value to an R&D project.
The Pistoia Alliance is also looking for other interested parties and companies to come forward and get involved in the project. To find out more please get in touch with Ian Harrow: ian.harrow@pistoiaalliance.org
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