POLAND Trends and Developments Contributed by: Barbara Kiełtyka, Jakub Gładkowski and Małgorzata Kiełtyka, Kieltyka Gladkowski KG Legal
and potential theft of patients’ and employees’ personal data. Use of Artificial Intelligence in the Life Sciences Sector Regarding AI use in life sciences, the most impor- tant legal acts are Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 on the establishment of harmo- nised rules on AI and the Act of 6 September 2001 – Pharmaceutical Law ( Journal of Laws of 2024 , item 686, as amended). In the context of the use of AI in the development of new medi- cines, the provisions on high-risk AI systems are important. High-risk systems are systems that meet the conditions specified in Article 6, para- graph 1 of the Regulation, as well as those listed in Annex III of the Regulation as systems posing a significant risk of damage to health, safety, fun- damental rights (eg, privacy) or the environment. The Regulation separately specifies the obliga- tions of suppliers of high-risk systems (primarily in Article 16 et seq) and the entities using such systems (Articles 26–27). Suppliers of high-risk systems will also have to undergo a procedure assessing their compliance with the require- ments of the Regulation. As alluded to above, AI systems used in the healthcare sector, including for the develop- ment and testing of new drugs, can be classified as high risk. In practical terms, by using an AI system to process registration documentation, companies will be able to speed up drug approv- al procedures during the necessary registration processes. In addition, AI algorithms will be able to help analyse large data sets, including pre- clinical and clinical documentation. AI can also facilitate the conduct of clinical trials, including through automatic analysis of clinical data and selecting patients for clinical trials and subse- quently monitoring them. Moreover, AI systems
can promote pharmacovigilance: algorithms can analyse adverse event reports and identify potential risks to patients. However, it should be remembered that any implementation of AI must comply with the principles of good manufactur- ing practice (GMP) and good clinical practice (GCP), and with EU regulations. Introducing modern technologies into the regu- lated pharmaceutical environment is associated with challenges related to ensuring quality and compliance with applicable regulations. In this context, Good Automated Manufacturing Prac- tice (GAMP) 5 is one of the most important tools for managing the life cycle of computer systems in the pharmaceutical and biopharmaceutical industries, including systems based on AI. GAMP 5 is a set of guidelines developed by the International Society for Pharmaceutical Engi- neering (ISPE) to assist pharmaceutical com- panies in ensuring compliance with regulations concerning the quality and security of computer systems. This document presents a comprehen- sive approach to managing the life cycle of com- puter systems, including the validation, design, implementation, operation and retirement of systems that are used in environments requiring high quality standards, such as the pharmaceuti- cal industry. Medical Device Conformity Assessment Significant regulations and trends can be observed in medical device conformity assess- ments for regulatory purposes. In this context, guidelines for technical and legal classifica- tion and certification of medical products and diagnostic devices, performed before they are placed on the market by a notified body assess- ing conformity in accordance with Regulation 2017/745, as well as the ISO 13485 standard –
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