The HPC & AI Infrastructure Stage is designed for infrastructure leaders, platform engineers, AI engineering teams, enterprise architects, IT leaders, computational scientists, and technology decision-makers across pharma, biotech, healthcare, and life sciences.

If you are responsible for enabling scalable AI workloads, supporting high-performance compute environments, or building AI-ready infrastructure, this stage is built for you.

Discover how organisations are building and optimising the infrastructure required to support AI across drug discovery and development.

Sessions focus on practical deployment strategies, HPC environments, GPU infrastructure, hybrid cloud orchestration, inference optimisation, storage architectures, and the operational realities of scaling AI workloads.

Most infrastructure events focus on general-purpose AI workloads.

This stage focuses specifically on the infrastructure challenges facing life sciences organisations — where AI workloads must support complex biological data, large-scale modelling, regulated environments, and demanding research pipelines.

Less theory. More operational scale.

The HPC & AI Infrastructure Stage focuses on the systems enabling enterprise-scale AI adoption, including:

• HPC architectures for AI workloads
• GPU acceleration and compute optimisation
• AI-ready storage and networking
• Hybrid cloud infrastructure strategies
• AI orchestration and workload management
• Training and inference optimisation
• Infrastructure sustainability and energy efficiency
• Scaling AI environments across R&D and clinical operations

Yes.

The organisations building AI infrastructure at scale will be in the room — sharing how they are supporting high-performance AI workloads, managing compute demand, optimising infrastructure efficiency, and operationalising AI across research environments.

The focus is measurable operational execution, not theoretical architecture.