WHAT WE FOCUS ON IN OUR SPECIALIST RESEARCH
Our research spans today’s most pressing challenges and tomorrow’s emerging opportunities in AI and digital health. Some of these technologies are already transforming care, while others are still being developed. Across all our work, we aim to ensure that AI is safe, effective, equitable and inclusive, sustainable, technically robust, and affordable for health systems.
Research Projects
Recent projects have explored how to safely implement AI for diabetic eye screening, when large language models become medical devices, what it takes for NHS organisations to be AI ready, and how regulation can remain both protective and enabling. Together, these initiatives reflect our mission to bring innovators, regulators, clinicians, and patients together to shape smarter, more adaptive pathways for safe and impactful AI in healthcare.
Hardian Regulatory Intelligence Platform (HaRi)
HaRi, created by Hardian Health, is a platform designed to enhance transparency in medical device regulation by consolidating fragmented global data into a unified, contextualised view. It aggregates device registrations, safety data, NHS procurement information, and peer-reviewed evidence from sources like Public Access Registration Data Base (PARD), UK, Food and Drug Administration (FDA), USA, The European Database on Medical Devices (EUDAMED), and PubMed, enabling searches across the UK, Europe, USA, Canada, and Australia.
Borderline Manual for Software as a Medical Device (SaMD)/ AI as a Medical Device (AIaMD)
Developing a manual to support innovators in knowing when an AI health technology falls under medical device regulation (in partnership with the MHRA). This project will help improve clarity, compliance and efficiency, accelerating innovation timelines and patient safety. Stay tuned for more updates as this work progresses.
AI Readiness Checklist
This project is developing a comprehensive tool to support NHS health providers in assessing and enhancing their readiness to deploy AI health technologies. The tool includes four key functions:
- Gating – Enables providers to self-assess their AI readiness before procurement and implementation.
- Growing – Identifies gaps in technical maturity and guides digital preparedness improvements.
- Governance – Offers internal and external assurance that AI is deployed safely and responsibly, aligning with regulatory expectations.
- Generalisability – Promotes consistent standards across NHS sites to support scalable, safe, and peer-supported AI adoption.
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Qualification and classification of Large Language Models
This project explores how large language models (LLMs) used in healthcare can be assessed under existing medical device regulations. By mapping common health-related LLM use cases from published literature, the team will collaborate with regulatory experts to craft Intended Use Statements and apply current regulatory frameworks to determine risk classifications. The goal is to identify whether LLMs can be regulated under existing rules, understand what factors influence their risk level, and provide policy recommendations to key regulatory bodies including MHRA, Care Quality Commission, National Institute for Health Care Excellence, and National Health Service, England.
Optimising SDEs for AI Health Technologies
This project aims to develop and share best practices for the provision of Secure Data Environments (SDEs) to support the development and testing of AI diagnostics within the NHS and beyond. It focuses on defining requirements across key areas including innovation, regulatory compliance, patient safety, equity, cybersecurity, and data privacy. The goal is to ensure that SDEs are optimally designed to enable safe, effective, and equitable AI innovation in healthcare.
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Primary Research Objectives
Identification of Need
We help Innovators know what to build, by helping the NHS ‘demand signal’, saying what patients and the NHS needs and are willing to pay for.
Project Design
We help Innovators know how to design their products to meet the needs of patients, health professionals and the wider NHS.
Technical Development
We help regulators address technical aspects of AI development, and help them ensure their processes balance the unique opportunities and risks.
Pre-market Evaluation
We work with innovators and regulators to design efficient but robust systems of evaluation to check the product is ready for routine use.
Post-market Surveillance
We design ways to assess that a product is continuing to work safely.
Updates & Withdrawals
We help innovators and the NHS decide when to replace a product, and how to do so safely.