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Artificial intelligence (AI) is key to leveraging large volumes of regulatory and health data as well as new tools. This will encourage research and innovation. It will also support regulatory decision-making for safe, effective and high-quality medicines that reach patients faster.
This approach is in line with the European medicines regulatory network's plans on how to make use of AI.
It is also documented in the Network Data Steering Group's workplan for 2025-2028.
The workplan identifies actions in four key AI-related areas:
This workplan integrates and expands on the AI workplan set up by the former Big Data Steering Group. This document is available in the 'Related documents' section on this page.
For more information, see:
A reflection paper on the use of artificial intelligence (AI) in the medicinal product lifecycle is available:
It includes considerations to help medicine developers and marketing authorisation applicants use AI and machine learning in a safe and effective way at the different stages of a medicine lifecycle.
This paper reflects EMA's current experience in the evolving field of AI.
Medicine developers and applicants should understand the paper's considerations in the context of EU legal requirements and principles on AI, data protection, and medicines regulation.
The Methodology Working party developed the paper with support from the former Big Data Steering Group.
The Committee for Human Medicinal Products (CHMP) and the Committee for Veterinary Medicinal Products (CVMP) both adopted the paper in September 2024.
Guiding principles are available for European medicines regulatory network staff on how to use large language models in their work.
This document aims to promote the safe, responsible and effective use of this category of artificial intelligence (AI) technology.
Large language models focus on text generation.
They can help staff at medicine regulators across the EU in areas such as processing extensive documentation, automating data mining and optimising routine administrative tasks.
They also present challenges such as providing irrelevant or inaccurate responses and posing potential data security risks.
The overarching purpose of these guiding principles is to convey both capabilities and limitations of large language models.
The document covers the following principles and recommendations on the use of large language models:
EMA and the Heads of Medicines Agency (HMA) published the first version of this document on September 2024. It is regularly updated.
Read guiding principles
AI observatory reports support the Network Data Steering Group (NDSG) to monitor AI activities and trends.
They also help the European medicines regulatory network build knowledge and prepare for future regulatory needs.
EMA and the Heads of Medicines Agencies (HMA) publish AI observatory reports every year.
The 2025 AI observatory report provides an overview of activities and trends focused on four broad areas:
EMA and HMA published the 2025 AI observatory report in June 2026.
AI observatory reports cover both human and veterinary medicines.
They inform the implementation of the NDSG workplan for 2026-2028 and the European medicines agencies network strategy (EMANS) to 2028.
Select the expandable panel below for information about the 2024 AI observatory report:
The first annual report of the European medicines regulatory network's AI Observatory is available, including the results of a horizon scanning.
The report compiles the Network's experience with artificial intelligence (AI) during 2024 in:
In addition to the report, two other related documents are also available:
The horizon scanning report was based on the review of scientific literature and EU-funded projects. It helps identifying gaps, challenges and opportunities for integrating AI in medicine regulation.
The observatory captures and shares experiences and trends in AI to inform the work of the Network Data Steering Group. It ultimately supports the implementation of the group's multi-annual AI workplan.
EMA extended the functionality of its AI-enabled knowledge mining tool Scientific Explorer to support EMA and national competent authorities (NCAs) in finding information related to initial marketing authorisation applications of human medicines.
This includes public assessment reports.
The extended search functionality is available as of March 2026.
The tool enables easy, focused and precise search of regulatory scientific information from European medicines regulatory network sources.
EMA and NCA assessors are able to use the tool to customise their search for related information based on medicine name, disease or relevant keywords.
This supports decision-making via efficient retrieval of regulatory precedents.
EMA introduced the tool in March 2024, initially focusing on improving searches for EMA scientific advice procedures for human and veterinary medicines.
The tool is available only to approved and authenticated users representing the European medicines regulatory network.
For more information, see the document below with answers to frequently asked questions about this tool:
EMA’s human medicines committee (CHMP) accepts clinical trial evidence generated by an artificial intelligence (AI) tool supervised by a human pathologist.
This is the first time EMA will consider data generated with the assistance of an AI-based tool to be scientifically valid.
This tool helps pathologists analyse liver biopsy scans to determine the severity of metabolic dysfunction associated steatohepatitis (MASH). This was formerly known as non-alcoholic steatohepatitis (NASH). The previous denomination gives the tool its name: AIM-NASH.
It helps researchers obtain clearer evidence on the benefits of treatments in clinical trials with fewer patients.
EMA reached this milestone after its human medicines committee (CHMP) issued a qualification opinion on this AI-based innovative development methodology, in March 2025.
The qualification opinion was available for public consultation between December 2024 and January 2025.
EMA and the U.S. Food and Drug Administration (FDA) have jointly identified ten principles for good artificial intelligence (AI) practice in the medicines lifecycle.
The principles will guide AI use in evidence generation and monitoring across all phases of a medicine, from early research and clinical trials to manufacturing and safety monitoring.
They apply to both human and veterinary medicines.
An update log is available to show the date and summary of changes to this webpage. It does not include updates to linked documents or minor edits like typos or broken link fixes.
The tracking of updates begins in March 2026.
4 June 2026
Section on 'AI Observatory reports' updated to include information on the AI observatory report for 2025
3 March 2026
'AI tools and technology' section updated with information on the extended functionality of EMA's AI-enabled knowledge mining tool Scientific Explorer. The extended functionality helps national competent authorities search for initial marketing authorisation applications.