Blog & Insights
Cloud Insights for Life Sciences Leaders
Expert perspectives on cloud architecture, AI, security, and cost optimisation for regulated industries.
Latest Posts
The AI Revolution in Drug Discovery: What’s Actually Happening Behind the Curtain
Exploring how generative AI is transforming drug discovery, with practical guidance on building scalable and secure AI infrastructure in the cloud.
FinOps for Life Sciences: Cut AWS Costs Without Cutting Corners
Life sciences organisations often overspend on AWS by 30–50% due to research workload variability and compliance-driven conservatism. FinOps — the cloud financial management discipline — provides the framework to achieve material cost savings without compromising validated system integrity or regulatory compliance.
Why Cloud Security in Life Sciences Feels Like Holding an Umbrella in a Hurricane
Comprehensive guide to implementing continuous cloud security monitoring and compliance for biotech and pharmaceutical organizations.
How Biotech Companies Are Using Generative AI on AWS in 2026
Generative AI is moving from pilot to production in biotech and pharmaceutical organisations — accelerating drug discovery, automating regulatory document generation, and transforming clinical data analysis. AWS's AI/ML stack, led by Bedrock and SageMaker, provides the secure, scalable foundation. This article explores the real use cases, the tools being used, and the governance requirements for regulated environments.
The Life Sciences Leader's Guide to AWS Cloud Migration in the UK
Cloud migration in life sciences is not just an IT project — it's a validated, regulated change to your operating environment. This guide covers the end-to-end process for migrating life sciences workloads to AWS in the UK, from initial discovery through to qualified production operation.
CI/CD Pipelines for Life Sciences: Balancing Speed and Compliance
CI/CD in life sciences is not incompatible with GxP compliance — it requires adapting. 'Validated DevOps' integrates automated testing as validation evidence, formalised pipeline qualification, and audit-trail-generating deployments. Done right, it accelerates delivery while strengthening the regulatory record.
AWS vs Azure for Life Sciences: A Regulated Industry Comparison
AWS and Azure both support regulated life sciences workloads, but differ significantly in their compliance documentation, partner ecosystems, and GxP-specific tooling. This comparison helps IT leaders and QA directors make an informed cloud platform decision.
The Definitive Guide to GxP Compliance in AWS Cloud (2026 edition)
GxP compliance on AWS requires a validated, documented approach to cloud infrastructure — covering access controls, audit trails, change management, and data integrity. This guide explains exactly what GxP means in a cloud context, what AWS provides, and what your organisation must manage to remain compliant.
Why Manual Infrastructure Still Haunts So Many Life Sciences Teams
How Infrastructure as Code transforms manual deployment processes into repeatable, auditable, and scalable systems for life sciences research.
The Multi-Cloud Question: Ambition, Reality and the Occasional Migraine
Exploring the benefits, challenges, and practical considerations of multi-cloud architectures for life sciences organizations.
Building AI in Life Sciences: Why Security Has to Be Baked In, Not Bolted On
Building secure AI/ML pipelines that meet GxP, HIPAA, and SOC 2 compliance requirements while maintaining agility and innovation.
Why Life Sciences Compute Costs Keep Blowing Holes in Budgets — and How Graviton Changes the Equation
Discover how AWS Graviton processors can reduce cloud costs by up to 50% while improving performance for computational biology and AI workloads.
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