For researchers, data custodians, and life sciences teams navigating AI adoption in sensitive data environments. Technical deep-dives, governance perspectives, and practical guidance from the Aridhia team on using AI responsibly within a Trusted Research Environment.
AI agents on sensitive research data: Biomni and ClawBio inside the Aridhia DRE for biomarker analysis, variant classification, and polygenic risk scoring.
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.
Aridhia’s Aira framework delivers secure offline AI in the DRE, enabling compliant, auditable model use for healthcare research without exposing sensitive data.
Discover how Aridhia integrates Azure MLOps into the DRE to streamline AI workflows, accelerate model deployment, and power secure, scalable research innovation
An experiment using offline LLMs within a Secure Data Environment to enable safe, privacy‑focused AI research.
How AI and the Aridhia DRE enable model-informed precision dosing: integrating patient-level PK/PD data across institutions for individualised pharmacotherapy.
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.
How the DRE supports medical imaging research: DICOM interoperability, AI and deep learning for image analysis, FAIR data management for global collaboration
