Blog
Understanding the impact of AI on Regulatory Affairs
Posted on the 4th April 2024
From content generation to self-driving cars, Artificial Intelligence (AI) has emerged as a transformative force in recent years.
Through intricate algorithms, machines have acquired the capacity to learn and mirror human intelligence, revolutionizing how we interact with technology in the workplace and our day-to-day lives.
Whilst an instantly recognizable term, AI remains a misunderstood concept that few in regulatory affairs truly comprehend, let alone fully utilize.
In this article, Dan Flynn demystifies AI, explores its fundamental components and functionalities, and provides a foundational understanding of AI and its potential future implications for regulatory publishing, particularly in its integration with eCTD 4.0.
An opportunity for innovation
Regulatory is constantly evolving, and the integration of AI presents an opportunity for innovation. By revolutionizing traditional processes, AI has the potential to pave the way for a more streamlined, efficient, and accurate submission process.
This blog dives into the key components of AI, as well as its potential role, specifically in regulatory publishing and integration with eCTD 4.0.
The integration of AI into regulatory publishing marks a significant shift in the regulatory landscape.
It introduces unprecedented opportunities to expedite processing time, elevate accuracy in submissions, and enhance overall compliance measures. In recent years, AI has seen remarkable advancements in availability and capability across various contexts and industries.
These empower regulatory professionals to navigate the complexities of document authoring, submission compilation, and quality control checks with greater ease than ever before.
eCTD 4.0
eCTD 4.0 is designed to align closely with current regulatory guidelines and standards, ensuring consistency and compliance across diverse regulatory agencies worldwide. This alignment encompasses adherence to ICH guidelines, regional requirements, and emerging best practices. The latest iteration of eCTD may introduce enhanced functionalities, such as improved support for structured product labeling (SPL), updated validation criteria, and enhanced compatibility with modern software and systems. (1)
The emergence of eCTD 4.0 catalyzes the integration of AI into regulatory publishing. The implementation of advanced features geared toward a data-oriented submission process lays a robust foundation for the incorporation of AI technologies.
Semantic Annotation and Metadata Tagging
Used to enrich understanding, organization, and retrieval of information within documents, databases, or other content repositories, semantic annotation, and metadata tagging are crucial elements of data structure, and accessibility.
The potential of these techniques could solve the challenges of manipulating unstructured and heterogeneous data sources within the pharmaceutical industry. Searchable information, tagged with metadata allows the use of complementary tools to develop structured documentation and published output.
This is particularly relevant to the next technology described below, natural language processing, where annotated data can be used to train algorithms for more accurate information extraction and analysis.
Natural Language Processing (NLP)
NLP focuses on enabling computers with the ability to comprehend both written text and spoken language like humans.
NLP advancements empower AI systems to rapidly understand and summarize large bodies of text. This capability holds immense potential in regulatory publishing, especially with the introduction of eCTD 4.0.
By employing NLP, AI can scan extensive text volumes, enabling it to highlight discrepancies and offer guidance in terms of accuracy and document location in the build where there is any ambiguity. (2)
Machine Learning
Machine learning is concerned with utilizing data and algorithms to mimic the learning processes of humans.
This helps the AI system gradually improve its accuracy over time. Implementing AI in the earlier stages of the eCTD 4.0 rollout will provide the AI systems with an opportunity to learn and improve.
Furthermore, machine learning allows AI systems to learn from historical data, thereby accelerating the compilation and preparation of submission documents with a precision that surpasses manual processes performed by humans. (3)
Data Analysis Capabilities
As eCTD 4.0 initiates the transition towards data-oriented submissions, the capability of AI to analyze vast datasets in real time will be instrumental in ensuring the accuracy and integrity of the data provided throughout the submission lifecycle.
This will allow regulatory professionals to efficiently detect any discrepancies before filing which may lead to future variations or inconsistencies in the product’s lifecycle. In this way, AI can be implemented as a vigilant safeguard, minimizing the risks of non-compliance.
Our Experience With AI
G&L Healthcare Advisors has been actively exploring the application of AI software in Regulatory Affairs, with a specific focus on streamlining regulatory processes.
Our work here has yielded promising results, positioning us to continue providing high-quality work with the utmost efficiency for our clients in the future. This also helps us to guide clients considering embarking on a similar digital journey.
Implementing AI technology in day-to-day business is a challenge almost any modern business will eventually have to tackle, and we are collaborating diligently with expert vendors to stay ahead of the curve, providing a platform of services that meet the future of Regulatory Affairs.
For help with your digital journey
G&L Healthcare Advisors has information on our website and LinkedIn. For an initial consultation on our Advisory Services please contact us
References:
- International Conference on Harmonisation, electronic Common Technical Document - eCTD v4.0, (Jan 2024), [Online] https://ich.org/page/ich-electronic-common-technical-document-ectd-v40
- https://www.ibm.com/topics/natural-language-processing