Smart IDMP: future-proofing the process

The EMA’s IDMP will become mandatory in February 2023. It may be the first digital requirement for life sciences, but where it leads, others will follow. Rather than thinking of it as a threat, companies should see it as an opportunity to do things in a smarter and more co-ordinated way,

The FDA in the US fosters similar goals linked specifically to labelling and CMC information management in pharma, with plans to extend its implementation of the ISO data standards to other areas, while other regulators worldwide are also looking at something similar.

What all these emerging standards have in common is support for new digitally enabled process efficiencies and for greater transparency and accessibility of product information.

It would be a mistake for life sciences companies to invest in each set of regulatory requirements individually. This would risk incurring great expense – not to mention investment of time and resources – only to create another system silo, a scenario that is at odds with the data-driven movement.

The smart money will be spent on preparing not just for a given set of external requirements, but for a data-driven future.

Tighter Synchronisation

Typically, companies still approach regulatory applications and reporting sequentially – documents are built from scratch each time, through a painstaking process involving each department gathering its information before throwing it over to the next team to add their contribution.

EMA’s target operating model for IDMP challenges this process head on. It requires that the originating data behind each dossier is submitted/made available at the same time, requiring much tighter synchronisation and alignment of document/data management activity.

Scope and Flexibility

Although it is tempting to wait until all the details of a particular regulatory mandate are finalised, it’s better for life sciences companies to regard the principles and templates from EMA’s implementation of IDMP and other regulatory initiatives as just helpful blueprints. Internal data models should be kept independent from regulator-specific parameters. Ideally, a company’s own data model will be built with the scope and flexibility to address a broad range of requirements through simple configuration. The key is that this new, improved organisation-wide capability will support the maintenance of up-to-date, high-quality data right across the product lifecycle.

Up-front Preparation

The smart approach is to prioritise up-front preparation, so that the company invests once and well for all future eventualities. Instead of looking for a single, mandate-specific system that delivers what’s needed for one region’s latest requirements, it focuses on creating a comprehensive internal capability that captures and maintains everything in a standard way for the global organisation. This master data and any linked, approved content can then be repurposed/reconfigured in any number of different ways for each new set of needs.

Six Steps for Sustainable RIM

There is still time to build a future-proof data-driven regulatory information management (RIM) capability, if companies start now. The better the preparation, the more sustainable, reusable and valuable the resulting platform will be.

This is how we recommend building such a capability:

1. Start with an understanding of the benefits of a ‘Smart IDMP’ approach, or multi-purpose platform/capability, and an appreciation/acceptance that this will require more investment and planning now than a single-purpose compliance system.
2. Establish a baseline. Identify the relevant data the company has, any gaps, and the steps and processes that will be needed to improve and maintain it – collaboratively and in the context of the desired data model. This should be thought of both from an internal perspective, and in the context of evolving regulator expectations.
3. Put a project in place, defining roles and responsibilities, and securing support from senior management to drive any necessary transformation to business processes, and even the organisational structure, to allow the new data-driven vision for RIM – and more – to be realised.
4. Implement the desired data model, accommodating the requirements of IDMP and any other relevant regulatory demands, along with the supporting tools or platform to enable these to be combined with associated processes. Consider scope for extending this capability to encompass functions beyond the Regulatory remit – such as Quality/Safety/PV and labelling management. A configurable platform will ideally support a wide range of use cases, based on the same core data set.
5. Establish appropriate data governance, reflecting interdependencies between roles and teams across the value chain, so that the quality of data can be built across departments. This may require change management to support a revised/optimised organisational structure.
6. Go live, ensuring that a data governance and associated process body is in place to maintain this valuable utility in a sustainable way, supporting continuous improvement to data quality and to processes.

If your company wants to avoid compromising its vision, the time to make the change is now.