WELCOME TO THE DATA STAGE

WHAT TO EXPECT: 

AI is only as powerful as the data behind it.

The Data Track goes where the real bottlenecks are - fragmented systems, broken interoperability, and datasets that were never built for AI. Discover how the industry's most advanced data teams are solving these problems to unlock deployment at enterprise scale.

The organisations that fix the data problem will define the next generation of AI in life sciences.

DATA STAGE SPEAKERS:

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WHO ATTENDS:

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Sanofi
Bristol Myers Squibb
AstraZeneca
Pfizer
Roche
Merck
AbbVie
J&J

Expect candid discussions on:

Building AI-ready data infrastructure across R&D

Harmonising multimodal datasets for scalable AI

Data interoperability and integration at enterprise scale

Improving data quality, governance, and standardisation

Advanced analytics driving faster drug discovery and development

Breaking down silos across research, clinical, and operational data

Real-world data integration and AI-driven insight generation

Scalable architectures supporting end-to-end AI adoption in life sciences

Built for the teams turning fragmented data into AI-ready infrastructure.

Build the foundations required for scalable AI

Discover how leading organisations are modernising data infrastructure to support reliable, enterprise-scale AI across research, clinical development, and operations.

Improve data readiness and unlock higher-quality insights

Leave with practical strategies for improving interoperability, harmonising fragmented datasets, and increasing the quality and usability of data across the AI lifecycle.

Turn disconnected data into operational advantage

Understand how organisations are integrating multimodal data, advanced analytics, and governance frameworks to accelerate decision-making and support faster drug discovery and development.

FAQ

The Data stage is designed for leaders across data, digital, AI, informatics, R&D, clinical operations, and enterprise technology within pharma, biotech, healthcare, and life sciences organisations.

If you are responsible for improving data readiness, scaling AI infrastructure, or connecting fragmented systems across the organisation, this track is built for you.

Discover how organisations are building the data foundations required for scalable AI adoption across drug discovery and development.

Sessions focus on the operational realities of improving data quality, integrating multimodal datasets, modernising infrastructure, and enabling advanced analytics across the pharmaceutical lifecycle.

Most data events focus on theory, tooling, or future-state AI ambitions.

This track focuses on operational execution - what organisations are doing right now to make data usable, interoperable, scalable, and AI-ready across complex R&D environments.

Less hype. More infrastructure, integration, and deployment.

Both.

The Data stage bridges executive strategy with operational implementation - covering infrastructure decisions, governance frameworks, integration challenges, scalability, and the practical requirements for supporting AI across R&D and clinical development.

Yes.

The organisations building scalable AI infrastructure across life sciences will be in the room - sharing how they are improving data readiness, integrating complex datasets, and enabling AI deployment across research and development environments.

The focus is measurable operational progress, not theoretical transformation.