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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.
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.
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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.
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.
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.
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