Life sciences & healthcare
Our Life Sciences and healthcare team work with some of the largest pharmaceutical, biotechnology, and medical device companies and healthcare providers in the world to a diverse collective of small-to-medium-sized start-up enterprises ready to upscale their business, and many companies in between.
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Advertising Medical Devices European Comparison Tool
Looking to promote your medical device products in Europe? Access our comparison tool to manage regulatory challenges across multiple jurisdictions.
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The Unified Patent Court (UPC)
The UPC and Unitary Patent will introduce the most radical changes to patent litigation in Europe in 40 years.
Read our guide to the UPC
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.
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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.
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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.
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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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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.
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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.
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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.
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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.
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