Beyond Research: How FAIR is Powering Pharma’s AI and Data Analytics Revolution

Over the past year, I’ve had many conversations with pharma research scientists about the real-world value of FAIR data. A common challenge with FAIR is, while it sounds great in theory, in practice, finding and re-using data often still means logging into yet another tool or navigating yet another silo. These extra steps are slowing down work and are a distraction from the flow.

But with the right integration, FAIR becomes seamless. There is a practical middle ground between the bright AI future of automated, scientifically sound suggestions and the manual grind of data entry and wrangling. We need to meet scientists where they are without disturbing the flow of their work.

At ZONTAL, we make that possible. All data points from all workflows are automatically captured and made FAIR, feeding raw data from instruments directly into analytics environment with no extra steps required. And when FAIR is done right, the benefits are visible at every level from bench scientists to an entire research business.

According to the 2024 FAIR Business Survey by the Pistoia Alliance, pharma companies that embraced FAIR early are already seeing measurable gains across research, development, and operations. The survey, which gathered insights from 36 organizations and 12 expert interviews, reveals that FAIR is the foundation for advanced data analytics and AI. Companies report faster time-to-insight, improved data quality, and enhanced decision-making capabilities.

The report highlights four key value categories where FAIR has a positive impact:

Cost saving: FAIR reduces manual efforts, avoids data duplication, and minimizes wasted time leading to leaner, more efficient operations.

Effectiveness: FAIR is unlocking new insights and increasing the success rate of R&D initiatives by making data more reusable and accessible across teams.

Speed: Faster decision-making and higher pipeline throughput are supporting innovation and accelerate time-to-market.

Trusted Data: Organizations are seeing improved data integrity and quality, which in turn enables more reliable AI capabilities.

The four pillars of FAIR’s business value: Cost saving, Effectiveness, Speed, and Trusted Data.

One of the most compelling findings is FAIR’s role in unlocking AI potential. Machine-readable data accelerates analytics and AI initiatives. This is transforming how pharma and biotech approach everything from early research to regulatory submissions.

However, the report also emphasizes that becoming FAIR is a technical and a cultural shift. Success depends on leadership support, cross-functional collaboration, and a shared understanding of the value of adopting FAIR. It encourages companies to define clear ROI from the start and engage stakeholders early, especially to secure continued investment.

At ZONTAL, we believe that FAIR is not just about better data it’s about better outcomes. A central FAIR data platform and automation are key to driving innovation and building trust in data across the value chain, all the way to the patient.

And the real power of FAIR comes to life when it is the basis for your analytics. With ZONTAL, your semantic and vendor neutral data becomes instantly available for advanced analytics, dashboards, and AI-driven insights.