The great debate

April 23, 2019
The benefits of improving data connections along the manufacturing-regulatory continuum

When life sciences organizations are able to share good-quality data between different teams and functions, the benefits are multiple — and potentially substantial. Greater collaboration means fewer people needlessly reinventing the wheel by re-entering data for each respective use case; fewer errors or issues slipping through the net; and a more efficient and productive use of valuable resources.

Conversely, as long as data is entered in different ways into different systems, in departmental silos, as is so often the case, the scope for improving productivity and efficiency and delivering strategic business benefits will be limited.

There are numerous practical reasons why this protracted, disjointed situation has evolved. Processes for information recording started out very manually, and each function had its own use case and priorities, which it reflected in its individual system requests and resulting IT projects.

New research published by Gens & Associates in late 2018, confirmed that the vast majority of organizations still struggle with “disconnected” information, with most companies using systems from as many as four or five different software providers (for publishing, document management, registration, labeling, submission planning and so on). These diverse systems tend not to be connected (except for submission document management and publishing).

Many companies are operating inefficiently due to this disjointed systems and data environment, the Gens & Associate report notes. It is one of the reasons why as many as three-quarters of the surveyed companies are now looking to investigate and potentially adopt an end-to-end regulatory information management (RIM) platform strategy, with the highest interest coming from mid-tier life sciences organizations where business scalability is a priority.

Digitization drivers

Certainly, as more of everything becomes digitally enabled and managed — even regulators’ own activities as well as information exchange with other parties along the supply chain — it no longer makes sense for companies to keep investing in multiple different systems, each with their own peculiarities and IT support burden. Fragmented systems, processes and data sources prevent organizations from being agile, creative and responsive. They prevent a clear line of sight across the company’s operations and products, which in turn limits strategic and timely decision-making. They incur a lot of cost, too, because each system needs to be maintained, updated and supported. Perhaps most cumbersome of all though is the inefficient way that data is used across and between different teams. It is hardly conducive to fluid, inter-departmental collaboration to keep valuable data locked behind individual functional lines.

Nowhere is this limitation more frustrating currently than along the manufacturing-regulatory continuum, where the fluid flow of accurate and current data is essential to get products to market reliably, efficiently and cost-effectively — and to keep them there, through correctly maintained licenses. In an ideal world, the latest, high-quality data would be available to both ERP and regulatory information systems, so that all teams are working from the same page.

But what are the options for making data more available to complementary business functions, when there are legacy investments everywhere? And what is involved in a master data management approach?

Prioritizing better connections

The imperative to improve data connections and information exchange, and how best to achieve this, was the subject of a recent roundtable debate among experienced industry experts.

Noting that product and regulatory information has an ever greater role to play in the efficiency and strategic direction of life sciences businesses, beyond immediate administrative obligations, the panel considered how companies could make more of this — and what needed to change to make this practical.

Steve Gens, managing partner, Gens & Associates, noted that, in his firm’s 2018 research into companies’ RIM activities and plans, the improvement of data management and connections to other functional areas is now a major priority for life sciences firms of all sizes. Yet, although some firms are making good progress, others remain held back by the scale of change to processes and systems that are involved — and the senior organization input that will be needed to effect a shift towards more routine collaborative working.

But change they must. Currently, only 14 percent 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, it can cause hold-ups in international markets. As ProductLife Group’s (PLG) 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.”

Keeping ahead of change

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 organizations is the speed and frequency with which data changes and needs to be updated across 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,” said Jesper Kihl, vice president for global regulatory affairs at LEO Pharma. “We recognize the potential benefit of having more integration.” Over the last year, LEO Pharma has updated its labeling 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.

Jan Vindberg-Larsen, senior director and head of global regulatory affairs at Lundbeck, noted that his regulatory affairs organization 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, principal at K2 Consulting, highlighted 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.”

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 would start to connect and automate regulatory supply release and product change control processes.

The role of master data management

Connecting disparate systems isn’t always straightforward, however, especially if those respective systems have their own product descriptors. 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 Gens noted, “One of the initiatives for the connection of information is the standardization 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,” 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.

Erick Gaussens, PhD, chief scientific officer at ProductLife Group, 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 organizations that have also identified the wider business benefits of more streamlined data management that have seen the greatest scope to modernize and innovate. At LEO Pharma, the team has used IDMP to highlight the broader potential for greater efficiencies and closer connection between functions. The team 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.

The panel agreed that, when a company treats data as a corporate asset and maintains it in the form of definitive master data, the whole organization benefits from an environment in which data can be trusted as being a high-quality record of the latest truth.

In the long run, this makes everyone’s life easier, makes processes slicker, and drives out cost and risk, while supporting greater market agility. And that’s a state organizations in every industry are now striving to achieve.

About the Author

Catherine Gambert Senior Consultant | Regulatory Affairs and Regulatory Information