Preparations for ISO IDMP (the global standard for Identification of Medicinal Products) may have faltered over the last couple of years, but the European Medicines Agency has returned its focus to the standards now and life sciences firms must do the same if they want to avoid being caught out. Currently, implementation guidelines are being finalised and deadlines are being firmed up, indicating that the countdown to compliance has begun in earnest.
This in turn demands that companies move beyond simply having a vision and roadmap for delivering compliant submissions (required from 2021 in Europe), and start delivering against tangible plans. Many larger multinationals now have proof-of-concept projects to build on, which others can learn from. Some are even looking to the high-quality master data sets they are building as the basis for process automation - for pre-filling regulatory submissions, for instance – with the potential for considerable efficiency gains and cost and risk containment. But even though they may have established their chosen approach to data management, and stakeholders and teams to deliver it, they still have a lot of work to do - to locate and vet all of the data, and determine how to fill any gaps.
Less substantial organisations, meanwhile, have tended to hang back, waiting to see what others do – reluctant to make an investment until there is real momentum behind IDMP. These firms could gain some advantage now – borrowing the conclusions of those who’ve considered IDMP compliance considerations from all angles, added to learnings from earlier experiences with IDMP’s predecessors, xEVMPD and eCTD.
Those organisations that have put serious thought into IDMP preparations are now planning to maximise the data assets they must now compile. This is not about buying a dedicated IDMP data submission tool – which ultimately would lead to yet another data silo, adding little to no new value for the business. Rather, the aim should be to transform existing data tracking and document preparation processes – for handling marketing submissions and updates, and creating and managing labels and patient information leaflets on a global scale, for instance – by first ensuring that these assets are created in or converted to a readily reusable form.
Where organisations can see past the immediacy of IDMP compliance, to the value in managing their data very differently, the end result can be radical transformation of the way that teams complete routine tasks – such as creating regulatory documents. With ready access to definitive, centralised product information, companies can begin to conceive of document authoring automation rates of 90%+, paving the way for a 10-fold acceleration in preparing regulatory submissions and patient-facing materials. All of which reduces costs, and risk of error, while substantially improving speed to market.
Creating an IDMP strategy with master data at the centre is about creating something much bigger and more broadly applicable than IDMP. It involves investing in and building an agreed, single version of product truth with the potential to inform and be repurposed ad infinitum for numerous use cases.
It is from this standpoint that companies are able to entertain plans for smarter document management, including structured authoring. Here, approved ‘fragments’ of content can be called up automatically and pulled into specific documents using smart templates, orchestrated by strict workflow rules that teams can control. In other industries, such as those involving complex engineering projects, this kind of practice happens as standard and is well proven. In repeat, routine scenarios, it is quite possible than 100% of document compilation and preparation, in any designated language, could be automated.
Richer data yields deeper insights
With rich, reliable master data resources prepared and at their disposal, life sciences firms have a chance to enhance these assets further with value-added, contextual information (about country-specific requirements, or a product’s global status across its lifecycle). This, in turn, will more directly serve internal business agendas and enable desirable process improvements. The richer the data that companies collect, the more they can do with it.
In one case, a firm reviewed data about the Tobacco Mosaic Virus that had sat dormant within data archives for more than two decades, only to later discover that with modifications to the virus it was possible to cultivate medicines from tobacco plants. This is a powerful illustration of how established data investments can continue to bear fruit long after the initial investment. The key to taking full advantage of this is ensuring that complete details are captured up front, and can be readily called up and repurposed to support multiple different use cases in future.
Initiatives such as ISO IDMP are enforcing this kind of structure on pharmaceutical data for the first time, which could be the start of a new era of unprecedented data-based insights. Add artificial intelligence and powerful, large-scale data analytics into the mix, and it becomes easier and faster to search for new patterns and discoveries that might once have been impossible to detect. Where data is confined to static documents, or stored in one-dimensional formats, it is much harder to distil new insights from it. A fully-rounded, master data approach to product information unlocks its latent potential.
Seeing beyond submissions
With a wider perspective, and as they gain experience, firms will begin to appreciate the broader value of viewing product profiles and data sets in the broadest imaginable terms. While IDMP encompasses clinical indications, and contraindications and adverse reactions, for instance, an MDM 2.0 approach to data preparations might also encompass CMC data, structuring more of this for re-use and more readily accessible insights. After all, manufacturing is where most changes happen across a product’s lifecycle, which will have a bearing on what needs to be reported, and what must be reflected in all of its labelling and patient information. So it makes sense that this fuller profile information is built into product databases, alongside clinical and patient safety data.
Companies that take an extended approach to their product data management efforts, could benefit from faster and more automated CMC document creation (eg Module 3 documents), and the ability to more efficiently and reliably assess the impact of manufacturing changes on regulatory obligations, down to a country by country level. This in turn would help with resource planning, adding further operational benefits. Meanwhile translations could be packaged for processing simultaneously, if the way is paved for documents to be auto-populated with already-approved translated blocks of content.
Finally, it worth considering that those companies which put in the groundwork now for broader data transformation will have a head start when other geographical regions start to mandate IDMP-based requirements, the US likely to follow Europe in due course.
Certainly, more holistic data reporting and real-time product transparency is the way global market requirements are heading. For now, though, companies’ priorities should be to review the early EMA implementation guidelines, and decide which data to focus on first and how to structure it, so that they can start to establish the solid foundations that will underpin all of the many possibilities.
Siniša Belina is a senior life sciences consultant within the AMPLEXOR Life Sciences Product Management team