Global product labeling as the lynchpin of Life Sciences’ data-driven future has been saved
Global product labeling as the lynchpin of Life Sciences’ data-driven future
The indisputable case for structured content authoring and management – ensuring more repeatable and reliable output with inherent traceability
By its very nature, Life Sciences product labeling is at the heart of regulated product information management, being effectively the definitive short summary of all of a drug’s current manufacturing and safety detail – covering everything from how to prescribe and administer it, to the specifics of potential adverse events and what to do about them.
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- Maintaining accuracy from the source
- The heavy burden of manual label management
- Finding a practical way forward
And yet, still today, all of this information is collated and managed in a highly piecemeal and manual way, which typically involves starting almost from scratch each time product information or safety advice is updated. That’s in terms of assembling and processing the new information, and getting it approved and correctly translated for each market. In the first year of a new drug being on the market, the number of cycles of changes can be significant as new usage-based data comes in from the real world, with implications for the safety information supplied in patient information leaflets.
It is in the context of product labeling, then, that one of the strongest business cases for a more structured and data-driven approach to content authoring and management emerges in Life Sciences – deepening the value of compliance with ISO IDMP and other emerging standards for data management and ongoing information exchange across the healthcare ecosystem.
Maintaining accuracy from the source
Not only is correct and current labeling of critical importance to a drug or medical device’s ongoing authorization/registration, and the safe and effective use of a product; it is also inherently ‘data heavy’ in its make-up.
In a multinational environment, key information from the Company Core Data Sheet must serve as a living document to capture the globally-relevant specifics, while allowing for the management of local/regional labeling, based on the Core but adjusted and translated according to local requirements. It follows then that labeling usually serves as the “source” for data submissions like XEVMPD / SPOR (in the EU), SPL (the US) or REP/XML PM (Canada).
But what if all of this could be reversed so that the data came first, and everything else flowed from it – and could be managed in a much more efficient, traceable, and repeatable way, with label change management one of the considerable business wins?
This makes more practical sense, especially in line with evolving regulatory requirements. In the EU, the majority of IDMP data elements for Iteration 1 come from the Summary of Product Characteristic (SmPC), and the expectation is that there is demonstrable consistency and continuity across the product labeling family – i.e. between the Core and local labeling, with any deviations (e.g. different forms, doses, strengths) carefully tracked.
This is where technological support, specifically in the form of structured content authoring and management software tools, presents tangible value – allowing for reliable re-use and adaptation of content, for detailed tracking, and more programmatic management of variations and data dependencies.
The heavy burden of manual label management
In the traditional set-up, label creation and change management continue to involve extensive knowledge work - from the strategic decisions made by Regulatory professionals about what to include in the Core Label and how to format it; to regional and local adaptation and translation (as well as periodic reverse translations to check for accuracy); to multiple layers of manual proof-reading (typically applying the ‘6-eye principle’ – 3 sets of eyes reviewing what the writer has produced).
While this extensive cycle may have been sustainable over previous decades, there are hard reasons why such practices can’t continue. These include new pressures on pricing in Life Sciences, as well as the growing need for agility and speed to market post pandemic. Laborious manual processes are both costly and painstakingly protracted.
The structured, data-based approach changes all of that. It aims to reduce/restrict the free-flowing narrative, replacing it with more formulaic content structures which can be assembled from pre-approved data points or content ‘fragments’ which can be flowed automatically into dynamic place-markers, via smart links.
As well as doing away with the scope for human error (e.g. associated with manually cutting and pasting information from another source), this set-up is inherently much more reliable because any changes to information can be cascaded automatically across whole groups of linked content at the touch of a button, because content (in this case, labeling) inter-dependencies have been accurately, definitively and dynamically mapped – right through from the Core labeling document to regional and national varieties.
Finding a practical way forward
There are some practical considerations to all of this, of course.
First, there will inevitably some organizational change implications, both as layers of traditional processes are reduced, and as Regulatory writers adapt to a more factual and formulaic and less narrative-based approach to content delivery – to maximize the scope for automated data/content re-use between documents and use cases.
Second, rather than attempt to adopt structured content authoring in one fell swoop across the international organization, it makes sense to start small, to keep the transition manageable and to deliver visible wins within a shorter timeframe. That might involve trying out structured content authoring to fulfil EMA’s expectations for standards-based electronic product information (ePI) delivery; or focusing on US-based labeling (which doesn’t have the same individual market and language demands of the EU’s diverse member states).
The gains for companies themselves, of adopting a more data-driven and structured approach to regulated content production and management, include readier compliance with evolving and ever-stricter Authority requirements, and greater efficiency in change management. More immediately, from a compliance perspective, adoption of structured authoring and content management promises to eliminate data/document discrepancies in IDMP data submissions.
For patients and healthcare providers, there are potentially substantial gains too as Life Sciences companies start to produce and manage their regulated information more systematically and dynamically. These include the scope for improved information accessibility (e.g., use of mobile devices, enlarged viewing for the visually impaired, and more diverse ways to disseminate information, including multimedia); more personalized information (e.g. based on the patient’s age, gender, weight, prescription etc.); and making drugs and their properties more readily searchable/comparable within a therapeutic area.
One thing is certain: today’s disconnected and highly manual label creation and management processes are unsustainable if companies are to stay on top of global regulatory expectations and remain competitive in the global market. A more streamlined, dependable, data-driven approach is really the only option manufacturers and marketing authorization holders have if they want to maximize their international opportunity while containing both cost and risk.