Pistoia Alliance launches FAIR data principles toolkit


The free toolkit has been backed by major pharma to improve data management and data sharing, supporting AI and machine learning

Pistoia Alliance launches FAIR data principles toolkit

The Pistoia Alliance, a global, not-for-profit alliance that works to lower barriers to innovation in life sciences R&D, has launched a freely accessible toolkit to help companies implement the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles for data management and stewardship.

The project is funded by large pharmaceutical companies and SMEs alike, including AstraZeneca, Bayer, Roche, Novartis, Bristol-Myers Squibb, AbbVie and Copyright Clearance Center. Collated by experts in the field, the toolkit contains numerous method tools, training and change management, as well as use cases, allowing organisations to learn from industry successes.

As the life sciences industry continues to digitise, the FAIR guiding principles of Findable, Accessible, Interoperable and Reusable data will help organisations realise their digital transformation, make preparations for the Lab of the Future (LoTF), and accelerate the application of AI and deep learning.

"At Roche, we know that implementing the FAIR principles can be difficult for biotech and pharma organisations of every size, so we are very pleased to lead on this project and help make the process easier," said Dr Martin Romacker, Principal Scientist at Roche. "The toolkit will help to smooth the path to greater data sharing within and between industries, which is critical to future research efforts. We see the FAIR guiding principles as a worthy goal, and one which will help the industry realise the value of technologies like deep learning."

Although organisations have become increasingly aware of data as an asset, data are often siloed, stored in varying formats, and difficult to retrieve or share. Adopting the FAIR principles helps companies break down internal siloes and cope with the growing volume and complexity of data generated.

The FAIR guiding principles were published in 2016 (Wilkinson,et al.) as a blueprint for well managed and machine-actionable data to allow computational systems to find, access, interoperate and reuse data with minimal human intervention. However, further research (Wise et al. 2019) found that many companies are still struggling with implementation of the principles.

"We are delighted to be working with our peers to facilitate this culture change and forge the path for industry-wide FAIR implementation," said Dr Alexandra Grebe de Barron, IT Business Partner at Bayer. "The launch of the toolkit is coming at a time when life science companies are assessing how they store and manage data to meet new requirements and successfully embark on digital transformation projects. By collaborating with colleagues and partners, we can better realise the value of AI and advanced analytics."

"Since we launched the project, we have had tremendous interest from global pharma as well SMEs, demonstrating just how important a resource like this is for the entire life science industry," explained Ian Harrow, Consultant at The Pistoia Alliance.

Sign up for your free email newsletter

The FAIR toolkit is available now. The Pistoia Alliance has worked with its industry partners to ensure that the toolkit remains compatible with other FAIR data standardisation projects, like the IMI FAIRplus project.