Azure MLOps Within the Aridhia DRE
Discover how Aridhia integrates Azure MLOps into the DRE to streamline AI workflows, accelerate model deployment, and power secure, scalable research innovation
An Experiment in Using Offline LLMs Within a Secure Data Environment – A Breast Cancer Case Study
An experiment using offline LLMs within a Secure Data Environment to enable safe, privacy‑focused AI research.
UKRI commits £1.6Bn to AI. Aridhia CEO David Sibbald argues the real adoption barrier isn't model capability but instead data infrastructure and governance.
Running AI Agents on Sensitive Research Data: What Is Possible Today
AI agents on sensitive research data: Biomni and ClawBio inside the Aridhia DRE for biomarker analysis, variant classification, and polygenic risk scoring.
Artificial Intelligence Opportunities to Guide Precision Dosing Strategies
How AI and the Aridhia DRE enable model-informed precision dosing: integrating patient-level PK/PD data across institutions for individualised pharmacotherapy.
Utilising AI Services in a Trusted Research Environment
How Aridhia is integrating AI into the DRE — vector search for FAIR data discovery, LLM metadata summaries, and AI-assisted airlock and federated code review.
Medical Imaging and the AI Revolution Harnessed for Good
How the DRE supports medical imaging research: DICOM interoperability, AI and deep learning for image analysis, FAIR data management for global collaboration
Output review at egress: how AIRAlock combines rules and AI advisory
Egress review is where TRE protections stand or fall. AIRAlock combines a rule engine with offline AIRA advisory for consistent, auditable disclosure review.
AIRAlock egress review now supports ACRO and SACRO output checking, plus offline AI models including UK sovereign LLMs, all running inside the TRE boundary.
Reviewing 2025: AI, federation and common data standards
Aridhia advanced AI (AIRA), expanded federation, added OMOP/SDTM model support, and improved interoperability, keeping 2025 priorities firmly on track.
