The European Medicines Agency- EMA went on to publish a draught reflecting paper dated July 19, which detailed out the agency’s present outlook when it comes to the usage of artificial intelligence so as to support safe as well as effective development, regulation, and also the use of human and veterinary drugs. The paper, which is now all out for public discussion, highlights the recommendations when it comes to the usage of Artificial Intelligence and Machine Learning across any step of the drug’s lifecycle, right from its discovery to the post-authorization setting.
As per the EMA’s press release, both AI and ML tools have it in them to effectively support the acquisition, analysis, transformation, and interpretation of data throughout the lifecycle of the medicinal product. Their application can go on to include AI as well as ML modelling approaches so as to replace, lessen, and refine the usage of animal models across preclinical development.
It is well to be noted that during the clinical trials’ stage, AI as well as ML systems can go on to assist with data recording and also its analyses, which can be submitted to regulators when it comes to marketing authorization procedures. Apparently, during the stage of marketing authorization, AI has tools so as to draft, translate, compile as well as review data that happens to be used in the product information of a drug. When it comes to the post-authorization stage, these tools can go on to potentially support pharmacovigilance actions.
The reflection paper stresses that a human-driven approach has to be at the forefront when it comes to all creation as well as the rollout of AI and ML. The total usage of AI must be in line with present legal requirements and also take into consideration ethics and fundamental rights’ respect into account.
The co-chair of the HMA-EMA Big Data Steering Group and the director of the Data Analytics Centre at the Danish Medicines Agency, Jasper Kjær said that the fact is that the use of AI is phenomenally developing in society, and as regulators, they see more applications when it comes to the medical field. It brings with it exciting options to create new insights and enhance processes. To have them entirely, they will have to be well-versed in the regulatory issues that are presented by a rapidly evolving ecosystem.
EMA also recommends that developers must look out for early regulatory support when it comes to AI and ML systems. As per Peter Arlett, who happens to be head of Data Analytics and Methods at EMA and BDSG’s co-chair, with this paper, they are indeed opening a dialogue with developers, other regulators, and academics to seek a way forward, making sure that the full potential of these innovations can be availed for the benefit of patients and also animal health.
The paper happens to be part of an initiative by BDSG to create the capability of the European Medicines Regulatory Network in regulation that is data-driven. It was created in collaboration with the EMA’s Committee for Veterinary Medicinal Products, the Committee for Medicinal Products for Human Use, and the BDSG.
