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.
MehrWhile 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.
MehrThe 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.
MehrUsing 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.
MehrThe 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.
MehrManufacturers/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.
MehrAI 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.
MehrAI 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.
MehrAs 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.
MehrAlison Dennis looks at the addition of the EU AI Act to the regulatory framework around medical devices.
Mehr
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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 von 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.
2 von 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.
7 von 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.
3 von 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 von 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.
4 von 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.
1 von 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.
9 von 10 Insights
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.
8 von 10 Insights
