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EMA: Harnessing AI in Medicines Regulation: The Role of Large Language Models (LLMs)

The advancement of Artificial Intelligence (AI) is transforming many industries, and the pharmaceutical and regulatory sectors are no exception. One of the most impactful AI technologies is Large Language Models (LLMs), such as GPT or BERT, which have immense potential to enhance regulatory processes, drive innovation, and support decision-making.


As part of a set of guiding principles, the European Medicines Agency (EMA) and Heads of Medicines Agencies (HMA) have agreed to use large language models (LLMs) to make regulatory decisions. As part of the integration of these technologies into the regulation of medicines, the European Medicines Agency (EMA) and other regulatory bodies have explored safe and effective methods.


Large Language Models (LLMs) are powerful AI systems trained on vast amounts of textual data to understand, generate, and respond to human language. These models use deep learning techniques to process natural language and can be employed to assist in a variety of tasks, including regulatory documentation, medical literature review, and even predicting outcomes based on data trends.


LLMs are now becoming essential tools in regulatory science, especially in tasks that involve large-scale data interpretation and text processing, allowing regulatory agencies to analyze vast bodies of data more efficiently.

Recognizing the potential of AI, the EMA has laid a roadmap for integrating LLMs into regulatory science. The recent guidance, titled Guiding Principles on the Use of Large Language Models in Regulatory Science and for Medicines Regulatory Activities sets forth principles and frameworks for using LLMs in a controlled and responsible manner.


To systematically incorporate AI into regulatory activities, the EMA and Heads of Medicines Agencies (HMA) have collaborated on the Multi-Annual Artificial Intelligence Workplan 2023-2028. This work plan provides a roadmap for harnessing AI in medicines regulation, focusing on Big Data, to foster innovation while ensuring safety.


As the use of AI increases, so does the need for responsible implementation. The EMA outlines four key principles for the safe and effective use of LLMs in regulatory science:

  1. Ensure safe input of data

  2. Apply critical thinking and cross-check outputs

  3. Keep up to date with how to make best use of LLMs

  4. Know who to consult and report issues to


EMA’s commitment to incorporating AI in a safe, transparent, and accountable manner ensures that the benefits of these technologies can be fully realized without compromising patient safety. The use of Large Language Models (LLMs) represents a groundbreaking step in medicines regulation, offering enhanced efficiency, better decision-making, and improved data processing capabilities.

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