By Frits Stulp, Iperion – a Deloitte business; and Aida Demneri, Deloitte
As became only too clear at the peak of the pandemic, the time to get a product approved and to market is too long and protracted in the EU. Although extraordinary measures were taken over the last two years so that vaccines and critical medicines could be brought safely to market at greater speed, this was achieved largely by extending the working hours of assessors. Now that market expectations have been raised, there is a new sense of urgency for the EC and EMA around transforming approval processes more permanently and sustainably.
The need for lasting transformation isn’t just about approving new products more swiftly. The pandemic also highlighted entire populations’ vulnerability to breaks in supply chains and shortages of critical medicines, and indeed medical devices, and the need to be able to track and manage inventories and stock movement across multiple geographies in ever more agile ways.
The answer to all of these real-world challenges lies in greater data centricity supported by the adoption of new technologies, and life sciences companies must play their own part in driving change. But this requires the right mind-set and that conversations are happening and plans are being enacted at the right levels.
At a clinical level, data-driven practices tend to be more advanced, but the challenge now is to standardise more of the data that’s in play (e.g., referential data), and to allow it to flow more freely and be used more interchangeably between functions and use cases.
In a regulatory context, there is considerable scope for improvement. Up to now, progress here has been held back by a lag in confirming precisely what regulators will require as their own processes evolve. It’s easy to become caught up in the finer details of what EMA is or isn’t mandating at any given time, for instance.
Keeping The Bigger Goals In Sight
The whole point of making data rather than static documents the future of regulatory information management (and beyond) is to transform what can be done with that data, over time and in all kinds of use cases. It also paves the way for information to be shared in different formats as use cases dictate, while still ensuring the consistency of the data. (In the case of electronic patient information (ePI), the data could drive the population of HCP-/patient-friendly information through channels other than a paper insert.)
The trouble with each function continuing to own and look after only its own data is that there will always be disharmony and overlap between the information and the way it is recorded and formatted between respective systems and teams. As well as the doubling-up of effort, this creates the risk that the overall product “story” has breaks or inconsistencies in it or is difficult to piece together. This has implications for compliance and patient safety, as well as for operational and commercial efficiency. (Ultimately, a life sciences company’s asset is its intellectual property, which needs to be strongly reflected in its product information.)
In the bigger picture – the vision WHO and its supporters have set out – standardized data sets that can be understood by any stakeholder and any system across the international ecosystem transform product traceability and transparency. They inspire confidence in all users that the information in front of them is the latest approved truth about a product and its status at any given time.
The Global IDMP Working Group (GIDWG) – whose members include representatives from WHO, EMA, and FDA – is advocating increasingly loudly for patients, ensuring that they see the benefits of international activity. It is proposing a global algorithm-based identifier for every product, as well as global pharmacovigilance traceability. WHO, as a neutral party, would coordinate such a platform, one that physicians, pharmacists, and patients around the world could trust.
Data Prioritization Is Catching On
Development of internationally agreed standards to underpin data-driven processes elsewhere in the product life cycle is on the cards, too. At the recent DIA 2022 event (strapline: Innovation through Collaboration), discussions pointed to shared plans by EMA, FDA, and Japan’s PMDA to promote standardized data for CMC content, something akin to a global take on PQ/CMC. This would pave the way for one part of regulatory dossiers to be created and managed more dynamically, and for more than one region. This would make lighter work of variations management, as just one potential use case.
It’s this kind of expanded vision for data use the major pharma companies are working toward today. Even if regulators haven’t quite got their ducks in a row yet, they know full well that this is the scenario that everything is pointing toward. So, to prepare for anything less would be unwise.
And actually, adoption of data standardization is already filtering down to a national authority level in some cases. In Europe, some National Competent Authorities have hinted at plans to change their primary system for dossier review to something that’s “data ready.” They see the potential for more efficient assessments if elements of the workflow can be automated – such as checks for information consistency, marketing authorization holder (MAH) follow-up, and, perhaps most importantly, to have one version of product truth across the MAH and all involved regulators.
From Functional Silos To An Enterprise Data Layer
Maximizing the future potential is about creating a product data capability that transcends individual operational functions, teams, and use cases. Ideally, it means creating a non-proprietary, cross-organization data layer that receives enterprise-level funding because this master data core will underpin the entire company. Like DNA, it will contain the details of its material makeup, the very essence of the business. With one transcendent, definitive, and standardized data layer to enrich and maintain, companies can focus their investment in data quality where it counts, while individual functional systems can call in and work with the aspects of that data that are relevant to their respective activities.
Another example of the difference this will make will be as the various authorities strive for greater harmony in their treatment of medicines and medical devices and as companies are required to provide consistent data across both portfolios. (The harmonization of drug and device data management makes sense for all sorts of reasons, not the least of which is the rise of combination products, which straddle the categories of both pharma and device. EMA is already actively looking at adding device fields to its data specifications in recognition of this.)
Waiting For ”Final Clarity” On Local Requirements Is Futile
To maximize the value of today’s data investments over the long term, it follows that life sciences companies should adhere to the core standards being set out by regulators, e.g., under ISO IDMP. But waiting for the day that individual variations of this have been finalized makes no sense, as this is a continuously evolving environment. Future-proofing, then, should involve adhering to the agreed core and tweaking as needed, following an agile approach to adding functions or amending features. And of course, one of the advantages of creating a master data layer is that each set of adaptations, when they are needed, will only need to be made once, at the source.
The work that needs to happen now continues to be around data surveying, assessment, standardization, and enrichment. In time, the growing reliance on data – internally to the business, and externally in exchanges with regulators, supply chain partners, healthcare providers, and ultimately patients – will pave the way for process transformation. This will include growing degrees of automation (e.g., through structured authoring of routine documents, whereby current approved data is combined to create narratives on the fly – even entire dynamic dossiers – with minimal manual intervention).
It helps to approach all of this with the end goal in mind, which is about patient benefits, enabled by faster approvals, more accurate and timely medicines monitoring, and more – all enabled by harmonized, consistent, and reliable data, from the lab to real-world evidence once products are out in the market. Whatever the particulars of formal data-based initiatives around the world, this must be the strategic goal and all plans must contribute toward it.
Ultimately, the ability to harness data to its fullest potential will allow life sciences companies to transform not only their own operations but also their role within the Future of Health. That could be through a keener focus on unmet medical needs or by reducing the negative impact of ingredients and manufacturing processes on the planet.
The full range of opportunities is vast.
About The Authors:
Frits Stulp is managing director of Iperion, a Deloitte company, where he leads a team of regulatory/IDMP experts to deliver value to both pharma companies as well as regulators. With more than two decades of industry and consultancy experience, Stulp is regarded internationally as a subject matter expert on IDMP and he proactively shares his insights wherever he can. Stulp is also involved with the not-for-profit organization Call To Action Delivering Health Literacy (CTADHL) as part of his efforts to support transatlantic data harmonization based on IDMP. You can reach him at firstname.lastname@example.org.
Aida Demneri is a partner in Deloitte’s Risk Advisory practice based in the Netherlands. She leads the European and the Netherlands’ Life Sciences and Health (including MedTech) Risk Advisory and Regulatory practice. She has more than 20 years of experience in risk management, regulatory affairs, and compliance. With her team, she works to help clients overcome challenges in their journey toward a responsible Future of Health. Specific topics include regulatory excellence and transformation, extended enterprise risk management, cybersecurity/data, and IT quality. You can reach her at email@example.com.