IDMP: Back on Track and Bearing Down with New Urgency—What’s Next?

By Siniša Belina
July 17, 2019


• Categories: 03-Manufacturing Execution, 05-Quality/Regulatory, Business Analysis, Combination Products, Market Access

For those life sciences firms that have put preparation for ISO IDMP (the global standard for Identification of Medicinal Products) on hold over the last one to two years, it is now time for action. At last, the definitive implementation guidelines are being finalized and deadlines are being set, which means that the countdown to compliance has begun in earnest. Next stages should go beyond developing a vision and roadmap for delivering compliant submissions (as required by the European Medicines Agency from 2021); these should be in place already. Rather, companies should now be finessing their practical plans and determining how they will maximize their return on investment.

Some larger multinationals have already made some progress here. Those organizations that continued to evolve their IDMP plans despite shifting timelines now have proof-of-concept projects to build on, which others have a chance to learn from. In the most advanced scenarios, firms are looking to the high-quality master data sets they are working towards as the basis for process automation—for pre-filling regulatory submissions, for instance—with the potential for substantial efficiency gains, cost containment and risk reduction benefits.

Indeed, the real trailblazers have taken advantage of prior delays with IDMP’s rollout to map out wider internal applications, rather than treating “compliance” as their sole aim. But in most cases, even these companies have not yet started to practically realize these ideas, or to prepare and organize their master data. They may have formulated an optimum approach to data management, and identified stakeholders and teams who will own and deliver this, but the extensive groundwork that will be needed to locate all of the data, assess its completeness and quality, and establish mechanisms to fill in any gaps, is all still to do.

Smaller organizations, meanwhile, have tended to take a more reactive approach—focusing on other priorities until much nearer to the go-live date. Although this wait-and-see attitude isn’t recommended, these companies 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—before that—eCTD.

The Value in Thinking Laterally

The encouraging signs are that the messages about investing time and effort in establishing robust master data seem to have been heeded. Most organizations that have put serious thought into IDMP preparations are now planning to maximize the data assets they must now build, by making sure they will be compiled in a readily reusable form. Certainly this is the approach being taken by major pharma brands. It is a wise path for generic drug manufacturers too, given that efficient, failsafe compliance is critical to their continued standing in the market.

The availability of formal implementation guidelines will finally give the industry something tangible to work with, beyond the IDMP data standards that have been drip-fed to the market in recent years under different category headings.
But, as approaches to implementation begin to crystalize, it is not advisable to wait for or expect that all of this can be covered with a targeted IDMP software solution: a panacea that will efficiently take care of all compliance activities for a company.

Those companies that decide to go out and look for a dedicated IDMP data submission tool continue to miss the point. For all the preparatory work that IDMP demands, its great benefit for companies is the data rigor and discipline it imposes. This should spur companies to transform their existing internal data tracking and document preparation processes—from the way they prepare marketing authorization submissions and updates, to the way they create, verify and manage labels and patient information leaflets internationally—with the result that they will be able to run and manage their operations in much more efficient and effective ways in future. If they take shortcuts —by trying to apply single-purpose solutions with the sole aim of complying with EMA requirements—firms will simply be generating new data silos that add no value for the business.

Harnessing the broader intentions of IDMP—greater data quality, instant traceability, and so on—offers life sciences organizations so much more than regulatory conformance. Additionally, it provides the basis for improved end-to-end visibility across products and their lifecycle, transformation of global labeling and management of translations, and so much more.

The Stronger the Foundations, the Greater the Potential

In advanced master data management scenarios, which we have dubbed MDM 2.0, companies are able to turn definitive, centralized product information into tangible business value by transforming the way teams create important, routine documents. It is not unthinkable to expect 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 center 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 that 100% of document compilation and preparation, in any designated language, could be automated.

Automated Document Assembly & AI-Enabled Analytics

Once firms have established rich, reliable master data resources, they have a chance to enhance them further with value-added, contextual information (about country-specific requirements, or a product’s global status across its lifecycle) that 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.

So it pays to think about product profiles and data sets in the broadest possible 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 do opt to take this extended approach to their product data management efforts could benefit from faster and more automated CMC document creation (i.e., 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.

A further benefit for companies that put in the groundwork now is that they will have a head start when other geographical regions start to mandate IDMP-based requirements too, with the United States being expected to follow Europe before long. Certainly, more holistic data reporting and real-time product transparency is the way global market requirements are heading.

But every major journey begins with a first step, and for now that is to get hold of the first pass of the EMA implementation guidelines— so that companies can move forward in the right direction, knowing which data to focus on first, what format to follow, and how to structure their data.

Certainly, IDMP has had many false starts—but momentum is building and the sooner firms give shape to their plans, the greater their opportunities to optimize their ROI.