Agenda
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Day 1 — Main Conference
April 15, 2026
Breakfast and Registration
Regulation Versus Innovation: Navigating the Complex Interplay Between Diverging Global AI Regulations
Koen CobbaertSenior Manager - Quality, Standards & RegulationPhillips
Andrew DavidsonGlobal Legal Business PartnerGilead Sciences
Alex DenoonPartner – Life Sciences RegulatoryBristows LLP
The global regulatory landscape for AI is evolving quickly, with each jurisdiction taking its own, sometimes divergent, approach. For life sciences companies operating across borders, this fragmentation creates a complex compliance landscape and a growing patchwork of laws that are shaping how AI is developed and utilized.
Get to grips with how global regimes intersect and diverge, and what that means for compliance, market access, and innovation.
Key takeaways:
- Comparing global AI regulatory trends and their impact on life sciences innovation – EU AI Act, FDA draft guidance, Chinese AI measures, UK MHRA AI principes.
- Managing dual or overlapping compliance obligations across the AI Act, MDR/IVDR, the Digital Omnibus proposal, data protection, and ethical frameworks.
- Building scalable AI governance frameworks that support responsible innovation while aligning with multi-jurisdictional expectations.
- Anticipating emerging standards, audit mechanisms, and enforcement priorities.
Networking and Refreshment Break
Sandra BarbosuAssociate Director, Center for Life Sciences InnovationInformation Technology & Innovation Foundation
Anne Kristine Steen MarkeSenior AI & Digital Governance LeadNovo Nordisk
Carmen MiguelGlobal Legal Data Privacy Director and Lead LawyerAlnylam Pharmaceuticals Inc.
Andreea ȘerbanGlobal Privacy and AI AnalystFuture of Privacy Forum
As AI adoption accelerates across the life sciences value chain, embedding data privacy principles is of paramount importance to ensure regulatory compliance and public trust.
This session addresses the legal, ethical, and operational risks under frameworks such as GDPR, the EU AI Act, the Digital Omnibus proposal and other emerging global privacy laws.
Key takeaways:
- Navigating the intersection of the AI Act, GDPR, the Digital Omnibus and global privacy frameworks across research and commercial use cases.
- Managing re-identification risks in AI training and model deployment.
- Ensuring lawful data use and consent across clinical and research contexts.
- Exploring the growing role of Privacy-Enhancing Technologies (PETs) in enabling secure and compliant data sharing.
- Applying privacy-by-design and privacy-by-default in AI development.
- Building trust through transparency, accountability, and ethical governance.
Networking Lunch
Noëmie BarberisDirector, Senior Counsel Digital, Privacy & Cyber SecurityGSK
Lien DelvoyeSenior Legal Director, Surgery EMEA & Strategic SolutionsJohnson & Johnson MedTech
Mimmi SundlerSenior Director, R&D Data & AI GovernanceNovo Nordisk
Dave HughesPartnerEversheds Sutherland
This session will explore how leading life sciences companies are building enterprise-wide AI governance frameworks that align innovation with accountability.
Gain insight into real-world strategies to operationalize responsible AI principles across complex global organizations that integrate regulatory, ethical, and data governance requirements into scalable processes.
Key takeaways:
- Defining AI from regulatory compliance perspective and taking inventory of the use of AI across the organization.
- Structuring effective AI governance frameworks across R&D, clinical, and commercial functions.
- Integrating AI oversight with existing quality and regulatory systems (GDPR, MDR/IVDR, FDA).
- Defining accountability, ownership, and cross-functional governance models.
- Building inventories, risk classification systems, and lifecycle controls for AI models.
- Fostering a culture of responsible AI and continuous compliance.
Networking and Refreshment Break
Peder BlomgrenVice President and Head of Data Office, R&DAstraZeneca R&D | Data Science & AI
Aneta TyszkiewiczDirector, Science & RegulatoryEFPIA - European Federation of Pharmaceutical Industries and Associations
Véronique ViardVice President, Global Head of Legal for DigitalSanofi Legal, EBI & Global Security
AI is reshaping target discovery, design, and development, but value only materializes when models, data, and workflows are validated, governable, and submission ready. This session cuts through the hype to show where AI is delivering measurable uplift, and what operating changes are required to scale it safely and responsibly.
Key takeaways:
- Addressing the AI Act R&D exemption
- Accelerating target identification, hit finding, lead optimization, and vaccine design.
- Demonstrating real-world case studies with measurable metrics.
- Validating models for scientific and regulatory fitness.
- Balancing innovation with compliance by governing model lifecycles, training teams, and prioritizing uses cases with clear ROI.
Olivier MignoletPartnerSimmons & Simmons LLP
As AI embeds into devices, diagnostics, and digital health, MedTech faces new liability exposure under the EU Product Liability Directive (2024/2853). Ahead of the December 2026 implementation deadline, this session will help you identify concrete steps – governance, documentation, and human-oversight controls – to anticipate and mitigate these risks.
