Queen Mary and Research Grid collaboration trials AI technology to improve efficiency in clinical trials
A project led by Queen Mary University of London, in partnership with Research Grid, Barts Health NHS Trust and the Royal Academy of Engineering, has successfully trialled a new AI-driven approach to automate clinical trial data entry, that could dramatically reduce the time and cost of running clinical trials.
Photo credit: Art Stock Creative
The research was undertaken on a large cardiac imaging study which had previously been undertaken by Queen Mary University of London investigators.
Over 80% of medical research data is still entered manually. In research institutions, highly qualified research staff spend hours on repetitive, often manual data entry. This slow, costly process contributes to the 90% of clinical trials failing to meet timelines, delaying life-changing medical advancements.
The challenges addressed in the Queen Mary study included a large volume of data entry that meant long processing times, increased costs, and a heavy administrative burden. Over 600 patients in the study had 26-30 pages of paper-based source data for their visits. Approximately 5% of every 1200 entries of data were affected by human error. Also, an analysis of staff time estimated a spend of £1.1 million and upwards of 24,000 hours on data entry alone. Research Grid’s algorithm tackled these bottlenecks by automating the data entry, including handwritten text, data, and images, showing that their proprietary AI can be used to auto-digitise, structure, and run quality assurance checks of over a year of paper-based patient data in seconds.
While AI systems have already found a home in industries like finance and insurance, their use in clinical trials has been limited by the complex and sensitive nature of medical records. This Queen Mary study illustrated that purpose-built AI automation can be introduced safely and effectively in clinical trials, academic research, and a wider variety of use cases.
Professor Anthony Mathur, Study Lead and Centre Lead for the Centre for Cardiovascular Medicine and Devices at Queen Mary’s William Harvey Research Institute, said:
“This technology has the potential to dramatically improve the efficiency and accuracy of how we perform clinical trials, and clearly emphasises the role of digital technologies in supporting research workflows. I look forward to the future of this technology.”
Beyond trials, the technology could help hospitals and healthcare providers digitise years’ worth of records, making it easier to track patient outcomes and improve services. With healthcare systems under increased pressure to modernize and increased financial and time constraints, the deployment of state-of-the-art AI at Queen Mary marks a major step forward in research to eliminate outdated manual processes.