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Having accurate and up-to-date global regulatory intelligence covering both requirements, intelligence and precedent has always been key for Regulatory Affairs (RA) to meet business objectives and align with the company strategy. But how do pharma companies meet the challenges of managing regulatory intelligence on a global scale? In this interview with Pharma Commerce, Jens-Olaf Vanggaard, Senior Director, Global Safety, Regulatory and Quality Solutions, IQVIA, addresses this question and outlines other critical factors in transforming intelligence to drive automation and better data-driven decisions.
Pharma Commerce: What is needed to have accurate and up-to-date global regulatory intelligence for Regulatory Affairs (RA) to meet business objectives and align with the company strategy?
Jens-Olaf Vanggaard: Organizations must embrace a connected intelligence strategy to efficiently execute data-driven regulatory strategies. This entails having easy access to a global operational dataset aligned with a global regulatory intelligence reference model enabling alignment of both regulatory requirements, intelligence, and operational experience across the spectrum of product specifics, regulatory activities and markets and being able to utilize it to drive regulatory strategy, planning and operations. Having such a global central source of the truth where regulatory experts can gain instant insights to critical factors impacting regulatory strategy is step one of the journey toward enabling augmented regulatory workers to make better decisions faster—driving optimized strategies and outcomes. Adding purpose-built and trained AI/ML to the mix is the second step of this journey. AI and ML will unleash the full potential and value of strategic data assets and transform both regulatory strategy, planning and operations by enabling intelligent process simplification and automation across all three spheres.
What are today's challenges of managing regulatory intelligence on a global scale?
There is an increasing number and complexity of regulations for the pharmaceutical industry to comply with. In fact, there has been a 150% increase in regulatory mandates in the last five years (over 23,000 new guidelines) issued annually. That means new or changed regulations are announced nearly every 22 minutes. Compounding the issue is the industry’s continued sub-optimal alignment of regulations across markets. This means that organizations lack a global, up-to-date, single source of truth for regulatory intelligence that integrates both internal and external sources of information. This limits pharmaceutical organizations’ ability to utilize past experiences and regulatory submissions to drive strategies and plans. Now, to solve these problems, companies are turning to data collection, aggregation and AI/ML-driven analysis to make more data-driven regulatory decisions.
What are key strategies to managing regulatory intelligence in the future?
In short: achieve optimal, timely regulatory compliance; optimize regulatory strategy as per unique product profiles; and accelerate approvals by optimizing strategy and pathways. In reality, companies need to establish a global source of truth—one place where information is stored and can be easily referenced and pulled for analysis. Then the information stored in the single source of truth must be categorized by the type of regulatory activity and product and market specifics at a granular level. This categorization will allow AI-driven automation to associate the appropriate historical regulatory data with ongoing operations to provide appropriate insights as needed.
Are there specific use cases of how to leverage regulatory intelligence to drive efficiency within RA?
A good example of leveraging regulatory intelligence for decreasing time to approval and market is the global registration of a new product for marketing with regulatory authorities around the world. Each authority has different requirements and standards that must be met. Connected regulatory intelligence can inform regulatory strategies and plans through easily accessible up-to-date market specific requirements combined with historical data around what regulatory authorities approved or rejected, enabling better more robust planning leading, shortening the critical path to approval across markets and reducing the risk of rework and delays with their negative impact on both cost and growth. Leveraging automated intelligence via actionable insights reduces the time and resources spent identifying that critical information for each region’s regulatory authorities and leads to better regulatory and business outcomes.
What does the journey towards the future look like and what are the critical success factors?
It’s all about data, but also about how we can transform intelligence into something that is actionable to drive automation and better data-driven decisions. There is an increased focus on managing regulatory intelligence, which will enable organizations to improve the quality and amount of intelligence used in regulatory processes and allow them to realize better regulatory outcomes when using AI-driven analysis. However, the effective use of AI necessitates large amounts of data for analysis. This is where connected intelligence comes into play by pulling information from other processes and functions, including clinical, quality, safety processes in addition to regulatory information.