Key takeaways:
- Understanding the EU PLD framework in relation to AI-driven medical and diagnostic products
- Managing liability for software updates, adaptive learning and model drift
- Allocating responsibility across complex AI supply chains and partnerships
- Understanding interactions between the AI Act, MDR/IVDR, and product liability frameworks
- Allocating risk across complex supply chains, vendors, and cloud/AI service providers
- Implementing governance measures: traceability, change control, post-market monitoring, and audit readiness
- Assessing insurance and contractual approaches to transfer or mitigate residual liability risk
Networking Reception Sponsored by
Day 2 — Main Conference
April 16, 2026
Breakfast and Registration
Alexander KorenbergPartnerKilburn & Stride
AI-driven discovery can reshape how therapeutics are identified and developed, but it triggers complex IP, data-protection, liability, and compliance concerns. This session focuses on establishing clear inventorship, preserving defensible IP, and structuring collaborations that fairly allocate ownership between pharma, AI developers, and research partners.
Key takeaways:
- Defining inventorship when AI contributes to molecular or biological discoveries.
- Understanding current positions of major patent offices (USPTO, EPO, CNIPA, UKIPO) on AI-assisted inventions.
- Drafting claims and disclosures that reflect human contribution and satisfy patentability requirements.
- Managing IP ownership in multi-party collaborations (AI developers, pharma, academia).
- Data rights and transparency: documenting datasets, training models, and model outputs to support patent claims.
- Avoiding invalidation risks from inadequate inventorship attribution or lack of human contribution.
- Preparing for policy evolution at WIPO and national IP offices on AI-generated inventions.
Networking and Refreshment Break
Alison DennisPartnerTaylor Wessing
Ulrich JuknatSenior Legal Director Regulatory Law, EMEAJohnson & Johnson MedTech
Julien SzczesniakProduct ReviewerTÜV SÜD
Alex ZaretskyAssociate Head AI Notified BodyBSI
Developers of AI-enabled devices and diagnostics face overlapping MDR/IVDR and AI Act duties. This session translates dual compliance into concrete steps. The presenters will clarify high-risk triggers, joint conformity assessment mechanics with notified bodies, and what data governance, transparency, and human-oversight rules mean in clinical/diagnostic contexts.
Key takeaways:
- Determining when the AI Act applies alongside MDR/IVDR.
- Integrating AI-specific QMS, risk, and data governance requirements.
- Coordinating conformity assessments with notified bodies.
- Managing algorithm changes and post-market monitoring.
- Preparing for phased implementation and future guidance.
Networking Lunch
Practical Approaches for Navigating Contractual Controls with Third-Party Party Suppliers’ Use of AI
Diederik ArnautLegal Lead IT & ProcurementUCB
Dr. Nils Rauer, MJIPartner, Global Co-Lead, AIPinsent Masons LLP
Kathrin Zapasnik-SchneiderGC Procurement, ESG & EU Legal OperationsTeva Pharmaceuticals Europe
Gain insight into how organizations are managing and governing AI developed or supplied by third parties, while maintaining accountability, regulatory compliance, and operational control. As AI supply chains grow increasingly complex – spanning data providers, software vendors, and cloud partners – robust frameworks are needed to ensure trust, quality, and legal defensibility.
Key takeaways:
- Developing due diligence processes for AI suppliers that integrate AI-specific obligations into supplier codes of conduct, procurement policies, and QMS.
- Structuring contractual indemnities, warranties and liability clauses to allocate risk.
- Defining human oversight mechanisms to ensure meaningful human control.
- Aligning supplier management and technical assurance with the AI Act, GDPR, and Product Liability frameworks
Kristof Van QuathemPartnerCovington & Burling LLP
The proposed BioTech Act Could reshape Europe’s innovation rules, and its intersections with the EU AI Act, MDR/IVDR, and GDPR will defined how AI-enabled biotech is built, validated, and commercialized. This session clarifies the emerging obligations and opportunities so legal, compliance, and R&D leaders can make near-term decisions with confidence.
Key takeaways:
- Mapping overlaps and conflicts between the BioTech Act, AI Act, MDR/IVDR, and GDPR
- Defining data governance duties
- Allocating IP and inventorship in AI-assisted discoveries and structuring collaboration terms with vendors, CROs, and academia
- Mitigating product-liability exposure and operationalizing compliance roadmaps for implementation
Refreshment Break
Unlocking the Potential of Health Data and AI to Accelerate Research, Foster Innovation and Improve Patient Outcomes
Dr. Hatim AbdulhusseinCEONHS' Health Innovation Kent Surrey Sussex (KSS)
Juan-Jose VenturaResearch and Patient Engagement DirectorCancer Patients Europe
As the EU moves toward implementing the European Health Data Space (EHDS), stakeholders are preparing for a new era of data-driven health innovation. This session will explore how the EHDS will open access to health datasets for AI research and what legal, technical, and ethical frameworks must be in place to manage the associated risks.
- Analysing the EHDS framework and its goals for research and AI innovation.
- Assessing how pseudonymized health data can be used responsibly to train AI systems.
- Comparing the UK Data Use and Access Act and implications for cross-border collaboration.
- Applying legitimate interest as a lawful basis for processing health data.
- Balancing innovation, patient privacy, and regulatory compliance under GDPR and sector-specific rules.