Fostering closer collaboration between manufacturing & regulatory functions

But change they must. Currently, only 14% of companies have connected RIM and enterprise resource planning (ERP) systems, according to Gens & Associates’ findings. This means most information gathering and verification is being conducted manually, creating a huge data management burden, not to mention considerable scope for business risk. 

When information that exists across RIM and ERP systems is inconsistent, and the respective systems aren’t set up to communicate with one another, this can create complexity and vulnerability - from compliance challenges to losses of sales based on a failure to get products to market in a timely fashion. 

If information about a change control process doesn’t flow between regulatory and manufacturing, meanwhile, it can cause hold-ups in international markets. As PLG’s Catherine Gambert cautioned, “When a product gets stuck at the border because the information printed on the box isn’t the same as that in the regulatory documents, it becomes a serious issue – and this can arise because the supply chain doesn’t have access to the information in the RIM system.”

It isn’t just the pharmaceutical sector that is facing practical issues because of faltering data exchange and poor visibility. The medical device sector shares many of the same challenges, and these will prove increasingly critical as regulators impose stricter regulations around device traceability. 

But effective data exchange isn’t just a compliance challenge in this sector either. As the digital health movement gathers momentum, the importance of having robust data trails will only grow. “Data integrity will be a major challenge—especially when it comes to connected medical devices involving remote measurements of physiological functions,” PLG’s Loetitia Jabri explained.

One of the growing issues for all life sciences organisations is the speed and frequency with which data can change and need to be updated across all departments and systems. Fragmented data chains and system silos create points of risk.

“The objective is to make sure we all use the same source of data,” Jesper Kihl of LEO Pharma said. “We recognise the potential benefit of having more integration.” Over the last year, LEO Pharma has updated its labelling practices, for instance, so that there is more end-to-end visibility and a seamless data flow. Having seen the positive impact this can have, the company is now looking at how to apply the same treatment to other parts of the business.

Lundbeck’s Jan Vindberg-Larsen noted that his regulatory affairs organisation has developed an effective infrastructure for collaborating more readily with production, allowing the two parties to share information more effectively. An SAP system is used for assessing all changes to products, including business cases; these are evaluated by commercial, regulatory and production teams before implementation. 

The ability to work from the same data is also prompting broader collaboration. “We’ve also established a product committee for our marketed products,” he said. “The committee governs any major cross-functional activities and ensures alignment between regulatory affairs, production, and commercial operations on goals and priorities.”

It helps that modern software systems are now being built to be more open, in support of easier data exchange and process traceability.

Kelly Hnat of K2 Consulting noted that today’s RIM systems are very good at tracking changes to each change to a set of registered particulars about a product, the associated variation’s filing, and the approval status of that particular variation filing. “So you can see all of the changes to each registered data point in a RIM system if it’s managed properly,” she explained.

In the Gens 2018 survey, two-thirds of respondents said their companies expected to start to automate the regulatory-clinical connection over the next two years, while just over half said they would start to connect and automate regulatory supply release and product change control processes.

Connecting disparate systems isn’t always straightforward, however, especially if those respective systems have their own descriptors for products. Not having a common vocabulary means it’s hard to identify data elements in one system and connect them to elements in the other.

It’s here that the prospect of master data management – building and maintaining a single, definitive version of the product truth – offers to transform things. As Steve Gens noted, “One of the initiatives for the connection of information is the standardisation of terminology, so that once systems are connected they can share information seamlessly. Typically, that’s the most difficult job—the handling of terminology—rather than the connection of systems.”

“It’s not just about the differences in controlled vocabularies, but also about how data is stored, what it’s stored for, when it changes, and how it changes,” Kelly Hnat added. “Regulatory and quality teams use their systems for different purposes, and they’re tracking information at different points in the process. One of the things companies have to be cautious about when implementing master data management is not only the importance of finding out who owns the data but also the purpose of the data, when it was updated, etc.

"Although data captured for IDMP regulatory purposes focuses on what’s registered, it doesn’t necessarily cater for what the manufacturing site is doing,” she noted. So master data approaches need to extend beyond specific use cases.

PLG’s Erick Gaussens suggested that an effective approach to keeping all of the fuller data sources and supporting documents aligned can be to layer the RIM system on top of the ERP system, maintaining control of the metadata.

Whatever the broader opportunities, it is typically the intensifying regulatory demands that continue to drive improvements and free up the necessary budget. Companies are aware that initiatives such as IDMP and the Falsified Medicines Directive mean data must become more integrated, so functions have become more willing to spend time and resources on building bridges and establishing interfaces.

But it’s those organisations that have also identified the wider business benefits of more streamlined data management that have seen the greatest scope to modernise and innovate. At LEO Pharma, Jesper Kihl, explained how his team has used IDMP to highlight the broader potential for greater efficiencies and closer connection between functions. He hopes that IDMP implementation timelines will be brought back on track by regulators soon, when a higher sense of urgency will help drive through the benefits.

When a company treats data as a corporate asset and maintains it in the form of definitive master data, the whole organisation stands to benefit from an environment in which data can be trusted as being a high-quality record of the latest truth, the panel agreed. In the long run, this makes everyone’s life easier, makes processes slicker, and drives out cost and risk, while supporting greater market agility. Given that these are benefits that all organisations are striving to deliver, the case for fundamental transformation of data management, and approaches to data-based collaboration, is pretty convincing.