Sharing practical examples of what has worked (and what hasn’t)
Highlighting key challenges and how to overcome them
Comparing tools in terms of ease of implementation, cost, and impact for smaller teams
Exploring which solutions are realistically adoptable within limited resources and existing systems
Exploring why protocol amendments, slow enrolment and late feasibility surprises are often failures of execution rather than science
Applying real-world operational evidence to trial design decisions before problems surface
Identifying execution risks early to design more predictable, scalable trials
Including a live demonstration of Aika, Biorce’s AI-driven clinical trials assistant
What changes for sponsors when EHDS, eIDAS 2.0 wallets, the Data Governance Act and the AI Act converge on clinical trial data infrastructure.
Why current consent and audit-trail architectures will not survive a participant’s right to revoke or port their data, and what the Nordic region is already building as the working answer: consent evidence ledgers, privacy-preserving computation, and neutral data altruism intermediaries
Global shifts affecting clinical trial supply and sourcing
Emerging geographic dependencies and areas of risk
What the data tells us about how the market is changing
Key trends sponsors should be preparing for
Understanding where reducing cost versus protecting patient safety creates real tension in clinical supply
Exploring trade-offs between speed cost and quality versus operational risk and trial integrity
Debating when cost reduction is justified versus when it creates unacceptable risk
Defining where efficiency gains are possible versus where quality must remain non-negotiable
Building strong cross-functional alignment before first patient in
Identifying and addressing operational risks early to avoid costly delays
Creating effective communication between sponsors, vendors and clinical supply teams
Practical lessons and common pitfalls from early-stage biotech programmes
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