Pfizer’s David Isom and Monica Mihedji, writing in the November 2023 edition of the DIA’s Global Forum magazine, examine how the European Medicines Agency is attempting to integrate the use of artificial intelligence in its regulatory work.
Regulators are advancing information technology and data modernization initiatives to drive more efficiencies and to become more responsive to industry use of digital technologies in drug development. These include digital health technologies to promote decentralized trials, cloud-based platforms to enable more capacity and external collaboration opportunities, and machine learning (ML) technologies including artificial intelligence (AI) to transform review of high-volume data, including real-world evidence programs. A key milestone took place in July of 2023, with the release by the European Medicines Agency (EMA) of a reflection paper sharing their views on the use of AI in the regulation of medicines.
The EMA recently published for public consultation a draft reflection paper on the use of artificial intelligence (AI) in the medicinal product lifecycle to support the safe and effective development, use, and regulation of AI for human and veterinary medicines. The paper reflects on principles relevant to the application of AI and ML at any step of a medicine’s lifecycle, from drug discovery to the post-authorization setting. The reflection paper, co-developed by the HMA (Heads of Medicines Agencies)/EMA Big Data Steering Group, the Committee for Medicinal Products for Human Use (CHMP, and its Methodology Working Party), and the Committee for Veterinary Medicinal Products (CVMP), is part of the joint HMA-EMA Big Data Steering Group (BDSG) initiatives to develop the European Medicines Regulatory Network’s capability in data-driven regulation.
AI tools are in common use by companies such as Google and Netflix, and have been in use in the pharmaceutical industry, particularly for automating internal processes. However, the use of AI can mean many different things. The EMA defines AI as systems that display intelligent behavior by analyzing their environment and taking actions with some degree of autonomy to achieve specific goals. The Food and Drug Administration (FDA) refers to AI as a range of technologies, statistics, and engineering that use algorithms or models to perform tasks and exhibit behaviors such as learning, making decisions, and making predictions. The acceleration of the use of AI, in particular the rapid introduction of new Large Language Models (LLMs) such as Generative AI (GenAI), have introduced excitement for the potential for AI to drive innovation in drug research and development, and with that has increased concerns around its potential for misuse.
