There is little more irksome to senior budget-holders than when an IT and process transformation initiative is purely a cost to the business, especially when it’s driven by a need to conform to the latest demands of industry regulators. As much as financial decision-makers may buy into the bigger picture, and have patient safety at heart, they can find it galling when the direct gains for the organization from any investment appear to be minimal. And in life sciences, it would be forgivable for finance directors to resent the ever-increasing circles of spending currently required. Risk mitigation is one thing, but even the wealthiest pharma leaders do not have a bottomless budget for regulatory compliance.
Yet, what choice do they have? The call to transform regulatory information management (RIM) is growing louder with every new reporting requirement set out by international authorities. The upcoming ISO IDMP (Identification of Medicinal Products) standard set continues to command a lot of media attention, with its emphasis on data completeness and quality. It’s not the only driver of regulatory spending either. Other international regions are adapting to IDMP at their own pace or putting their own twist on the requirements, while alternative transparency initiatives exist throughout the global life sciences industry. In Europe, there is also the influence of Brexit which has created some uncertainty around the timelines of new standards. At the latest check, IDMP was due for implementation across the EU in mid-2019, though this could slip into 2020.
There is no risk of IDMP fading into the background though. The U.S., Canada, and non-EU countries like Switzerland appear keen to embrace the ISO standards because of the improved visibility and accountability they promise. The European Medicines Agency has been facilitating discussions through the International Pharmaceutical Regulators Forum, an adjunct to the International Conference on Harmonization (ICH), and set up an IDMP implementation group to foster more discussion between international regulators about the global potential of the standards.
But what approaches are organizations taking to manage critical regulated data — and what is required to ensure that companies derive some operational and strategic benefits from their investments? For pharma companies, success will depend on a taking a holistic and strategic approach to regulatory information management while also preparing for the future, as AI tools enter the scene.
Forming a Data Strategy
Given all of this continued regulatory diversity and uncertainty, life sciences organizations have decided that finding new budgets and initiating dedicated new projects each time a new regulation comes out, or is updated, is not an efficient nor effective way to go about compliance in a complex, continuously evolving global market.
While nothing moves quickly in life sciences, organizations’ plans to get their product lifecycle data management in order started to move up a gear in 2017, and momentum has been building steadily since.
At the same time, companies have now begun to grasp the strategically important role that product data could play in future — especially as a means of driving new productivity, efficiency and competitive differentiation. Success depends on making the right provisions, and finding a practical way to make regulated data work harder and deliver more across a range of use cases.
An Evolution Towards Reusable Data Assets
At a recent conference, independent industry expert Andrew Marr, who recently hung up his hat after more than 30 years in the business, emphasized the rising importance of making product and regulatory information more shareable between and beyond specific functions in the business. His perspective on companies’ evolving data strategies was particularly poignant, given that he has spent his career helping life sciences organizations improve product lifecycle visibility and keep accurate records for regulatory reporting purposes — developments that have taken place in parallel with advances in software and data management technology.
To emphasize how far things have come, Marr recalled the shift from manual paper records to rudimentary electronic regulatory submissions, preceding the evolution of relatively static, 2D documents to more dynamic and intelligent digital versions which can be searched more readily, paving the way for smarter, data-oriented RIM. That’s as long as information is complete, captured in a standard form, readily accessible, and reliable as a robust source of product truth.
In a global regulatory context, we’re also seeing the growing synchronization of efforts to drive up data quality and consistency, a consistent emphasis on transparency and data sharing, and the promotion of online portals for submitting and interacting with data. All of this creates considerable potential to do something more clever with this richer, more holistic and meaningful data bank that companies are building about their products across the complete lifecycle, and their status at any given time in the global market.
It is here that artificial intelligence begins to have significant appeal, as a means of making sense of and doing more with these increasingly substantial data assets.
Smarter Resource Allocation: The Emerging Role of AI
Combined with machine learning capabilities, artificial intelligence algorithms can both make discrete connections and spot trends in masses of data, and become increasingly efficient at this over time in response to the conditions they are exposed to and the results they find. This offers a wealth of potential to transform the way the life sciences industry manages and extracts value from data.