Data in life sciences is more than a mere byproduct of research; it is a driving force behind innovation. By harnessing extensive datasets, organisations can speed up drug discovery, refine precision medicine, and improve operational efficiency. This shift has transformed data management into an essential cornerstone rather than just a technical tool. Although artificial intelligence (AI) continues to captivate the industry, the true cornerstone of successful digital initiatives lies in mastering data control.

Yet, without proper oversight, the risks are substantial. For instance, the EU’s AI Act imposes severe penalties on life sciences companies deploying non-compliant systems. In this context, data is no longer merely a resource but a core strategic asset requiring active protection and management.

The Growing Data Opportunity

The scale of data in life sciences is staggering. Pharmaceutical firms partner with thousands of study sites and tens of thousands of trial participants. A study by Tufts University found that Phase III clinical trials now generate an average of 3.6 million data points, tripling the volume collected a decade earlier. Amid this deluge of information, ensuring timely access to the right data is crucial to optimise R&D efforts, while reducing the time spent on data preparation and management.