Current Edition

In-flight Data Control

How to Approach the Next Frontier in Transforming Life Sciences Business Process Efficiency.

The trouble with non-standardised data, from an internal company perspective, is that it hampers agility and the ability to innovate. If each department uses slightly different terminology for a product and has its own system and way of logging information, the scope for coordinating associated insights, identifying opportunities, and accelerating processes will be compromised.

As agility becomes a focus for the European Medicines Agency, and pharma companies comprehend more fully the benefits of a continuous, reliable, harmonised data flow across their operations, the focus is turning to ‘in-flight’ data control. This is about ensuring that information captured and used in one function or part of an extended process can be matched and reconciled with related information elsewhere. The idea is to create a rich, combined and current narrative that all functions can access and add to, to support a range of use cases.

Here, Max Kelleher, Chief Operating Officer at Generis and Remco Munnik, a Director at Iperion, a Deloitte business, offer practical tips on how companies can systematically control and harness the flow of data between functional silos, and the potential benefits this could have.

At the recent DIA Europe event in Switzerland, conversations abounded about how to leverage live company master data more effectively and strategically across the Life Sciences R&D lifecycle. Rather than focusing solely on the information logged formally (and often in duplicate or worse) in separate departmental systems, this is about the flow of broader data and insights between functions, potentially serving a range of different use cases. Much of this ‘in-flight’ data is incidental information captured as part of a task, yet its value in providing oversight, traceability and impact assessment to senior management could be considerable – if only companies could find a way to harness and control it more systematically.

Today, ‘point’ software solutions – regulatory systems (RIMS), clinical trial management (CTMS), pharmacovigilance (PV), or whatever – have become commodities, whose value is largely restricted to the immediate use case. And it is in the handover of the data between these departments that gaps and discrepancies in information between systems occur, leading to operational blind spots and strategic oversights at best, or regulatory incompliance at worst. This makes hard work of change management and could mean that product development information, and indeed patient safety events, aren’t fully traceable. Overcoming the silos, interconnecting the data, and keeping those connections dynamic and smart, is the next big opportunity – and provide the key to using everyday operational data to drive business improvements.