Harnessing Data for the Power of Good

With the global Covid-19 pandemic firmly in the rearview mirror, life science organisations are taking a microscopic view at future opportunities, their challenges, and their risks.

The life sciences industry has undergone a profound digital transformation during the last five years, with many pharma and biotech companies experiencing high revenue growth and demand fuelled by the pandemic. Investments in cloud, high-performance computing (HPC), artificial intelligence (AI), data centre infrastructure, and big data technologies have also intensified, enabling ongoing breakthroughs in genomics, drug discovery, personalised medicine, and other areas critical to improving human health. 

However, these advancements also bring with them demand for immense computing power and data storage capacity. As life sciences organisations increasingly rely on complex data models and AI analytics, the need for robust, scalable, energy efficient and sustainable digital infrastructure has never been greater.

The Role of Data Centers in Life Sciences

There’s no doubt that the life sciences industry generates vast amounts of data. From genomic sequencing to clinical trials and medical imaging, to harness the full potential of this data, organisations require the processing power of data centres designed to handle the computational intensity of HPC, which is essential for running complex simulations, analysing large datasets, and training AI models which are foundational to modern life sciences research.

AI in particular is playing a transformative role in life sciences. For instance, large language models (LLMs) are being used to analyse vast amounts of scientific literature, predict molecular structures, and accelerate drug discovery. 

These models require two main processes: training and inference. During the training phase, the AI model learns from massive datasets, while during inference, the trained model applies its knowledge to generate actionable insights from new data. Both processes are digitally and computational-intensive and require significant resources, driving the need for scalable, energy efficient and high-density digital infrastructure.

Challenges in Scaling Digital Infrastructure

As data-intensive research continues to scale, life sciences organisations can experience a plethora of challenges. The largely unpredictable nature of research and development can make it difficult to forecast future requirements – a model that starts small can quickly scale as more data is ingested and processed, requiring additional compute power, storage, and network capacity. In many cases, organisations need to add new server racks, GPUs, or even entire data centres at short notice.

Building traditional ‘bricks-and-mortar’ facilities can be time-consuming and costly, with limited scope for expansion. Modular data centres can, therefore, offer a solution to these challenges by providing a flexible, scalable, and efficient approach to deployment. 

When delivered in prefabricated form, these pre-built facilities are deployed as fully integrated units that include everything from power and cooling systems to server racks and network equipment. Because they are pre-integrated and pre-tested, they can also become operational quickly and with minimal disruption to ongoing operations.

One of their key advantages is their level of scalability. As data processing and storage requirements grow, end-users can easily add more modules to expand capacity. This is particularly beneficial for life sciences organisations that need to scale rapidly in response to research or data demands. 

For example, as an AI model grows in complexity, more GPU power, storage, and rack space are needed. A modular data centre allows the organisation to add these resources incrementally, ensuring that they can keep up with the growing data requirements, without overbuilding.

Bringing Intelligence Closer to the Source

As AI and HPC workloads increasingly move to the edge there is also a need for infrastructure that can be deployed in remote or unconventional locations. Edge computing is especially relevant in scenarios where low latency and real-time processing are essential, such as in remote diagnostics, real-time genomic analysis, or AI-driven medical devices.

Modular data centres are also well-suited for edge deployments because they can be placed almost anywhere, from rural research facilities to urban hospitals. Their compact and often self-contained nature allows them to be installed in locations where traditional facilities would be impractical. By bringing computing power closer to the edge, life science organisations can process and analyse data in real-time, enabling faster insights and more timely decision-making.

Time-to-deployment is another critical factor, and in a fast-paced industry where research timelines can directly impact research and patient outcomes, the ability to deploy digital infrastructure quickly is a significant advantage. Prefabricated systems dramatically reduce deployment times compared to traditional builds. Since these solutions are pre-engineered and pre-tested, they can be up and running in a matter of weeks. 

This speed of deployment also translates to greater predictability. Life sciences organizations can plan their infrastructure investments with greater confidence, knowing that additional capacity can be added as needed, without the risks of delays or cost overruns. The standardisation inherent in modular solutions also ensures consistent performance and reliability, which is crucial for mission-critical applications in life sciences.

A great example of this is The Pirbright Institute, a world-leading centre of excellence for research into the control and surveillance of virus diseases of farm animals, and viruses that spread from animals to humans. The Institute wanted to transform its data centre operations to fast track its scientific research programmes and ensure it could stay abreast of new advancements in HPC and AI. 

Schneider Electric, together with our EcoXpert Partners, Advanced Power Technology (APT), developed a new containerised modular data centre to meet the Institute’s requirement for a scalable, resilient, flexible, and energy efficient infrastructure - futureproofing it for new evolutions in high-tech research equipment such as sequencers and diamond-light processes for virus analysis that can generate data sets of 700GB each. 

Sustainability and Efficiency

Sustainability is another important consideration for life sciences organisations, particularly given the industry’s increasing focus on green practices. Many data centres are designed with energy efficiency front of mind, incorporating advanced cooling systems, power management technologies, and data centre infrastructure management (DCIM) software to help reduce operational costs and align with sustainability and ESG commitments.

The ability to have primary compute and processing power close to where data is produced is also what allows life sciences organisations such as the Wellcome Sanger Institute to carry out its vital work. The volume and velocity of data makes cloud services unsuitable for the Institute’s requirements, and means the physical location of its 4.5MW data centre is critical, and is where its data and the mapped genomes are analysed by the scientific community. 

For the Sanger Institute, energy efficiency, resilience and sustainability are vital to its operations and its mission is to keep the science as sustainable as possible. Working with EfficiencyIT, an EcoXpert Partner to Schneider Electric, the Institute has used Schneider Electric’s EcoStruxure DCIM and custom APC power distribution units to reduce its data centre energy consumption by 33% - a significant energy saving.  

Powering Next-gen Life Science Research

As life sciences organisations continue to push the boundaries of research and innovation, the role of digital infrastructure becomes increasingly vital, enabling new scientific discoveries, improving patient outcomes, and advancing the future of healthcare. 

Data centres, whether deployed as on-premises or prefabricated systems offer a compelling solution for addressing the industry’s unique challenges. By using sustainable, resilient and energy efficient technologies, life science organisations can remain at the forefront of lifesaving innovation, while ensuring they’re well-equipped to meet the challenges and opportunities of a data-intensive future, with minimal environmental impact.