Augmenting the Pharmaceutical Regulatory Worker With AI and ML
Learn how AI, ML, and LLM technologies augment regulatory workers.
The power of automation and artificial intelligence has reached far and wide, and the pharmaceutical regulatory affairs industry is preparing to navigate the integration of next-generation technologies and human expertise, says Michelle Gyzen, senior director at IQVIA.
The expansion of artificial intelligence (AI) within the life sciences space is fundamentally altering the landscape of the pharmaceutical industry. Ongoing efforts focus on optimizing and expediting regulatory affairs functions through the integration of automated processes, utilizing tools such as generative AI, machine learning (ML), natural language processing (NLP), and large language models (LLMs).
Considering these technological innovations, what does this transformed reality entail for regulatory teams and their workflows? In a nutshell, attention has shifted to leveraging automation to augment the skills of regulatory professionals, leading to the emergence of what has been termed ‘the augmented regulatory worker.’
So, how can organizations navigate the implementation of automated processes and ready themselves for the evolution towards the augmented regulatory professional?
What Are the Key Objectives of Pharma Regulators?
First, it is important to look at where regulators focus on improving their responsibilities. Global regulatory harmonization seeks to minimize regulatory differences without compromising substance, aligning with agencies’ holistic mission to
- Ensure optimal and timely compliance with global regulations across the product lifecycle.
- Facilitate enhanced patient access and expedite approval timelines by optimizing regulatory strategy, pathways, and operations.
The continued evolution of regulatory affairs in the pharmaceutical sector relies on the ability of pharmaceutical organizations to develop and implement increasingly sophisticated strategies to optimize the time, cost, and risk associated with drug development from discovery to post-registration. Across multiple dimensions of regulatory affairs, current trends reflect a rising complexity spanning requirements, operating models, data collection, technology, and resourcing.
To mitigate these evolving complexities, pharmaceutical companies are focused on augmenting their capabilities and access to information. The emphasis lies not in supplementing regulatory professionals but in making the role more accessible and manageable, empowering regulatory professionals to focus on essential aspects that can improve outcomes.
Success here requires a thorough understanding of current and future trends in regulatory compliance and technological expertise to leverage these trends through extracting, analyzing, and contextualizing relevant data. This new paradigm involves a cultural shift, with internal process enhancements, strategic collaborations with vendors, and the increased diversity of skill sets amongst team members.
The integration of worker-augmenting automation is a fundamental component in this effort, as the shift in regulatory operations towards cloud-based Regulatory Information Management (RIM) platforms that started in the 2010s has evolved into the 2020s. The focus is on augmenting regulatory workers with enhanced capabilities and expanding the RIM domain by emphasizing intelligence, strategy, and decision-making.
Incorporating state-of-the-art platforms across next-generation electronic document management, labeling, regulatory tracking, and publication technology will act as a catalyst for embracing the transformative process and bringing it to fruition. Reflecting on the regulatory objectives, enabling, supporting, and accelerating regulatory technology and services is becoming more vital than ever.
See More: Global AI Regulation: Adaptability Is the Key to Success
What Does Augmentation Look Like?
To ascertain the optimum level of augmentation required to enhance human expertise and productivity, pharmaceutical companies must evaluate the nature of the automated task. For example, repetitive tasks of low complexity are well-suited for total automation that utilizes bots, rule-based algorithms, or integrated operational applications.
On the other hand, as task complexity increases – for example, data extraction, transformation, pattern-based suggestions, and content generation – AI, ML, NLP, and LLM technologies start to add tangible value in expediting operations. These semi-automated processes still require expert validation and finalization by a regulatory professional.
Automation is focused on gathering data when we move up the ladder to high-level strategic decision-making tasks. These tools make all the necessary information available for informed human decision-making through automated smart search, summaries, data analysis, and intelligent chatbots.
There is no one-size-fits-all approach to implementing automation levels to augment regulatory professionals. It is a complex undertaking, as augmentation is integrated at various stages of the worker journey and incorporates individual expertise levels.
A Word on Generative AI
The previous year has been all about Generative AI, and it is important to explore the role that the adoption of this technology is likely to have on regulatory worker augmentation.
Although in its early stages, the expectations are significant. Generative AI will greatly augment the regulatory profession by expediting data mining, analytics, software operations, and content creation. By enhancing these functions, AI can reduce the burden on people and elevate the speed and precision of strategic risk assessments, predictive analyses of regulatory outcomes, and engagements with health authorities.
Integrated Solutions
Integrated platforms that can streamline and consolidate processes from various internal and external regulatory intelligence sources should be considered a priority. Beyond regulatory intelligence gathering, an augmented approach benefits the publishing workflow in regulatory affairs. These solutions and their advanced automation capabilities can, for example, significantly improve the efficiency of manual bookmarking and hyperlinking in this process.
Of course, not all regulatory functions will be equally or immediately suitable for automation. Workflows requiring specialized regulatory, therapeutic area, or product program management expertise will be impacted last. There remains a critical role for local regulatory expertise and specific knowledge in therapeutic areas demanding dedicated focus and resource allocation.
Future Is a Collaborative Evolution
Embracing the automation of regulatory functions that support process streamlining and acceleration, pharmaceutical companies must anticipate changes affecting culture, processes, worker skill sets, and partnership strategies. To ensure a seamless transformation, organizations must comprehensively understand change management and clearly outline the proactive steps to be taken.
A culture that embraces augmented workers demands transparency, awareness, and an openness to technology and innovation. The emphasis must be on supporting rather than replacing, and overcoming historical hesitations in regulatory affairs technology is crucial, as is embracing imperfections in the iterative development process. Ongoing discussions and refinements are key to producing ‘technology champions.’ Understanding how vendors and providers contribute to these goals is also pivotal, requiring alignment with organizational strategy.
From a pharmaceutical regulatory affairs perspective, automation and worker augmentation can drive important benefits such as enhanced compliance and data integrity, increased efficiency, and greater productivity.
Automation can complement human expertise. AI-powered tools can help analyze complex data and provide insights that humans might miss, leading to better regulatory decisions.
What tools has your organization adapted to streamline the workflow? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
Image Source: Shutterstock
MORE ON AI REGULATIONS
