iCAIRD wins Innovative Collaboration Award

Published: 29 March 2021

The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) wins the Innovative Collaboration Award at the 2021 Scotland’s Life Sciences Awards

The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) is this years’ recipient of the Innovative Collaboration Award (sponsored by Marks & Clerk) at the 2021 Scotland’s Life Sciences Awards, hosted virtually on the evening of March 24th 2021.


Held annually, the event presents awards in recognition of achievements in the life sciences industries across a range of areas, including innovation, business leadership, skills development, innovative collaboration & skills development. Attendees & nominees come from all areas of life sciences, from biology /biotechnology to academic leaders & investors.

iCAIRDs’ CTO James Blackwood accepted the award on behalf of the team, acknowledging the exceptional calibre of competition within and across the categories & paying tribute to the incredible hard work and achievements of colleagues & collaborators working across the iCAIRD Programme. Highlighting the partnerships developed across the life sciences in Scotland in the past year against the backdrop of the global COVID19 pandemic, he stated that “Scotland has a rich life sciences ecosystem which can shorten the distance between inventors and their customers. iCAIRD is a national programme which focusses that ecosystem on delivering AI solutions for digital diagnostics. Diversity, inclusivity, creativity & collaboration lie at the heart of the programme.”

The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) is one of 5 AI Centres established via funding from the UKRI Innovate UK Industrial Strategy Challenge Fund (ISCF). iCAIRD is developing the healthcare infrastructure & AI tools to support clinical decision-making, allowing new relevant insights to be gained from health data which will lead to delivery of improved outcomes for patients, through faster turnaround in diagnosis & identification of optimal treatment plans. It aims to establish a National Centre for AI research, development, evaluation and deployment in the health and social care sector in Scotland & is the only 1 of the 5 UKRI AI Centres working in both radiology & pathology.

Based at the University of Glasgow Clinical Innovation Zone at the Queen Elizabeth University Hospital Campus, iCAIRD brings together a pan-Scotland collaboration of over 16 partners from across industry, the NHS and academia. These include NHS Greater Glasgow & Clyde, NHS Grampian, NHS Lothian & NSS. Industry leadership is provided by Canon Medical Research Europe for radiology and Royal Philips for digital pathology, with technology partners EPCC; Intersystems and Nvidia. The University of Aberdeen, University of Edinburgh, University of Glasgow and University of St Andrews comprise the academic partners on iCAIRD. The programme has six current actively engaged SMEs working on clinically focussed projects: Bering Ltd, Blackford Analysis Ltd, Deep Cognito Ltd, Glencoe Software Ltd, Kheiron Medical Technologies Ltd and SeeAI Ltd. iCAIRDs SME partners are leading on key exemplar projects focussing on development of AI in radiology for (i) acute stroke treatment assessment, (ii) breast screening, (iii) chest X-Ray triage & (iv) COVID19 diagnostic/treatment assessment triage. In pathology, the teams are working to build Scotlands’ future capability in pathology healthcare by (i) fully digitising pathology at NHS GGC, (ii) establishing a digital national pathology research archive service & (iii) developing AI tools for gynaecological cancer screening.

Key achievements on the Programme to date include deployment of a national secure analytical machine learning platform (SHAIP) in 2 iCAIRD hubs in Glasgow and Aberdeen Safe Havens & extraction of imaging & non-imaging data at scale from local and national NHS data repositories. This is deidentified to safe guard patient privacy and enable the SMEs to undertake machine learning training and validation to develop Artificial Intelligence tools for clinical decision support.

Enquiries: ali.howard@glasgow.ac.uk or elizabeth.mcmeekin@glasgow.ac.uk / 0141 330 6557 or 0141 330 4831

First published: 29 March 2021

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