Bird & Bird’s international life sciences and healthcare team is at the forefront of the legal developments with regard to AI and the life sciences sector. This article is the introduction of a series, which will highlight different legal angles to consider when implementing AI in the life sciences and healthcare industry.
As the life sciences sector continues to witness remarkable advancements in AI technology, the importance of a solid AI strategy becomes clearer – especially as this industry is already highly regulated.
In a short period of time, AI has been introduced in several areas, including drug discovery (including target identification), clinical research (for example outcome predictions), medical imaging, patient monitoring (for example for the treatment of chronic diseases) and manufacturing (for example for process optimization). The results are promising, but as one can imagine, the legal framework around AI in life sciences is rather complex.
At the moment the so-called trilogue negotiations for the AI Act are in full force, meaning the European Parliament, European Council and the European Commission are working towards agreement on a final text. For a more extensive update on this piece of legislation, see one of our updates here. Based on the current position, the AI Act may apply from the first half of 2026.
For the life science sector not only the AI Act is of major relevance, but also all other legislation that covers for example medical devices, pharmaceuticals, and clinical trials.
For medical devices, most notably the interplay between the Medical Device Regulations (EU) 2017/745 and 746 and the AI Act will be relevant, whereas the use of AI models may impact the classification and conformity assessment of medical devices. The Health Technology Assessment (HTA) Regulation (Regulation (EU) 2021/2282) adds another legal layer.
For the pharmaceutical industry, many changes are on the horizon already, with the proposed reform of the pharmaceutical legislation as announced by the European Commission recently. This proposal makes direct references to the use of AI already, and has a strong aim to foster technological innovation, for example by introducing so-called regulatory sandboxes. These sandboxes are in particular aimed to account for new technological advancements by allowing for derogations from the codified regulatory framework where otherwise the development of a medicinal product would not be possible. Currently applicable Directive 2001/83/EC on medicinal products for human use does not address the use of AI directly, but there are several relevant aspects that may have implications for the use of AI in the development and regulation of medicinal products. A good example of this is the pharmacovigilance requirement to monitor the safety of pharmaceuticals once they are on the market. AI may be used to analyse adverse event reports and identify potential safety issues. However, any use of AI in pharmacovigilance must be compliant with relevant regulations and guidelines, including the guidelines issued by the European Medicines Agency (EMA).
Focusing further on clinical trials, it is clear that AI has the potential to play a significant role in the design and implementation of clinical trials, including the identification of suitable patient populations, the selection of endpoints, and the analysis of trial data. As such, the use of AI in clinical trials may be subject to the requirements of the Clinical Trials Regulation (EU) no. 536/2014 and Directive 2001/83/EC – let alone the relevant national and international guidelines and relevant ethics committees that are involved during a clinical trial.
Furthermore, data protection is a key aspect to consider when deploying AI technologies in the life sciences. For example, for the EU the General Data Protection Regulation (EU) 2016/679 imposes stringent requirements for the collection, storage, and processing of personal data. Ensuring compliance with GDPR principles, such as data minimization, purpose limitation, and transparency, is crucial when handling vast amounts of patient information. In addition, patient information will most likely contain or consist of health data, which are classified under the GDPR as ‘special category data’ for which a heightened level of protection, and thus even stricter rules apply when collecting, storing and processing such data.
Very recently, the European Medicines Agency also published a draft reflection paper on the use of artificial intelligence in the lifecycle of medicines, with the aim to ‘reflect on the scientific principles that are relevant for regulatory evaluation when these emerging technologies are applied to support safe and effective development and use of medicines’. The reflection paper is part of the wider strategy of the Big Data Steering Group (BDSG) from the Heads of Medicines Agencies and the European Medicines Agency, which focusses on data-driven regulation. Public consultation on this specific draft paper is open until 31 December 2023.
In conclusion, the use of AI has the potential to transform the life science industry and is already doing so as we speak. However, the implementation of AI in the life science sector must be done responsibly and in compliance with the relevant regulations and guidelines. With a clear strategy in mind, AI provides possibilities to revolutionize the life science industry and improve patient outcomes for years to come.
This article is the start of our AI & Life sciences series. In our next articles we will dive deeper in some of these topics mentioned, see below for our future articles. In case of questions, do reach out to Christian Lindenthal or Hester Borgers.