As life-science organizations race to adopt (generative) AI, one point begins to stand out: your AI is only as good as your data. While large language models (LLMs) offer powerful capabilities, they’re not tailored to specialized scientific data—and do need a solid data foundation. Making data Findable, Accessible, Interoperable, and Reusable (FAIR) enables AI systems […]
Beyond Research: Realizing the Value of FAIR Initiatives The FAIR Community has undertaken an extensive survey to assess the impact of FAIR data in life science companies. Our new report examines the most significant business drivers for implementing FAIR data principles and the key outcomes being delivered. Pharmaceutical companies are applying FAIR in research and […]
As life-science organizations race to adopt (generative) AI, one point begins to stand out: your AI is only as good as your data. While large language models (LLMs) offer powerful capabilities, they’re not tailored to specialized scientific data—and do need a solid data foundation. Making data Findable, Accessible, Interoperable, and Reusable (FAIR) enables AI systems […]
March 2025 Poster
The FAIR Maturity Matrix (FAIRMM) is a descriptive (self-)assessment instrument for Leadership and Communities of FAIR data practitioners evolving in the life-sciences. It provides a frame for actionable conversations, aligning stakeholders towards shared FAIR implementation goals.
To create value and guide strategic decision-making in lifescience organisations, data needs to be Findable, Accessible, Interoperable and Reusable (FAIR) both by humans and machines. The Pistoia Alliance FAIR –for-Pharma Community of Experts to enables the implementation of FAIR data principles in the life sciences. We have two working groups: FAIR for Business and FAIR […]
This project aims to convert the biological assay protocols contained in research publications into a machine-readable FAIR format.
To create value and guide strategic decision-making in pharmaceutical and healthcareorganisations, data needs to be Findable, Accessible, Interoperable and Reusable (FAIR) both byhumans and machines. The objective of the Pistoia Alliance FAIR implementation Community ofExperts (CoE) is to enable the implementation of FAIR data principles in the life sciences
This project aimed to establish best practices for data visualization, support life science research, and identify opportunities for communicating and implementing these best practices.
The FAIR Maturity Matrix is a descriptive (self-)assessment instrument for Leadership and Communities of FAIR data practitioners evolving in the life-sciences. It provides a frame for actionable conversations, aligning stakeholders towards shared FAIR implementation goals.
To create value and guide strategic decision-making in pharma and Life Science companies, data needs to be Findable, Accessible, Interoperable and Reusable (FAIR) both by humans and machines. The objective of the Pistoia Alliance FAIR implementation project , from its inception in 2019 to today, is to enable precompetitive instruments for the implementation of FAIR […]
This Community of Experts supports the implementation of the Findable, Accessible, Interoperable and Re-usable (FAIR) guiding principles in the life sciences by promoting best practices as well as supporting enabling methods and tools across industries.
