The European Medicines Agency- EMA and the Heads of Medicines Agencies- HMAs have gone on to publish a plan that helps to set out a collaborative as well as coordinated strategy so as to maximize the advantages of artificial intelligence- AI in regulation.
The workplan, which happens to run until 2028, will go on to help the European medicines regulatory network- EMRN take up the opportunities of AI when it comes to personal productivity, automating processes along with systems, growing insights into data, as well as supporting stronger decision-making in order to benefit public and also animal health.
The plan happened to be prepared by the Big Data Steering Group- BDSG which is a joint initiative between HMA and EMA. The objective of this steering group is to make sure that the EMRN continues to be at the forefront of benefiting from AI when it comes to medicine regulation.
Apparently, the document was adopted by EMA’s Management Board at its meeting in December.
Four key dimensions when it comes to the AI workplan
It is well to be noted that the first version of the BDSG multi-annual workplan focuses on four areas so as to facilitate the development as well as use of responsible and beneficial AI.
Guidance and policy, along with product support: Actions focus on consistent support for products in development, along with the development and evaluation of apt guidance for the usage of AI in the lifecycle of a medicine. Work has already started with the ongoing public consultation when it comes to the AI reflection paper, which is open until the end of 2023. Preparations so as to support the implementation of the EU AI Act will begin in 2024.
AI tools and technology: The idea is to identify as well as provide frameworks so as to use AI tools to grow efficiency, elevate understanding and evaluation of data, and support decision-making. Complete compliance when it comes to data protection legislation will be ensured.
Training and partnership: Initiatives happen to be designed so as to continuously develop the capacity as well as capability of the network, partners, along with stakeholders so as to keep ahead of the evolving field of AI.
Experimentation: The workplan considers the fundamental role of experimentation when it comes to experimentation in speeding-up learning and also gaining new insights. Numerous actions are proposed so as to make sure of a structured approach to experimentation throughout the network.
Because of the fast evolution of AI technology such as the ethical and policy aspects that are related to it, the Big Data Steering Group looks to regularly update the workplan.
