The utilisation of artificial intelligence (AI) is an important part of the digital transformation. Such systems are often developed through the process of machine learning (ML) where models are trained from data, with or without human input.
However, as these models often contain exceptionally large numbers of trainable parameters arranged in non-transparent model architectures, new risks areintroduced that need to be mitigated to ensure the safety of patients and integrity of clinical study results.
Also, as the overarching approach is inherently data-driven, active measures must be taken to minimise the integration of bias into AI/ML applications and promote reliable and trustworthy AI.
This reflection paper provides considerations on the use of AI/ML in the lifecycle of medicinal products, including medicinal products development, authorisation, and post-authorisation.
Given the rapid development in this field, the aim of this reflection paper is to reflect on the principles that are relevant for regulatory evaluation when these emerging technologies are applied to support safe and effective development, manufacturing and use of medicines.
Reflection paper on the use of Artificial Intelligence (AI) in the medicinal product lifecycle