Edge Colocation: Just the Tonic for Healthcare and Life Sciences
Digital transformation in healthcare and life sciences presents enormous opportunities.
However, without a high-performance data center infrastructure, hospitals, research institutes and pharmaceutical companies fall short of their potential. Regional ‘edge’ colocation data centers offer an alternative that combines modern infrastructure, predictable costs, the highest security standards and flexible scalability for AI workloads.
Digitalization in healthcare is unstoppable. According to Bitkom 81 percent of physicians in Germany see it as an opportunity, but when asked about the rate of progress in the domestic healthcare sector, 83 percent believe Germany to be lagging significantly behind by international comparison. At the same time technological demands are increasing rapidly: AI-supported diagnostics and the analysis of massive datasets require computing power that conventional IT infrastructures can no longer handle. While the potential is enormous many organizations are reaching a fundamental limit: their data center architecture.
AI: Catalyst and Challenge
Artificial intelligence is fundamentally changing healthcare and life sciences. In medical imaging, algorithms analyze MRI and CT scans in a fraction of the time, supporting physicians in making more precise diagnoses. Pharmaceutical companies are using machine learning to identify promising drug candidates from millions of molecular structures to shorten development cycles.
Research institutes are using AI to decipher genomic data and develop personalized therapies. But these innovations come at a price – an infrastructural one. For example, if a university research institute trains an AI model for automated cancer detection it processes several million high-resolution images, often in the petabyte range. However, a university’s existing IT infrastructure is usually designed for administrative systems and standard applications, not for GPU-intensive calculations that run for weeks.
Similar scenarios exist in pharmaceutical research. The required computing power is often much greater than existing systems can provide. Large hospitals generate thousands of MRI and CT scans, each of which can be several gigabytes in size. This data must not only be stored securely but also be available to AI algorithms with low latency.
Gartner forecasts global IT spending will grow by 7.9 percent to $5.43 trillion, driven primarily by investments in data center infrastructure. Investments in AI-optimized servers are expected to triple the spending on traditional servers. For healthcare and life sciences this means that those who don’t invest in the right infrastructure today will be left behind tomorrow.
Compliance and Technical Complexity
The challenges in healthcare and life sciences extend far beyond mere computing power. European organizations operate within a dense web of regulations: GDPR protects sensitive patient data, the Medical Device Regulation (MDR) sets strict requirements for digital medical devices and the NIS2 Directive mandates comprehensive cybersecurity measures.
Pharmaceutical companies also face additional compliance requirements. Clinical trial data is subject to the strictest data protection regulations. Transference to data centers outside the EU is legally problematic and involves complex approval processes. The EU’s AI Regulation classifies medical AI systems as high-risk which is why organizations must establish comprehensive risk management systems, ensure data quality and guarantee human oversight.
Violations of these regulations can not only lead to substantial fines but also permanently damage the trust of patients and research partners. Added to this is the dilemma between latency and data sovereignty: While cloud solutions – often expensive – offer seemingly unlimited resources their use in healthcare frequently fails due to legal requirements. Applications such as AI-powered real-time support for surgical procedures require minimal latency, which is often difficult to guarantee with a purely cloud-based solution.
The Cost Efficiency of Colocation
Many organizations face the strategic question: on-premises data center, cloud or a hybrid approach? The answer depends on the specific requirements but for many players in the healthcare and life sciences sector, colocation is proving to be the most economically viable option.
Building and operating their own data center infrastructure pushes organizations to their financial and personnel limits. Even small edge locations require high initial investments and specialized personnel who are often in short supply. Colocation shifts this burden: Instead of investing in building technology, organizations rent rack space, power and cooling in a professional data center.
Costs are predictable from the outset: fixed monthly fees based on rack space used and power consumption. Unforeseen expenses for repairs, upgrades or infrastructure expansions are largely eliminated.
Another advantage: specialized personnel are already available. Owning your own data center requires expertise in climate control, power supply and physical security – skills that are not part of the core expertise of most healthcare and pharmaceutical organizations. With colocation the operators take on these tasks, allowing healthcare organizations to focus on their core mission: diagnostics and research.
Scalability and Flexibility
Research projects have highly variable requirements. Meeting these fluctuations with in-house infrastructure is practically impossible: either planning is done for peak loads, resulting in permanently unused capacity, or it’s designed for normal operation, preventing projects from being completed at the desired speed.
Colocation offers a practical solution. Additional racks can be provisioned within a few weeks when projects gain momentum or new AI models are introduced. If demand decreases after a project is completed capacity can be reduced again.
Furthermore, in a colocation model, hardware can be flexibly replaced without losing investments in buildings, power supply or cooling.
Certifications and Security as Standard Features
Professional colocation data centers in Germany and Europe are designed to meet the requirements of sensitive industries. Typical certifications include ISO 27001 for information security management and SOC 2 for service organization and controls. These certifications demonstrate that systematic processes for security, availability and data protection are implemented. With colocation companies utilize professional data center infrastructure while retaining control over their data.
Many providers offer additional security modules for healthcare-specific requirements. Physical data storage within the EU safeguards data sovereignty and avoids the legal gray areas associated with data transfers to third countries. The physical security of modern colocation data centers often meets bank standards: multi-stage access controls, 24/7 video surveillance, biometric access systems and strictly separated customer areas.
For pharmaceutical companies researching highly sensitive active ingredients or hospitals processing patient data, such a security architecture is indispensable. It provides the foundation for meeting regulatory requirements while simultaneously driving innovation in AI and data analytics.
Ecosystem Effects and Connectivity
A university hospital operating its AI infrastructure in a colocation data center can establish direct interconnects with research partners. Pharmaceutical companies connect their systems with specialized cloud services or biotech startups without having to transmit data over the public internet, thus reducing latency and attack surfaces.
This spatial and logical proximity enables collaborations that would otherwise be difficult to achieve across large geographical distances. Research projects that combine data from multiple institutions benefit from the ability to establish secure, high-performance data connections within the same data center.
Made for Healthcare
The geographic location of edge locations is a crucial factor. Since 2020, the Portus Data Centers (PDC) Group has offered carrier-neutral edge colocation services in Germany and neighboring regions with strategic locations in Hamburg, Munich, and Luxembourg. These locations enable customers to process data where it originates, close to their own premises.
Portus Data Centers’s services support fast data processing and low latency, thus forming the basis for a high-performance IT infrastructure for business-critical applications. The highly networked and secure data centers are independent of network operators and offer a wide range of interconnection options.
The provider’s data centers hold certifications such as ISO 27001, EN 50600 VK4 and ISO 9001. Certain locations also have additional certifications for hosting healthcare data. This allows Portus Data Centers to meet the stringent requirements of healthcare and life sciences organizations as well as the security and availability expectations of international partners.
Conclusion: Future-proofing in uncertain times
Digital transformation in healthcare and life sciences is not a question of if, but how. Organizations that continue to rely on outdated, overloaded, or unsuitable IT systems not only risk inefficient processes and high costs but also miss the opportunity to be at the forefront of medical and pharmaceutical innovation.
Colocation data centers offer clear added value: predictable costs instead of unforeseen investments, modern infrastructure without the need for in-house development, the highest security and compliance standards and the flexibility to keep pace with technological advancements. For an industry characterized by both groundbreaking technological possibilities and strict regulatory requirements, colocation can be the key to taking research and care to the next level.