Taking label management beyond the superficial

For some life sciences firms, product labelling is treated as a distinct, manually-driven process. This is a major error and can leave them vulnerable to risk, such as costly product recalls, and inefficiency. To reduce this risk, associated processes need to be systematically managed, using automation - so that the latest compliant wording, symbols and other criteria are used consistently and reliably, and that checks and controls aren’t reliant on human proofing alone.

While many organisations still rely too much on manual processes, intensifying regulatory requirements and the evolution towards IDMP means that they are looking again at their processes and systems for managing content. The most effective way to do so is via a centralised (or virtualised) ‘master data’ approach, meaning those responsible for labelling and related content preparation, have a definitive database of approved assets to work from.

In the context of labelling management, the goal should be to enable systematic, structured content altering as regulatory requirements are updated in given markets, or as products evolve over time. If this can happen as an integral part of next-generation regulatory information management, the associated IT/process payback will be greater.

Regulatory information management (RIM) should be about more than straightforward registration planning and tracking. At its most effective, RIM should be a holistic enterprise that takes in dossier management, submission planning and tracking as well as manufacturing, change control, safety reporting, master data management, and labelling and document management.

If these activities take place in silos, each served by standalone systems and processes, companies risk reinventing the wheel many times over, and introducing inconsistencies and errors with each new content preparation task. Without master data management, cost, risk and inefficiency remain and in the context of labelling, companies’ exposure could be significant.

So ideally any master data management initiative should start with a product master data object model, of which regulatory intelligence is a part. The regulatory factors may not fit generic system data fields, being the proprietary IP of each company. But if it the information is structured, it can still be reflected in the main product information system, contributing to that holistic, 360-degree resource which caters for all information needs.

Combining product master data with regulatory intelligence makes it possible to automate more processes – including labelling management - and the need for heavy manual work is reduced each time there is a new content-related requirement.

Taking a master data/complete product profile approach means all of the correct content for accurate, compliant labelling can be called up quickly and easily for the given use. In addition to ingredients and manufacture information, it should be possible to call up detail for all authorised medicinal products alongside all the respective countries’ procedures, health authority organisation information and marketing authorisation programmes and processes. Labelling processes, change requests, sequences and templates should all be possible to manage in a clear and structured way.

Proper provision for labelling, to reduce risk and improve efficiency, should include the ability to select approved content elements as self-contained label ‘objects’ or assets. These might include the name of a medicinal product or its clinical particulars, pharmaceutical particulars or pharmaceutical form.

By seeing the bigger picture around labelling and data management, life sciences firms open themselves to a range of new possibilities – to reduce complexity, cost and risk, while improving productivity, accuracy and speed.

Romuald Braun Vice President Strategy, Life Sciences, AMPLEXOR