The upcoming introduction of the Identification of Medicinal Products (IDMP) regulation across Europe poses a serious challenge to the pharmaceutical industry.
Under the new regulation, pharmaceutical companies will be required to standardise the way they record, store and share key information on their products. Data management for everything from ingredients and manufacturer to dosage and branding will need to be unified, with the aim of enabling smoother information sharing and collaboration across borders in the industry.
However, for many companies, achieving this goal will be a challenging process. Many pharmaceuticals simply aren’t prepared to bring their data into line in such a comprehensive manner.
Compliance with IDMP will require organisations to get a deep, 360-degree view into their data, wherever it resides -in the cloud or on-premise.
At present, different organisations use a variety of vocabularies to refer to medicine variables including dosage form, route of administration and units of measurement. Substances themselves are also often classified under different names across different manufacturers, and brand names frequently change across nationalities.
For example, paracetamol is also known by the generic name acetaminophen, and is marketed as both Tylenol and Panadol in the USA.
Although the equivalence is often tacitly understood by industry professionals, this discrepancy leads to unnecessary fragmentation in data banks, making it harder to find and classify multiple medicines of the same variety.
This inconsistency only complicates data management processes, limiting the ability to rapidly identify trends across medicinal brands and clouding the view of the supply chain, making it harder to identify shortages and counterfeit medicines.
Many organisations also currently operate a manual data-entry system, wasting a great deal of administration time. Not only must each company enter and store the relevant data points for its medicines in its own system, but it must also then re-enter that data in line with the format of all other organisations or agencies with which it does business.
Industry data is broadly speaking difficult to read and hard to rely on, with duplications, mislabeling and failures in production standards becoming increasingly hard to spot and address. This leads to a risk of decision-making based on inaccurate information.
What’s more, the manual processes required to manage such vast amounts of information lead to slower decision-making and a more sluggish industry, with more hurdles to clear before new medicines are made available.
Clearly this state of affairs demands that pharmaceutical organisations take control of their data, especially if they are to gain a clear picture of all the information linked to their products and organise and store it in line with IDMP.
Before standardisation can be achieved, it’s essential that companies adopt a strong data management strategy in order to provide complete and reliable data.IDMP data is highly fragmented by internal process – causing duplications, contradictions and ambiguous meanings.
A focus on improving data quality so that it is fit for submission will be a key component of any IDMP data management strategy.
To do this, they must be able to identify their master data – information which plays a key role in the basic functioning of the company.