Recommended

Download this feature partnership: Continuous manufacturing: an evolving technology for drug substance manufacturing
New webinar: Defining the right digital strategy for oncology: What do you want to measure?
Join now: Pharmaceutical continuous manufacturing: what’s next for industry?
Register now for our upcoming webinar: Enhancing oral drug delivery: Exploring multiparticulate systems
Download our latest in-depth focus to read articles on single temperature incubation, endotoxin standards and aseptic connections in pharma manufacturing.
Discover more in our new application note: validating recombinant cascade reagents in 3 simple steps
Register now: Simplifying complex dosage forms with advanced encapsulation
Join our webinar: Unmasking the unknown: how mass spectrometry delivers accurate identifications
podcasts

EPR Podcast 25 – FAIR Data in Pharma – Giovanni Nisato, Pistoia Alliance

In this podcast, Giovanni Nisato, Project Manager at the Pistoia Alliance discusses data integrity and the progress towards implementation of FAIR data principles in the pharmaceutical industry.

Podcast graphic - FAIR data

Podcast: Play in new window | Download

In this podcast, Giovanni Nisato, project manager at the Pistoia Alliance discusses data integrity and the FAIR data principles. In this role, he coordinates FAIR Community of Experts, which created the FAIR Maturity Matrix.

Giovanni starts the conversation by defining data integrity and explaining why it is ‘mission critical’ for the pharmaceutical industry. 

Next, the podcast introduces FAIR (Findable, Accessible, Interoperable, Reusable) data principles and explores how their adoption have evolved over the past decade.

“This year we celebrated the 10-year anniversary of the first workshop where those FAIR data principles were reformulated. And they were then published in 2016,” Giovanni says.

Since then, the pharmaceutical industry has seen a “move towards data centricity as a way of thinking.” But adoption of the FAIR data principles is not mainstream yet. 

Adoption of FAIR data principles

Additionally, while the principles are increasingly recognised in academia and R&D, their implementation in the clinical domain is lagging behind.

While the principles are increasingly recognised in academia and R&D, their implementation in the clinical domain is lagging behind”

“I would say that the implementation of FAIR data principles is perhaps starting, but there’s a lot of room for improvement in the clinical space,” Giovanni reflects.

This is one area the Alliance has focused on, producing the FAIR4Clin guide that gives a comprehensive overview on FAIR resources in the clinical domain.

Giovanni also explains the FAIR Maturity Matrix, a framework developed to help organisations benchmark and assess their systemic level of FAIR maturity. The FAIR Maturity Matrix was co-created by members of the FAIR Community of Experts of the Pistoia Alliance. Giovanni presents seven key dimensions that make up the matrix: data, leadership, strategy, roles, processes, knowledge, and tools. He also introduces the six maturity levels of the framework.

Finally, Giovanni looks ahead, outlining two priorities that are needed to accelerate adoption of FAIR data principles in the industry.

About the speaker

Interviewee headshotGiovanni Nisato is an expert in collaborative innovation management across organisations at the international level. He has over 20 years of experience in the industrial and public-private deep tech sectors. As a Project Manager with the Pistoia Alliance, he has facilitated the FAIR Community of Experts since 2022. Its aim is to co-create and maintain pre-competitive resources to foster the implementation of FAIR data principles in the life sciences ecosystem for the benefit of pharmaceutical companies, CROs, technology providers, and ultimately, patients.