New product liability risks for AI products

The new Product Liability Directive aims to modernise the product liability rules and remove obstacles for consumers. What should life sciences companies using AI in products know about the new product liability rules.

by Dr. Lena Niehoff

5 of 10 Insights

Purpose limitation and data minimisation: key considerations for AI training in the life sciences sector

The use of real-world evidence data to train AI models is becoming a critical component in advancing research and drug development. We explore how two of the GDPR's guiding principles are more than just regulatory requirements.

by Victoria Hordern and Dr. Tim Jonathan Schwarz

3 of 10 Insights

UK approach to regulating AI in Life Sciences

As AI innovation in the life sciences sector continues at pace, the Medicines and Healthcare products Regulatory Agency (MHRA) publishes principles and guidance in relation to software-as-a-medical-device which includes the application of AI.

by Alison Dennis

1 of 10 Insights

Selecting your AIA notified body

Manufacturers/providers of medical devices that, according to the EU AI Act, include a high-risk AI system (HRAIS) require a notified body assessment of their technical documentation and/or quality management system should urgently consider which notified body to appoint.

by Dr. Stefanie Greifeneder and Alison Dennis

6 of 10 Insights

Re-use of patient data in scientific research to train AI systems - important GDPR considerations

Using AI systems in scientific research raises important regulatory considerations. When an AI system is trained with patient data, compliance with GDPR becomes necessary and must undergo a compatibility assessment to ensure it aligns with the purpose limitation principle.

by Séverine Bouvy

4 of 10 Insights

Data privacy in AI due diligence

AI has become an integral part of business operations across various industries. Its deployment demands careful legal and strategic considerations. Before integrating AI systems in a company’s workflows, thorough diligence should be conducted.

by Dr. Carolin Monsees, CIPP/E

7 of 10 Insights

The regulation of clinical trials in which AI is deployed

While the AI Act is not applicable to certain research uses of AI, these exemptions do not apply to the use of AI in clinical trials, where a myriad of regulation and guidance has potential application.

by Alison Dennis and Dr. Manja Epping

2 of 10 Insights

Damages for Incorrect SCHUFA Report: Analysis of the BGH Ruling of 28 January 2025 (VI ZR 183/22)

by Dr. Jakob Horn, LL.M. (Harvard) and Alexander Schmalenberger, LL.B.

Data privacy in AI pre-contractual due diligence

AI is transforming healthcare and life sciences, by enabling innovations in diagnostics, treatment personalisation, and operational efficiency. This article explores essential considerations for data privacy in pre-contractual AI due diligence, focusing on legal obligations, risk mitigation strategies, and ethical concerns.

by Marc Schuler

8 of 10 Insights

Navigating IP in AI due diligence

As AI models evolve over time, specific considerations will need to be incorporated into any due diligence. These include whether the solution is licensed-in to be licensed-out and has been pretrained/trained with third party or customer data.

by Christopher Bakier

9 of 10 Insights

FinTech Matters - March 2025

by multiple authors

The UPC: a new rocket docket for life sciences patent litigation

by Dr. Anja Lunze, LL.M. and Dr Paul England